The coronavirus pandemic of the past several years has had a profound impact on all aspects of life, including resource utilization. One notable example is the increased demand for freshwater, a lifeblood of our planet, on the other hand, the smart city vision aims to attain a smart water management goal by investing in innovative solutions such as recycled water systems. However, the problem lies in the public’s sentiment and willingness to use this new resource which discourages investors and hinders the development of this field. Therefore, in our work, we applied sentiment analysis using an extended version of the fuzzy logic and neural network model from our previous work, to find out the general public opinion regarding recycled water and to assess the effects of sentiments on the public’s readiness to use this resource. Our analysis was based on a dataset of over 1 million text content from 2013 to 2022. The results show, from spatio-temporal perspectives, that sentiment orientation and acceptance- behavior towards using recycled water have increased positively. Additionally, the public is more concerned in areas driven by the smart city vision than in areas of medium and low economic development, where investment in sensibilization campaigns is needed.
ICT Mediated Community Water Management & Decision MakingRajat Kumar
Community based water resource management is a valuable tool that strives to sustain and improve environmental health through a natural resource management approach that integrates locally driven initiatives. It seeks to bring together stakeholders to identify issues, needs & strategies; integrate social, economic & ecological concerns towards generating comprehensive solutions. The increasing penetration of Information & Communication Technologies (ICTs) presents a great potential for communities to connect with government officials, policy makers and other relevant stakeholders that would have; under normal circumstances; been inaccessible for them. What is important is that this ease of sharing information through ICTs should also decrease the time taken for members in a community to acquire equal knowledge about the issue at hand and to encourage faster collaboration & quicker and more informed decision making about these community water resources.
This paper seeks to examine this claim by examining literature and feedback from the “Neerjaal” portal, developed by the Digital Empowerment Foundation in association with Social Work Resource Centre and the Barefoot College, in Rajasthan.
Artificial Intelligence And Water Cycle ManagementJennifer Daniel
This document discusses how artificial intelligence can help manage water resources more effectively by processing large amounts of data. AI applications have potential in areas like monitoring water quality and quantity, detecting illegal dumping or changes in water bodies, and improving the efficiency of water treatment plants. By using sensors and data from smart homes, AI systems can also help optimize water distribution networks and consumption patterns. Overall, AI can support more sustainable water management through integrated analysis of environmental information across different sectors.
A Review Paper On Water Resource ManagementSabrina Baloi
This document summarizes key concepts in water resource management. It discusses how water management structures can change water regimes and impact stakeholders. It also notes that while water projects aim to provide economic benefits, some populations have inadequate access to safe water for basic needs. The document then reviews experts' concepts on water management and financing allocations. It identifies areas for further addressing such as governance, accountability, gender, and targeting of aid and sector budgets. Finally, it discusses developing a framework for water management that is measurable, affordable and applicable globally.
The influence-of-monitoring-and-evaluation-on-water-project-performance-in-mi...oircjournals
In a 2010 study by World Bank, it was evidenced that people lack proper services because systems fail, often because not enough resources are invested to appropriately build and maintain them, and also because of the stress that the fast growing population places on the existing infrastructure. According to Migori county report card in 2016, it was established that there was lack of continuity in water projects commenced and that construction of water projects does not help if they fail after a short time. This study analyzed the influence of community participation on water project performance in Migori County. The study specifically; examined influence of communication, management skill, technology and monitoring and evaluation on water project performance. The conceptualization of the study was guided by Resource dependence, the theory of Change, System theory and the Theory of Constraints. The study applied descriptive approach through survey design. The target population comprised of 228 stakeholders and water service company staffs working on water project in Migori County. The sample size of the study was 145 respondents arrived at using a 1967 Taro Yamane’s formula of sample size determination. Data analysis was done by descriptive statistics. The study revealed that monitoring and evaluation is statistically significant influence on water project performance (β=0.152, p<0.05). The study concluded that project managers have adequate and experience in project management. Projects have clear documentation and the company has project progress reports. The study recommends that county government should empower project managers at County levels to improve planning and implementation towards the goal of sustaining water projects benefits, Non-Governmental Organizations to evaluate the performance and sustainability of water projects vis a vis the community participation at all stages of the project cycle.
Socio economic analysis of the interventions aimed at improvingAlexander Decker
This document summarizes a study on the socio-economic analysis of water and sanitation interventions in rural areas of Abbottabad, Pakistan. It employed a cross-sectional study design using interviews, questionnaires and focus groups. Respondents were generally satisfied with the quality and cost of water delivery but a top-down implementation approach was still used. A cost-benefit analysis found the economic benefits of the interventions to be good. The study assessed the demographic characteristics, wealth rankings, existing water/sanitation infrastructure, and roles of stakeholders in the target communities. Overall, the interventions improved access to water but supply was still insufficient and a community-engaged approach was needed.
A Decision Support System for the Design and Evaluation of Durable Wastewater...AM Publications
To develop the waste water solutions challenging task. To design sustainable wastewater solution requires information about new ideas, new systems and latest technology. Generally it is assumed that, decision making needs to involve field experts and engineers to define values and brainstorms solution. This paper describes a decision support system model that is designed to help community planners to identify the solution which balance the environmental, economic and social needs. System will be scalable, adaptable and flexible. Our decision support system will take modular description of components and description of community constraints, suggest the design of alternative waste water system, and facilitates evaluating how well each design satisfies the given constraints. Decision support system will give alternatives with visualization of the effect of various trade-offs and their effect in the relation of the community’s goals.
A Decision Support System for the Design and Evaluation of Durable Wastewater...AM Publications
To develop the waste water solutions challenging task. To design sustainable wastewater solution requires information about new ideas, new systems and latest technology. Generally it is assumed that, decision making needs to involve field experts and engineers to define values and brainstorms solution. This paper describes a decision support system model that is designed to help community planners to identify the solution which balance the environmental, economic and social needs. System will be scalable, adaptable and flexible. Our decision support system will take modular description of components and description of community constraints, suggest the design of alternative waste water system, and facilitates evaluating how well each design satisfies the given constraints. Decision support system will give alternatives with visualization of the effect of various trade-offs and their effect in the relation of the community’s goals.
ICT Mediated Community Water Management & Decision MakingRajat Kumar
Community based water resource management is a valuable tool that strives to sustain and improve environmental health through a natural resource management approach that integrates locally driven initiatives. It seeks to bring together stakeholders to identify issues, needs & strategies; integrate social, economic & ecological concerns towards generating comprehensive solutions. The increasing penetration of Information & Communication Technologies (ICTs) presents a great potential for communities to connect with government officials, policy makers and other relevant stakeholders that would have; under normal circumstances; been inaccessible for them. What is important is that this ease of sharing information through ICTs should also decrease the time taken for members in a community to acquire equal knowledge about the issue at hand and to encourage faster collaboration & quicker and more informed decision making about these community water resources.
This paper seeks to examine this claim by examining literature and feedback from the “Neerjaal” portal, developed by the Digital Empowerment Foundation in association with Social Work Resource Centre and the Barefoot College, in Rajasthan.
Artificial Intelligence And Water Cycle ManagementJennifer Daniel
This document discusses how artificial intelligence can help manage water resources more effectively by processing large amounts of data. AI applications have potential in areas like monitoring water quality and quantity, detecting illegal dumping or changes in water bodies, and improving the efficiency of water treatment plants. By using sensors and data from smart homes, AI systems can also help optimize water distribution networks and consumption patterns. Overall, AI can support more sustainable water management through integrated analysis of environmental information across different sectors.
A Review Paper On Water Resource ManagementSabrina Baloi
This document summarizes key concepts in water resource management. It discusses how water management structures can change water regimes and impact stakeholders. It also notes that while water projects aim to provide economic benefits, some populations have inadequate access to safe water for basic needs. The document then reviews experts' concepts on water management and financing allocations. It identifies areas for further addressing such as governance, accountability, gender, and targeting of aid and sector budgets. Finally, it discusses developing a framework for water management that is measurable, affordable and applicable globally.
The influence-of-monitoring-and-evaluation-on-water-project-performance-in-mi...oircjournals
In a 2010 study by World Bank, it was evidenced that people lack proper services because systems fail, often because not enough resources are invested to appropriately build and maintain them, and also because of the stress that the fast growing population places on the existing infrastructure. According to Migori county report card in 2016, it was established that there was lack of continuity in water projects commenced and that construction of water projects does not help if they fail after a short time. This study analyzed the influence of community participation on water project performance in Migori County. The study specifically; examined influence of communication, management skill, technology and monitoring and evaluation on water project performance. The conceptualization of the study was guided by Resource dependence, the theory of Change, System theory and the Theory of Constraints. The study applied descriptive approach through survey design. The target population comprised of 228 stakeholders and water service company staffs working on water project in Migori County. The sample size of the study was 145 respondents arrived at using a 1967 Taro Yamane’s formula of sample size determination. Data analysis was done by descriptive statistics. The study revealed that monitoring and evaluation is statistically significant influence on water project performance (β=0.152, p<0.05). The study concluded that project managers have adequate and experience in project management. Projects have clear documentation and the company has project progress reports. The study recommends that county government should empower project managers at County levels to improve planning and implementation towards the goal of sustaining water projects benefits, Non-Governmental Organizations to evaluate the performance and sustainability of water projects vis a vis the community participation at all stages of the project cycle.
Socio economic analysis of the interventions aimed at improvingAlexander Decker
This document summarizes a study on the socio-economic analysis of water and sanitation interventions in rural areas of Abbottabad, Pakistan. It employed a cross-sectional study design using interviews, questionnaires and focus groups. Respondents were generally satisfied with the quality and cost of water delivery but a top-down implementation approach was still used. A cost-benefit analysis found the economic benefits of the interventions to be good. The study assessed the demographic characteristics, wealth rankings, existing water/sanitation infrastructure, and roles of stakeholders in the target communities. Overall, the interventions improved access to water but supply was still insufficient and a community-engaged approach was needed.
A Decision Support System for the Design and Evaluation of Durable Wastewater...AM Publications
To develop the waste water solutions challenging task. To design sustainable wastewater solution requires information about new ideas, new systems and latest technology. Generally it is assumed that, decision making needs to involve field experts and engineers to define values and brainstorms solution. This paper describes a decision support system model that is designed to help community planners to identify the solution which balance the environmental, economic and social needs. System will be scalable, adaptable and flexible. Our decision support system will take modular description of components and description of community constraints, suggest the design of alternative waste water system, and facilitates evaluating how well each design satisfies the given constraints. Decision support system will give alternatives with visualization of the effect of various trade-offs and their effect in the relation of the community’s goals.
A Decision Support System for the Design and Evaluation of Durable Wastewater...AM Publications
To develop the waste water solutions challenging task. To design sustainable wastewater solution requires information about new ideas, new systems and latest technology. Generally it is assumed that, decision making needs to involve field experts and engineers to define values and brainstorms solution. This paper describes a decision support system model that is designed to help community planners to identify the solution which balance the environmental, economic and social needs. System will be scalable, adaptable and flexible. Our decision support system will take modular description of components and description of community constraints, suggest the design of alternative waste water system, and facilitates evaluating how well each design satisfies the given constraints. Decision support system will give alternatives with visualization of the effect of various trade-offs and their effect in the relation of the community’s goals.
This document discusses the development of an improved hydrological information system (HIS) in India using emerging information technologies. It notes that existing Indian HIS are inadequate and lack integration. The Hydrology Project aims to develop comprehensive and reliable HIS by standardizing data collection, establishing computerized databases, and ensuring sustainability. The improved HIS will provide reliable hydrological data to support long-term planning, management, and research on water resources development and use in India.
IoT Based Smart Water Monitoring and Distribution System For An ApartmentsYogeshIJTSRD
This document presents a smart water monitoring and distribution system for apartments using IoT. The system addresses water wastage by measuring flow rates and scheduling water supply. It can monitor the quality and quantity of water distributed to households using pH and flow sensors. An Arduino board implements the system using sensors to continuously monitor water levels. The system aims to ensure water quality and reduce wastage using IoT technologies like sensors and cloud-based monitoring. It is intended for use in densely populated residential buildings to survey individual water usage and detect leaks or contamination issues.
ICT solutions for highly-customized water demand management strategiesSmartH2O
1) Smart metering technologies and big data analytics can help water utilities better understand residential water usage patterns and identify different consumption profiles.
2) Gamification approaches, like the SmartH2O project's "DropTheQuestion" app, show potential for inducing behavioral change and reducing household water consumption. Preliminary results from SmartH2O indicate water savings of 10% on average.
3) Further analysis of smart meter data from over 11,000 households in Valencia, Spain identified common daily, weekly, and hourly water usage patterns and helped classify households into consumption categories from very high to low users.
Development of an Open-Source Water Consumption Meter for HousingIEREK Press
This article reports on the project "Design and development of water and gas P.L. measurement devices in the housing: an approach to sustainable consumption in Mexico", prepared at the Metropolitan Autonomous University in the Department of the Environment, whose objective was to develop a device to measure water consumption in the housing, which allows users to know their spending and can make decisions in favor of efficiency through the reduction of water use in household activities. The meter is made up of open source, programmable or reconfigurable software, which receives the signal from a water flow sensor and a casing designed to contain the hardware and facilitate the user's installation. Both the hardware and the casing can be purchased, downloaded, manufactured and assembled at home (Do It Yourself). As specific results were obtained: hardware programming and housing design and as a final result: the assembly of the functional prototype with which measurements of water consumption were made in a housing in Mexico. With this work we conclude that through the development of new accessible and common measurement technologies for the users of a house, it will be possible to promote efficiency in the use of natural resources in cities, increasing availability and promoting a more sustainable urban development.
Development of an Open-Source Water Consumption Meter for HousingIEREK Press
This article reports on the project "Design and development of water and gas P.L. measurement devices in the housing: an approach to sustainable consumption in Mexico", prepared at the Metropolitan Autonomous University in the Department of the Environment, whose objective was to develop a device to measure water consumption in the housing, which allows users to know their spending and can make decisions in favor of efficiency through the reduction of water use in household activities. The meter is made up of open source, programmable or reconfigurable software, which receives the signal from a water flow sensor and a casing designed to contain the hardware and facilitate the user's installation. Both the hardware and the casing can be purchased, downloaded, manufactured and assembled at home (Do It Yourself). As specific results were obtained: hardware programming and housing design and as a final result: the assembly of the functional prototype with which measurements of water consumption were made in a housing in Mexico. With this work we conclude that through the development of new accessible and common measurement technologies for the users of a house, it will be possible to promote efficiency in the use of natural resources in cities, increasing availability and promoting a more sustainable urban development.
Cities around the world are facing challenges brought about by rapid increases in population and geographic spread, which places greater pressure on infrastructure and services. Climate change impacts, including rising sea level, more frequent and severe storms, coastal erosion and declining freshwater sources will likely exacerbate these urban issues, in particular in poor and vulnerable communities that lack adequate infrastructure and services.
Globally, the impacts of climate change on urban areas have received less attention than on rural areas where poverty levels are higher and populations depend directly on climate-sensitive livelihoods. However, more than 50% of the world’s population currently lives in cities. By 2050, this figure is expected to increase to 70%, or 6.4 billion people, and Asian cities are likely to account for more than 60% of this increase. Urban areas are the economic powerhouses that support both the aspirations of the poor and most national economies. Furthermore, urban residents and the economic activity they generate depend on systems that are fragile and often subject to failure under the combination of climate and development pressures. If urban systems fail, the potential direct and indirect impacts of climate change on urban residents in general, on poor and vulnerable populations, and on the wider economy is massive. As a result, work on urban climate resilience is of critical importance in overall global initiatives to address the impacts of climate change.
The Asian Cities Climate Change Resilience Network (ACCCRN) works at the intersection of climate change, urban systems and social vulnerability to consider both direct and indirect impacts of climate change in urban areas.
A Model of (P-GIS) for Hydraulic Protection Dams in Northern Moroccoijait
This document summarizes a study that used a participatory geographic information system (P-GIS) to delineate protection zones around the Ibn Battouta dam in northern Morocco. The study combined GIS software, descriptive data collected in the field, and a data type model to analyze factors impacting the delineation of three protection zones around the dam based on water quality and human activities. The resulting P-GIS model created a spatial data management system and delineated protection areas in an innovative way to safeguard the dam's water resources and identify areas requiring action to reduce pollution.
A MODEL OF (P-GIS) FOR HYDRAULIC PROTECTION DAMS IN NORTHERN MOROCCOijait
To strengthen the quality of information, inclusion and implementation of continuous link between different categories of actors by mobilizing P-GIS as tools for participation and methodological aid to decision-making, and help to better understanding of environmental issues and challenges related
to climate change, allowing regional authorities to better analyze and process. So what we've seen, that the conventional GIS does not include certain information such as social exclusion, displacement, narrative conflicts of use of land and water, cultural stories, local politics. Hence the need to find an effective method to circumvent these problems.
So this study is based on a software solution that is supported on the geographic information system (GIS) coupled with the participatory model to give the (P-GIS). By manipulating various GIS software el descriptive data collected directly from the study area of the dam Ibn Battouta. A Data Type Model was generated to model the flow of data and related information. The delineation of protection zones will then contribute to the superposition, by adding each of the identified factors. The result of this study has created a multi-source spatial data management. This produces what is appalled the demonstration model GIS-remote sensing.'' It is based on certain factors that use parameters observed in the field and the information collected from censuses.
The document provides an overview of city projects undertaken by the Asian Cities Climate Change Resilience Network (ACCCRN) across 10 cities in Asia. It discusses ACCCRN's goal of building climate resilience in cities and outlines six key characteristics of urban resilience: flexibility, redundancy, safe failure, responsiveness, resourcefulness, and learning. It also identifies 10 urban climate change resilience action areas that the city projects address, such as water and drainage systems, land use planning, and health systems. The document then provides brief summaries of 32 city projects funded by ACCCRN, highlighting the climate risks and urban issues each project aims to tackle.
Community Participation Framework for Water Utilization in Jammu Region (J&K)...scmsnoida5
In the current global scenario water management
is the prime mover of economic growth and is
vital to the sustenance of a modern economy.
Future economic growth also, crucially depends
on the long term availability of perennial water
sources specially the ones that are affordable,
accessible and environment friendly. The analysis
of data from the Economic Survey of India,
2012-13, shows that energy and water demand
is on the rise in India and this is due to increase
in the development efforts and population
growth. Therefore, the present study will focus
on what has been achieved and what needs to
be achieved with reference to water management
through community participation in Jammu and
Kashmir State by understanding the experiences
from Singapore. Therefore, the study will be
utilizing the references and applying the research
by utilizing the knowledge and generating
a viable framework for the Jammu region,
which would be a little contribution towards proposing a Sustainable Water management
policy framework for Jammu and Kashmir
State by involvement of community through
non government organizations and self help
groups. In this regard, the exploration of water
renewal through Public Utilities Board (PUB),
Singapore’s national water agency gives an
insight to the study by providing an ideal model of
community participation which can be adopted
in Jammu region of state of J&K.
This document provides a research proposal to analyze citizen perception of participation in governance of urban water supply systems in Bangalore, India. The study will explore how the Bangalore Water Supply and Sewerage Board (BWSSB) allows citizen participation and the role of information and communication technologies (ICT) in improving participation. It reviews literature on the importance of citizen involvement in decision making for equitable and sustainable water systems. The conceptual framework assesses current conditions, explores areas of citizen participation and ICT applications used, analyzes generated data, and proposes verifying participation through a cyclic approach to address changing urban dynamics.
This document provides a research proposal to analyze citizen perception of participation in governance of urban water supply systems in Bangalore, India. The study will explore how the Bangalore Water Supply and Sewerage Board (BWSSB) allows citizen participation and the role of information and communication technologies (ICT) in improving participation. It reviews literature on the importance of citizen involvement in decision making for equitable and sustainable water systems. The conceptual framework assesses current conditions, explores areas of citizen participation and ICT applications used, analyzes generated data, and proposes verifying participation through a cyclic approach to address changing urban dynamics.
This document discusses guidelines for sustainable urbanization. It recommends that cities adopt a high-density centralized layout to minimize environmental footprint and encourage public transportation. Environmental technologies should utilize natural systems to purify water and generate energy on-site. Successful sustainable cities require collaboration among stakeholders and policymakers to address challenges through coordinated regional planning.
Assessing the resilience of a city in relation to its healthy urban systems: ...Dr.Hayam alsa'atee
This research investigates the relationship between city resilience and its urban
systems. The study determines the efficiency of a healthy urban system as one of a main
characteristic in achieving a compatible resilient city. Most of the current studies are theoretical
and suggest pathways and procedures that are beyond virtual practices. Healthy urban systems
are suggested to link human well-being with the effectiveness of the city infra-structure and
municipal services.
Assessing the resilience of a city in relation to its healthy urban systems: ...Dr.Hayam alsa'atee
This research investigates the relationship between city resilience and its urban
systems. The study determines the efficiency of a healthy urban system as one of a main
characteristic in achieving a compatible resilient city. Most of the current studies are theoretical
and suggest pathways and procedures that are beyond virtual practices. Healthy urban systems
are suggested to link human well-being with the effectiveness of the city infra-structure and
municipal services. These services are associated with the drinking water supply, sewage
disposal, garbage system, and adequacy of the transport system.
The document discusses the growing problem of water pollution worldwide and proposes a multi-pronged solution. It suggests creating a fund to educate young professionals in developing countries about water treatment techniques. It also proposes establishing community water centers to oversee local sanitation projects and offering incentives for waste water treatment programs and good water management practices among communities and industries. The goal is to increase technical knowledge, encourage local initiatives, raise awareness from an early age, and incentivize sustainable practices to address water pollution issues.
Green Solutions for Water and Waste is one of VTT’s Spearhead Programmes that has been running since 2011. This publication presents some of the research highlights from the first half of the programme. Focal areas of this programme have been water treatment technologies and waste management. In water treatment the research has focused in enzyme and membrane technologies and membrane surface treatment methods, water monitoring technologies, and sludge treatment. Regarding waste treatment methods and technologies the focus has been in refining organic waste and conceptualising new business on valorisation of waste streams.
Tamimi - socioeconomic dimension of water policyWANA forum
This document discusses the socioeconomic dimensions of water policy and integrated water resource management (IWRM). It addresses several key points:
1) IWRM aims to balance economic, social, and environmental needs in water allocation and management. However, implementation faces challenges in integrating different sectors and balancing universal vs. region-specific policies.
2) Water demand is growing due to population, economic growth, and climate change, putting pressure on existing supplies. Reallocating water from irrigation could impact regions socioeconomically.
3) The document outlines important socioeconomic trends to consider in water policy, like income, unemployment, poverty, food security, and climate change. It also discusses tensions, transitions, and
Redefining brain tumor segmentation: a cutting-edge convolutional neural netw...IJECEIAES
Medical image analysis has witnessed significant advancements with deep learning techniques. In the domain of brain tumor segmentation, the ability to
precisely delineate tumor boundaries from magnetic resonance imaging (MRI)
scans holds profound implications for diagnosis. This study presents an ensemble convolutional neural network (CNN) with transfer learning, integrating
the state-of-the-art Deeplabv3+ architecture with the ResNet18 backbone. The
model is rigorously trained and evaluated, exhibiting remarkable performance
metrics, including an impressive global accuracy of 99.286%, a high-class accuracy of 82.191%, a mean intersection over union (IoU) of 79.900%, a weighted
IoU of 98.620%, and a Boundary F1 (BF) score of 83.303%. Notably, a detailed comparative analysis with existing methods showcases the superiority of
our proposed model. These findings underscore the model’s competence in precise brain tumor localization, underscoring its potential to revolutionize medical
image analysis and enhance healthcare outcomes. This research paves the way
for future exploration and optimization of advanced CNN models in medical
imaging, emphasizing addressing false positives and resource efficiency.
Embedded machine learning-based road conditions and driving behavior monitoringIJECEIAES
Car accident rates have increased in recent years, resulting in losses in human lives, properties, and other financial costs. An embedded machine learning-based system is developed to address this critical issue. The system can monitor road conditions, detect driving patterns, and identify aggressive driving behaviors. The system is based on neural networks trained on a comprehensive dataset of driving events, driving styles, and road conditions. The system effectively detects potential risks and helps mitigate the frequency and impact of accidents. The primary goal is to ensure the safety of drivers and vehicles. Collecting data involved gathering information on three key road events: normal street and normal drive, speed bumps, circular yellow speed bumps, and three aggressive driving actions: sudden start, sudden stop, and sudden entry. The gathered data is processed and analyzed using a machine learning system designed for limited power and memory devices. The developed system resulted in 91.9% accuracy, 93.6% precision, and 92% recall. The achieved inference time on an Arduino Nano 33 BLE Sense with a 32-bit CPU running at 64 MHz is 34 ms and requires 2.6 kB peak RAM and 139.9 kB program flash memory, making it suitable for resource-constrained embedded systems.
More Related Content
Similar to Smart city: an advanced framework for analyzing public sentiment orientation toward recycled water
This document discusses the development of an improved hydrological information system (HIS) in India using emerging information technologies. It notes that existing Indian HIS are inadequate and lack integration. The Hydrology Project aims to develop comprehensive and reliable HIS by standardizing data collection, establishing computerized databases, and ensuring sustainability. The improved HIS will provide reliable hydrological data to support long-term planning, management, and research on water resources development and use in India.
IoT Based Smart Water Monitoring and Distribution System For An ApartmentsYogeshIJTSRD
This document presents a smart water monitoring and distribution system for apartments using IoT. The system addresses water wastage by measuring flow rates and scheduling water supply. It can monitor the quality and quantity of water distributed to households using pH and flow sensors. An Arduino board implements the system using sensors to continuously monitor water levels. The system aims to ensure water quality and reduce wastage using IoT technologies like sensors and cloud-based monitoring. It is intended for use in densely populated residential buildings to survey individual water usage and detect leaks or contamination issues.
ICT solutions for highly-customized water demand management strategiesSmartH2O
1) Smart metering technologies and big data analytics can help water utilities better understand residential water usage patterns and identify different consumption profiles.
2) Gamification approaches, like the SmartH2O project's "DropTheQuestion" app, show potential for inducing behavioral change and reducing household water consumption. Preliminary results from SmartH2O indicate water savings of 10% on average.
3) Further analysis of smart meter data from over 11,000 households in Valencia, Spain identified common daily, weekly, and hourly water usage patterns and helped classify households into consumption categories from very high to low users.
Development of an Open-Source Water Consumption Meter for HousingIEREK Press
This article reports on the project "Design and development of water and gas P.L. measurement devices in the housing: an approach to sustainable consumption in Mexico", prepared at the Metropolitan Autonomous University in the Department of the Environment, whose objective was to develop a device to measure water consumption in the housing, which allows users to know their spending and can make decisions in favor of efficiency through the reduction of water use in household activities. The meter is made up of open source, programmable or reconfigurable software, which receives the signal from a water flow sensor and a casing designed to contain the hardware and facilitate the user's installation. Both the hardware and the casing can be purchased, downloaded, manufactured and assembled at home (Do It Yourself). As specific results were obtained: hardware programming and housing design and as a final result: the assembly of the functional prototype with which measurements of water consumption were made in a housing in Mexico. With this work we conclude that through the development of new accessible and common measurement technologies for the users of a house, it will be possible to promote efficiency in the use of natural resources in cities, increasing availability and promoting a more sustainable urban development.
Development of an Open-Source Water Consumption Meter for HousingIEREK Press
This article reports on the project "Design and development of water and gas P.L. measurement devices in the housing: an approach to sustainable consumption in Mexico", prepared at the Metropolitan Autonomous University in the Department of the Environment, whose objective was to develop a device to measure water consumption in the housing, which allows users to know their spending and can make decisions in favor of efficiency through the reduction of water use in household activities. The meter is made up of open source, programmable or reconfigurable software, which receives the signal from a water flow sensor and a casing designed to contain the hardware and facilitate the user's installation. Both the hardware and the casing can be purchased, downloaded, manufactured and assembled at home (Do It Yourself). As specific results were obtained: hardware programming and housing design and as a final result: the assembly of the functional prototype with which measurements of water consumption were made in a housing in Mexico. With this work we conclude that through the development of new accessible and common measurement technologies for the users of a house, it will be possible to promote efficiency in the use of natural resources in cities, increasing availability and promoting a more sustainable urban development.
Cities around the world are facing challenges brought about by rapid increases in population and geographic spread, which places greater pressure on infrastructure and services. Climate change impacts, including rising sea level, more frequent and severe storms, coastal erosion and declining freshwater sources will likely exacerbate these urban issues, in particular in poor and vulnerable communities that lack adequate infrastructure and services.
Globally, the impacts of climate change on urban areas have received less attention than on rural areas where poverty levels are higher and populations depend directly on climate-sensitive livelihoods. However, more than 50% of the world’s population currently lives in cities. By 2050, this figure is expected to increase to 70%, or 6.4 billion people, and Asian cities are likely to account for more than 60% of this increase. Urban areas are the economic powerhouses that support both the aspirations of the poor and most national economies. Furthermore, urban residents and the economic activity they generate depend on systems that are fragile and often subject to failure under the combination of climate and development pressures. If urban systems fail, the potential direct and indirect impacts of climate change on urban residents in general, on poor and vulnerable populations, and on the wider economy is massive. As a result, work on urban climate resilience is of critical importance in overall global initiatives to address the impacts of climate change.
The Asian Cities Climate Change Resilience Network (ACCCRN) works at the intersection of climate change, urban systems and social vulnerability to consider both direct and indirect impacts of climate change in urban areas.
A Model of (P-GIS) for Hydraulic Protection Dams in Northern Moroccoijait
This document summarizes a study that used a participatory geographic information system (P-GIS) to delineate protection zones around the Ibn Battouta dam in northern Morocco. The study combined GIS software, descriptive data collected in the field, and a data type model to analyze factors impacting the delineation of three protection zones around the dam based on water quality and human activities. The resulting P-GIS model created a spatial data management system and delineated protection areas in an innovative way to safeguard the dam's water resources and identify areas requiring action to reduce pollution.
A MODEL OF (P-GIS) FOR HYDRAULIC PROTECTION DAMS IN NORTHERN MOROCCOijait
To strengthen the quality of information, inclusion and implementation of continuous link between different categories of actors by mobilizing P-GIS as tools for participation and methodological aid to decision-making, and help to better understanding of environmental issues and challenges related
to climate change, allowing regional authorities to better analyze and process. So what we've seen, that the conventional GIS does not include certain information such as social exclusion, displacement, narrative conflicts of use of land and water, cultural stories, local politics. Hence the need to find an effective method to circumvent these problems.
So this study is based on a software solution that is supported on the geographic information system (GIS) coupled with the participatory model to give the (P-GIS). By manipulating various GIS software el descriptive data collected directly from the study area of the dam Ibn Battouta. A Data Type Model was generated to model the flow of data and related information. The delineation of protection zones will then contribute to the superposition, by adding each of the identified factors. The result of this study has created a multi-source spatial data management. This produces what is appalled the demonstration model GIS-remote sensing.'' It is based on certain factors that use parameters observed in the field and the information collected from censuses.
The document provides an overview of city projects undertaken by the Asian Cities Climate Change Resilience Network (ACCCRN) across 10 cities in Asia. It discusses ACCCRN's goal of building climate resilience in cities and outlines six key characteristics of urban resilience: flexibility, redundancy, safe failure, responsiveness, resourcefulness, and learning. It also identifies 10 urban climate change resilience action areas that the city projects address, such as water and drainage systems, land use planning, and health systems. The document then provides brief summaries of 32 city projects funded by ACCCRN, highlighting the climate risks and urban issues each project aims to tackle.
Community Participation Framework for Water Utilization in Jammu Region (J&K)...scmsnoida5
In the current global scenario water management
is the prime mover of economic growth and is
vital to the sustenance of a modern economy.
Future economic growth also, crucially depends
on the long term availability of perennial water
sources specially the ones that are affordable,
accessible and environment friendly. The analysis
of data from the Economic Survey of India,
2012-13, shows that energy and water demand
is on the rise in India and this is due to increase
in the development efforts and population
growth. Therefore, the present study will focus
on what has been achieved and what needs to
be achieved with reference to water management
through community participation in Jammu and
Kashmir State by understanding the experiences
from Singapore. Therefore, the study will be
utilizing the references and applying the research
by utilizing the knowledge and generating
a viable framework for the Jammu region,
which would be a little contribution towards proposing a Sustainable Water management
policy framework for Jammu and Kashmir
State by involvement of community through
non government organizations and self help
groups. In this regard, the exploration of water
renewal through Public Utilities Board (PUB),
Singapore’s national water agency gives an
insight to the study by providing an ideal model of
community participation which can be adopted
in Jammu region of state of J&K.
This document provides a research proposal to analyze citizen perception of participation in governance of urban water supply systems in Bangalore, India. The study will explore how the Bangalore Water Supply and Sewerage Board (BWSSB) allows citizen participation and the role of information and communication technologies (ICT) in improving participation. It reviews literature on the importance of citizen involvement in decision making for equitable and sustainable water systems. The conceptual framework assesses current conditions, explores areas of citizen participation and ICT applications used, analyzes generated data, and proposes verifying participation through a cyclic approach to address changing urban dynamics.
This document provides a research proposal to analyze citizen perception of participation in governance of urban water supply systems in Bangalore, India. The study will explore how the Bangalore Water Supply and Sewerage Board (BWSSB) allows citizen participation and the role of information and communication technologies (ICT) in improving participation. It reviews literature on the importance of citizen involvement in decision making for equitable and sustainable water systems. The conceptual framework assesses current conditions, explores areas of citizen participation and ICT applications used, analyzes generated data, and proposes verifying participation through a cyclic approach to address changing urban dynamics.
This document discusses guidelines for sustainable urbanization. It recommends that cities adopt a high-density centralized layout to minimize environmental footprint and encourage public transportation. Environmental technologies should utilize natural systems to purify water and generate energy on-site. Successful sustainable cities require collaboration among stakeholders and policymakers to address challenges through coordinated regional planning.
Assessing the resilience of a city in relation to its healthy urban systems: ...Dr.Hayam alsa'atee
This research investigates the relationship between city resilience and its urban
systems. The study determines the efficiency of a healthy urban system as one of a main
characteristic in achieving a compatible resilient city. Most of the current studies are theoretical
and suggest pathways and procedures that are beyond virtual practices. Healthy urban systems
are suggested to link human well-being with the effectiveness of the city infra-structure and
municipal services.
Assessing the resilience of a city in relation to its healthy urban systems: ...Dr.Hayam alsa'atee
This research investigates the relationship between city resilience and its urban
systems. The study determines the efficiency of a healthy urban system as one of a main
characteristic in achieving a compatible resilient city. Most of the current studies are theoretical
and suggest pathways and procedures that are beyond virtual practices. Healthy urban systems
are suggested to link human well-being with the effectiveness of the city infra-structure and
municipal services. These services are associated with the drinking water supply, sewage
disposal, garbage system, and adequacy of the transport system.
The document discusses the growing problem of water pollution worldwide and proposes a multi-pronged solution. It suggests creating a fund to educate young professionals in developing countries about water treatment techniques. It also proposes establishing community water centers to oversee local sanitation projects and offering incentives for waste water treatment programs and good water management practices among communities and industries. The goal is to increase technical knowledge, encourage local initiatives, raise awareness from an early age, and incentivize sustainable practices to address water pollution issues.
Green Solutions for Water and Waste is one of VTT’s Spearhead Programmes that has been running since 2011. This publication presents some of the research highlights from the first half of the programme. Focal areas of this programme have been water treatment technologies and waste management. In water treatment the research has focused in enzyme and membrane technologies and membrane surface treatment methods, water monitoring technologies, and sludge treatment. Regarding waste treatment methods and technologies the focus has been in refining organic waste and conceptualising new business on valorisation of waste streams.
Tamimi - socioeconomic dimension of water policyWANA forum
This document discusses the socioeconomic dimensions of water policy and integrated water resource management (IWRM). It addresses several key points:
1) IWRM aims to balance economic, social, and environmental needs in water allocation and management. However, implementation faces challenges in integrating different sectors and balancing universal vs. region-specific policies.
2) Water demand is growing due to population, economic growth, and climate change, putting pressure on existing supplies. Reallocating water from irrigation could impact regions socioeconomically.
3) The document outlines important socioeconomic trends to consider in water policy, like income, unemployment, poverty, food security, and climate change. It also discusses tensions, transitions, and
Similar to Smart city: an advanced framework for analyzing public sentiment orientation toward recycled water (20)
Redefining brain tumor segmentation: a cutting-edge convolutional neural netw...IJECEIAES
Medical image analysis has witnessed significant advancements with deep learning techniques. In the domain of brain tumor segmentation, the ability to
precisely delineate tumor boundaries from magnetic resonance imaging (MRI)
scans holds profound implications for diagnosis. This study presents an ensemble convolutional neural network (CNN) with transfer learning, integrating
the state-of-the-art Deeplabv3+ architecture with the ResNet18 backbone. The
model is rigorously trained and evaluated, exhibiting remarkable performance
metrics, including an impressive global accuracy of 99.286%, a high-class accuracy of 82.191%, a mean intersection over union (IoU) of 79.900%, a weighted
IoU of 98.620%, and a Boundary F1 (BF) score of 83.303%. Notably, a detailed comparative analysis with existing methods showcases the superiority of
our proposed model. These findings underscore the model’s competence in precise brain tumor localization, underscoring its potential to revolutionize medical
image analysis and enhance healthcare outcomes. This research paves the way
for future exploration and optimization of advanced CNN models in medical
imaging, emphasizing addressing false positives and resource efficiency.
Embedded machine learning-based road conditions and driving behavior monitoringIJECEIAES
Car accident rates have increased in recent years, resulting in losses in human lives, properties, and other financial costs. An embedded machine learning-based system is developed to address this critical issue. The system can monitor road conditions, detect driving patterns, and identify aggressive driving behaviors. The system is based on neural networks trained on a comprehensive dataset of driving events, driving styles, and road conditions. The system effectively detects potential risks and helps mitigate the frequency and impact of accidents. The primary goal is to ensure the safety of drivers and vehicles. Collecting data involved gathering information on three key road events: normal street and normal drive, speed bumps, circular yellow speed bumps, and three aggressive driving actions: sudden start, sudden stop, and sudden entry. The gathered data is processed and analyzed using a machine learning system designed for limited power and memory devices. The developed system resulted in 91.9% accuracy, 93.6% precision, and 92% recall. The achieved inference time on an Arduino Nano 33 BLE Sense with a 32-bit CPU running at 64 MHz is 34 ms and requires 2.6 kB peak RAM and 139.9 kB program flash memory, making it suitable for resource-constrained embedded systems.
Advanced control scheme of doubly fed induction generator for wind turbine us...IJECEIAES
This paper describes a speed control device for generating electrical energy on an electricity network based on the doubly fed induction generator (DFIG) used for wind power conversion systems. At first, a double-fed induction generator model was constructed. A control law is formulated to govern the flow of energy between the stator of a DFIG and the energy network using three types of controllers: proportional integral (PI), sliding mode controller (SMC) and second order sliding mode controller (SOSMC). Their different results in terms of power reference tracking, reaction to unexpected speed fluctuations, sensitivity to perturbations, and resilience against machine parameter alterations are compared. MATLAB/Simulink was used to conduct the simulations for the preceding study. Multiple simulations have shown very satisfying results, and the investigations demonstrate the efficacy and power-enhancing capabilities of the suggested control system.
Neural network optimizer of proportional-integral-differential controller par...IJECEIAES
Wide application of proportional-integral-differential (PID)-regulator in industry requires constant improvement of methods of its parameters adjustment. The paper deals with the issues of optimization of PID-regulator parameters with the use of neural network technology methods. A methodology for choosing the architecture (structure) of neural network optimizer is proposed, which consists in determining the number of layers, the number of neurons in each layer, as well as the form and type of activation function. Algorithms of neural network training based on the application of the method of minimizing the mismatch between the regulated value and the target value are developed. The method of back propagation of gradients is proposed to select the optimal training rate of neurons of the neural network. The neural network optimizer, which is a superstructure of the linear PID controller, allows increasing the regulation accuracy from 0.23 to 0.09, thus reducing the power consumption from 65% to 53%. The results of the conducted experiments allow us to conclude that the created neural superstructure may well become a prototype of an automatic voltage regulator (AVR)-type industrial controller for tuning the parameters of the PID controller.
An improved modulation technique suitable for a three level flying capacitor ...IJECEIAES
This research paper introduces an innovative modulation technique for controlling a 3-level flying capacitor multilevel inverter (FCMLI), aiming to streamline the modulation process in contrast to conventional methods. The proposed
simplified modulation technique paves the way for more straightforward and
efficient control of multilevel inverters, enabling their widespread adoption and
integration into modern power electronic systems. Through the amalgamation of
sinusoidal pulse width modulation (SPWM) with a high-frequency square wave
pulse, this controlling technique attains energy equilibrium across the coupling
capacitor. The modulation scheme incorporates a simplified switching pattern
and a decreased count of voltage references, thereby simplifying the control
algorithm.
A review on features and methods of potential fishing zoneIJECEIAES
This review focuses on the importance of identifying potential fishing zones in seawater for sustainable fishing practices. It explores features like sea surface temperature (SST) and sea surface height (SSH), along with classification methods such as classifiers. The features like SST, SSH, and different classifiers used to classify the data, have been figured out in this review study. This study underscores the importance of examining potential fishing zones using advanced analytical techniques. It thoroughly explores the methodologies employed by researchers, covering both past and current approaches. The examination centers on data characteristics and the application of classification algorithms for classification of potential fishing zones. Furthermore, the prediction of potential fishing zones relies significantly on the effectiveness of classification algorithms. Previous research has assessed the performance of models like support vector machines, naïve Bayes, and artificial neural networks (ANN). In the previous result, the results of support vector machine (SVM) were 97.6% more accurate than naive Bayes's 94.2% to classify test data for fisheries classification. By considering the recent works in this area, several recommendations for future works are presented to further improve the performance of the potential fishing zone models, which is important to the fisheries community.
Electrical signal interference minimization using appropriate core material f...IJECEIAES
As demand for smaller, quicker, and more powerful devices rises, Moore's law is strictly followed. The industry has worked hard to make little devices that boost productivity. The goal is to optimize device density. Scientists are reducing connection delays to improve circuit performance. This helped them understand three-dimensional integrated circuit (3D IC) concepts, which stack active devices and create vertical connections to diminish latency and lower interconnects. Electrical involvement is a big worry with 3D integrates circuits. Researchers have developed and tested through silicon via (TSV) and substrates to decrease electrical wave involvement. This study illustrates a novel noise coupling reduction method using several electrical involvement models. A 22% drop in electrical involvement from wave-carrying to victim TSVs introduces this new paradigm and improves system performance even at higher THz frequencies.
Electric vehicle and photovoltaic advanced roles in enhancing the financial p...IJECEIAES
Climate change's impact on the planet forced the United Nations and governments to promote green energies and electric transportation. The deployments of photovoltaic (PV) and electric vehicle (EV) systems gained stronger momentum due to their numerous advantages over fossil fuel types. The advantages go beyond sustainability to reach financial support and stability. The work in this paper introduces the hybrid system between PV and EV to support industrial and commercial plants. This paper covers the theoretical framework of the proposed hybrid system including the required equation to complete the cost analysis when PV and EV are present. In addition, the proposed design diagram which sets the priorities and requirements of the system is presented. The proposed approach allows setup to advance their power stability, especially during power outages. The presented information supports researchers and plant owners to complete the necessary analysis while promoting the deployment of clean energy. The result of a case study that represents a dairy milk farmer supports the theoretical works and highlights its advanced benefits to existing plants. The short return on investment of the proposed approach supports the paper's novelty approach for the sustainable electrical system. In addition, the proposed system allows for an isolated power setup without the need for a transmission line which enhances the safety of the electrical network
Bibliometric analysis highlighting the role of women in addressing climate ch...IJECEIAES
Fossil fuel consumption increased quickly, contributing to climate change
that is evident in unusual flooding and draughts, and global warming. Over
the past ten years, women's involvement in society has grown dramatically,
and they succeeded in playing a noticeable role in reducing climate change.
A bibliometric analysis of data from the last ten years has been carried out to
examine the role of women in addressing the climate change. The analysis's
findings discussed the relevant to the sustainable development goals (SDGs),
particularly SDG 7 and SDG 13. The results considered contributions made
by women in the various sectors while taking geographic dispersion into
account. The bibliometric analysis delves into topics including women's
leadership in environmental groups, their involvement in policymaking, their
contributions to sustainable development projects, and the influence of
gender diversity on attempts to mitigate climate change. This study's results
highlight how women have influenced policies and actions related to climate
change, point out areas of research deficiency and recommendations on how
to increase role of the women in addressing the climate change and
achieving sustainability. To achieve more successful results, this initiative
aims to highlight the significance of gender equality and encourage
inclusivity in climate change decision-making processes.
Voltage and frequency control of microgrid in presence of micro-turbine inter...IJECEIAES
The active and reactive load changes have a significant impact on voltage
and frequency. In this paper, in order to stabilize the microgrid (MG) against
load variations in islanding mode, the active and reactive power of all
distributed generators (DGs), including energy storage (battery), diesel
generator, and micro-turbine, are controlled. The micro-turbine generator is
connected to MG through a three-phase to three-phase matrix converter, and
the droop control method is applied for controlling the voltage and
frequency of MG. In addition, a method is introduced for voltage and
frequency control of micro-turbines in the transition state from gridconnected mode to islanding mode. A novel switching strategy of the matrix
converter is used for converting the high-frequency output voltage of the
micro-turbine to the grid-side frequency of the utility system. Moreover,
using the switching strategy, the low-order harmonics in the output current
and voltage are not produced, and consequently, the size of the output filter
would be reduced. In fact, the suggested control strategy is load-independent
and has no frequency conversion restrictions. The proposed approach for
voltage and frequency regulation demonstrates exceptional performance and
favorable response across various load alteration scenarios. The suggested
strategy is examined in several scenarios in the MG test systems, and the
simulation results are addressed.
Enhancing battery system identification: nonlinear autoregressive modeling fo...IJECEIAES
Precisely characterizing Li-ion batteries is essential for optimizing their
performance, enhancing safety, and prolonging their lifespan across various
applications, such as electric vehicles and renewable energy systems. This
article introduces an innovative nonlinear methodology for system
identification of a Li-ion battery, employing a nonlinear autoregressive with
exogenous inputs (NARX) model. The proposed approach integrates the
benefits of nonlinear modeling with the adaptability of the NARX structure,
facilitating a more comprehensive representation of the intricate
electrochemical processes within the battery. Experimental data collected
from a Li-ion battery operating under diverse scenarios are employed to
validate the effectiveness of the proposed methodology. The identified
NARX model exhibits superior accuracy in predicting the battery's behavior
compared to traditional linear models. This study underscores the
importance of accounting for nonlinearities in battery modeling, providing
insights into the intricate relationships between state-of-charge, voltage, and
current under dynamic conditions.
Smart grid deployment: from a bibliometric analysis to a surveyIJECEIAES
Smart grids are one of the last decades' innovations in electrical energy.
They bring relevant advantages compared to the traditional grid and
significant interest from the research community. Assessing the field's
evolution is essential to propose guidelines for facing new and future smart
grid challenges. In addition, knowing the main technologies involved in the
deployment of smart grids (SGs) is important to highlight possible
shortcomings that can be mitigated by developing new tools. This paper
contributes to the research trends mentioned above by focusing on two
objectives. First, a bibliometric analysis is presented to give an overview of
the current research level about smart grid deployment. Second, a survey of
the main technological approaches used for smart grid implementation and
their contributions are highlighted. To that effect, we searched the Web of
Science (WoS), and the Scopus databases. We obtained 5,663 documents
from WoS and 7,215 from Scopus on smart grid implementation or
deployment. With the extraction limitation in the Scopus database, 5,872 of
the 7,215 documents were extracted using a multi-step process. These two
datasets have been analyzed using a bibliometric tool called bibliometrix.
The main outputs are presented with some recommendations for future
research.
Use of analytical hierarchy process for selecting and prioritizing islanding ...IJECEIAES
One of the problems that are associated to power systems is islanding
condition, which must be rapidly and properly detected to prevent any
negative consequences on the system's protection, stability, and security.
This paper offers a thorough overview of several islanding detection
strategies, which are divided into two categories: classic approaches,
including local and remote approaches, and modern techniques, including
techniques based on signal processing and computational intelligence.
Additionally, each approach is compared and assessed based on several
factors, including implementation costs, non-detected zones, declining
power quality, and response times using the analytical hierarchy process
(AHP). The multi-criteria decision-making analysis shows that the overall
weight of passive methods (24.7%), active methods (7.8%), hybrid methods
(5.6%), remote methods (14.5%), signal processing-based methods (26.6%),
and computational intelligent-based methods (20.8%) based on the
comparison of all criteria together. Thus, it can be seen from the total weight
that hybrid approaches are the least suitable to be chosen, while signal
processing-based methods are the most appropriate islanding detection
method to be selected and implemented in power system with respect to the
aforementioned factors. Using Expert Choice software, the proposed
hierarchy model is studied and examined.
Enhancing of single-stage grid-connected photovoltaic system using fuzzy logi...IJECEIAES
The power generated by photovoltaic (PV) systems is influenced by
environmental factors. This variability hampers the control and utilization of
solar cells' peak output. In this study, a single-stage grid-connected PV
system is designed to enhance power quality. Our approach employs fuzzy
logic in the direct power control (DPC) of a three-phase voltage source
inverter (VSI), enabling seamless integration of the PV connected to the
grid. Additionally, a fuzzy logic-based maximum power point tracking
(MPPT) controller is adopted, which outperforms traditional methods like
incremental conductance (INC) in enhancing solar cell efficiency and
minimizing the response time. Moreover, the inverter's real-time active and
reactive power is directly managed to achieve a unity power factor (UPF).
The system's performance is assessed through MATLAB/Simulink
implementation, showing marked improvement over conventional methods,
particularly in steady-state and varying weather conditions. For solar
irradiances of 500 and 1,000 W/m2
, the results show that the proposed
method reduces the total harmonic distortion (THD) of the injected current
to the grid by approximately 46% and 38% compared to conventional
methods, respectively. Furthermore, we compare the simulation results with
IEEE standards to evaluate the system's grid compatibility.
Enhancing photovoltaic system maximum power point tracking with fuzzy logic-b...IJECEIAES
Photovoltaic systems have emerged as a promising energy resource that
caters to the future needs of society, owing to their renewable, inexhaustible,
and cost-free nature. The power output of these systems relies on solar cell
radiation and temperature. In order to mitigate the dependence on
atmospheric conditions and enhance power tracking, a conventional
approach has been improved by integrating various methods. To optimize
the generation of electricity from solar systems, the maximum power point
tracking (MPPT) technique is employed. To overcome limitations such as
steady-state voltage oscillations and improve transient response, two
traditional MPPT methods, namely fuzzy logic controller (FLC) and perturb
and observe (P&O), have been modified. This research paper aims to
simulate and validate the step size of the proposed modified P&O and FLC
techniques within the MPPT algorithm using MATLAB/Simulink for
efficient power tracking in photovoltaic systems.
Adaptive synchronous sliding control for a robot manipulator based on neural ...IJECEIAES
Robot manipulators have become important equipment in production lines, medical fields, and transportation. Improving the quality of trajectory tracking for
robot hands is always an attractive topic in the research community. This is a
challenging problem because robot manipulators are complex nonlinear systems
and are often subject to fluctuations in loads and external disturbances. This
article proposes an adaptive synchronous sliding control scheme to improve trajectory tracking performance for a robot manipulator. The proposed controller
ensures that the positions of the joints track the desired trajectory, synchronize
the errors, and significantly reduces chattering. First, the synchronous tracking
errors and synchronous sliding surfaces are presented. Second, the synchronous
tracking error dynamics are determined. Third, a robust adaptive control law is
designed,the unknown components of the model are estimated online by the neural network, and the parameters of the switching elements are selected by fuzzy
logic. The built algorithm ensures that the tracking and approximation errors
are ultimately uniformly bounded (UUB). Finally, the effectiveness of the constructed algorithm is demonstrated through simulation and experimental results.
Simulation and experimental results show that the proposed controller is effective with small synchronous tracking errors, and the chattering phenomenon is
significantly reduced.
Remote field-programmable gate array laboratory for signal acquisition and de...IJECEIAES
A remote laboratory utilizing field-programmable gate array (FPGA) technologies enhances students’ learning experience anywhere and anytime in embedded system design. Existing remote laboratories prioritize hardware access and visual feedback for observing board behavior after programming, neglecting comprehensive debugging tools to resolve errors that require internal signal acquisition. This paper proposes a novel remote embeddedsystem design approach targeting FPGA technologies that are fully interactive via a web-based platform. Our solution provides FPGA board access and debugging capabilities beyond the visual feedback provided by existing remote laboratories. We implemented a lab module that allows users to seamlessly incorporate into their FPGA design. The module minimizes hardware resource utilization while enabling the acquisition of a large number of data samples from the signal during the experiments by adaptively compressing the signal prior to data transmission. The results demonstrate an average compression ratio of 2.90 across three benchmark signals, indicating efficient signal acquisition and effective debugging and analysis. This method allows users to acquire more data samples than conventional methods. The proposed lab allows students to remotely test and debug their designs, bridging the gap between theory and practice in embedded system design.
Detecting and resolving feature envy through automated machine learning and m...IJECEIAES
Efficiently identifying and resolving code smells enhances software project quality. This paper presents a novel solution, utilizing automated machine learning (AutoML) techniques, to detect code smells and apply move method refactoring. By evaluating code metrics before and after refactoring, we assessed its impact on coupling, complexity, and cohesion. Key contributions of this research include a unique dataset for code smell classification and the development of models using AutoGluon for optimal performance. Furthermore, the study identifies the top 20 influential features in classifying feature envy, a well-known code smell, stemming from excessive reliance on external classes. We also explored how move method refactoring addresses feature envy, revealing reduced coupling and complexity, and improved cohesion, ultimately enhancing code quality. In summary, this research offers an empirical, data-driven approach, integrating AutoML and move method refactoring to optimize software project quality. Insights gained shed light on the benefits of refactoring on code quality and the significance of specific features in detecting feature envy. Future research can expand to explore additional refactoring techniques and a broader range of code metrics, advancing software engineering practices and standards.
Smart monitoring technique for solar cell systems using internet of things ba...IJECEIAES
Rapidly and remotely monitoring and receiving the solar cell systems status parameters, solar irradiance, temperature, and humidity, are critical issues in enhancement their efficiency. Hence, in the present article an improved smart prototype of internet of things (IoT) technique based on embedded system through NodeMCU ESP8266 (ESP-12E) was carried out experimentally. Three different regions at Egypt; Luxor, Cairo, and El-Beheira cities were chosen to study their solar irradiance profile, temperature, and humidity by the proposed IoT system. The monitoring data of solar irradiance, temperature, and humidity were live visualized directly by Ubidots through hypertext transfer protocol (HTTP) protocol. The measured solar power radiation in Luxor, Cairo, and El-Beheira ranged between 216-1000, 245-958, and 187-692 W/m 2 respectively during the solar day. The accuracy and rapidity of obtaining monitoring results using the proposed IoT system made it a strong candidate for application in monitoring solar cell systems. On the other hand, the obtained solar power radiation results of the three considered regions strongly candidate Luxor and Cairo as suitable places to build up a solar cells system station rather than El-Beheira.
An efficient security framework for intrusion detection and prevention in int...IJECEIAES
Over the past few years, the internet of things (IoT) has advanced to connect billions of smart devices to improve quality of life. However, anomalies or malicious intrusions pose several security loopholes, leading to performance degradation and threat to data security in IoT operations. Thereby, IoT security systems must keep an eye on and restrict unwanted events from occurring in the IoT network. Recently, various technical solutions based on machine learning (ML) models have been derived towards identifying and restricting unwanted events in IoT. However, most ML-based approaches are prone to miss-classification due to inappropriate feature selection. Additionally, most ML approaches applied to intrusion detection and prevention consider supervised learning, which requires a large amount of labeled data to be trained. Consequently, such complex datasets are impossible to source in a large network like IoT. To address this problem, this proposed study introduces an efficient learning mechanism to strengthen the IoT security aspects. The proposed algorithm incorporates supervised and unsupervised approaches to improve the learning models for intrusion detection and mitigation. Compared with the related works, the experimental outcome shows that the model performs well in a benchmark dataset. It accomplishes an improved detection accuracy of approximately 99.21%.
KuberTENes Birthday Bash Guadalajara - K8sGPT first impressionsVictor Morales
K8sGPT is a tool that analyzes and diagnoses Kubernetes clusters. This presentation was used to share the requirements and dependencies to deploy K8sGPT in a local environment.
Understanding Inductive Bias in Machine LearningSUTEJAS
This presentation explores the concept of inductive bias in machine learning. It explains how algorithms come with built-in assumptions and preferences that guide the learning process. You'll learn about the different types of inductive bias and how they can impact the performance and generalizability of machine learning models.
The presentation also covers the positive and negative aspects of inductive bias, along with strategies for mitigating potential drawbacks. We'll explore examples of how bias manifests in algorithms like neural networks and decision trees.
By understanding inductive bias, you can gain valuable insights into how machine learning models work and make informed decisions when building and deploying them.
A review on techniques and modelling methodologies used for checking electrom...nooriasukmaningtyas
The proper function of the integrated circuit (IC) in an inhibiting electromagnetic environment has always been a serious concern throughout the decades of revolution in the world of electronics, from disjunct devices to today’s integrated circuit technology, where billions of transistors are combined on a single chip. The automotive industry and smart vehicles in particular, are confronting design issues such as being prone to electromagnetic interference (EMI). Electronic control devices calculate incorrect outputs because of EMI and sensors give misleading values which can prove fatal in case of automotives. In this paper, the authors have non exhaustively tried to review research work concerned with the investigation of EMI in ICs and prediction of this EMI using various modelling methodologies and measurement setups.
DEEP LEARNING FOR SMART GRID INTRUSION DETECTION: A HYBRID CNN-LSTM-BASED MODELgerogepatton
As digital technology becomes more deeply embedded in power systems, protecting the communication
networks of Smart Grids (SG) has emerged as a critical concern. Distributed Network Protocol 3 (DNP3)
represents a multi-tiered application layer protocol extensively utilized in Supervisory Control and Data
Acquisition (SCADA)-based smart grids to facilitate real-time data gathering and control functionalities.
Robust Intrusion Detection Systems (IDS) are necessary for early threat detection and mitigation because
of the interconnection of these networks, which makes them vulnerable to a variety of cyberattacks. To
solve this issue, this paper develops a hybrid Deep Learning (DL) model specifically designed for intrusion
detection in smart grids. The proposed approach is a combination of the Convolutional Neural Network
(CNN) and the Long-Short-Term Memory algorithms (LSTM). We employed a recent intrusion detection
dataset (DNP3), which focuses on unauthorized commands and Denial of Service (DoS) cyberattacks, to
train and test our model. The results of our experiments show that our CNN-LSTM method is much better
at finding smart grid intrusions than other deep learning algorithms used for classification. In addition,
our proposed approach improves accuracy, precision, recall, and F1 score, achieving a high detection
accuracy rate of 99.50%.
We have compiled the most important slides from each speaker's presentation. This year’s compilation, available for free, captures the key insights and contributions shared during the DfMAy 2024 conference.
International Conference on NLP, Artificial Intelligence, Machine Learning an...gerogepatton
International Conference on NLP, Artificial Intelligence, Machine Learning and Applications (NLAIM 2024) offers a premier global platform for exchanging insights and findings in the theory, methodology, and applications of NLP, Artificial Intelligence, Machine Learning, and their applications. The conference seeks substantial contributions across all key domains of NLP, Artificial Intelligence, Machine Learning, and their practical applications, aiming to foster both theoretical advancements and real-world implementations. With a focus on facilitating collaboration between researchers and practitioners from academia and industry, the conference serves as a nexus for sharing the latest developments in the field.
Low power architecture of logic gates using adiabatic techniquesnooriasukmaningtyas
The growing significance of portable systems to limit power consumption in ultra-large-scale-integration chips of very high density, has recently led to rapid and inventive progresses in low-power design. The most effective technique is adiabatic logic circuit design in energy-efficient hardware. This paper presents two adiabatic approaches for the design of low power circuits, modified positive feedback adiabatic logic (modified PFAL) and the other is direct current diode based positive feedback adiabatic logic (DC-DB PFAL). Logic gates are the preliminary components in any digital circuit design. By improving the performance of basic gates, one can improvise the whole system performance. In this paper proposed circuit design of the low power architecture of OR/NOR, AND/NAND, and XOR/XNOR gates are presented using the said approaches and their results are analyzed for powerdissipation, delay, power-delay-product and rise time and compared with the other adiabatic techniques along with the conventional complementary metal oxide semiconductor (CMOS) designs reported in the literature. It has been found that the designs with DC-DB PFAL technique outperform with the percentage improvement of 65% for NOR gate and 7% for NAND gate and 34% for XNOR gate over the modified PFAL techniques at 10 MHz respectively.
ACEP Magazine edition 4th launched on 05.06.2024Rahul
This document provides information about the third edition of the magazine "Sthapatya" published by the Association of Civil Engineers (Practicing) Aurangabad. It includes messages from current and past presidents of ACEP, memories and photos from past ACEP events, information on life time achievement awards given by ACEP, and a technical article on concrete maintenance, repairs and strengthening. The document highlights activities of ACEP and provides a technical educational article for members.
Literature Review Basics and Understanding Reference Management.pptxDr Ramhari Poudyal
Three-day training on academic research focuses on analytical tools at United Technical College, supported by the University Grant Commission, Nepal. 24-26 May 2024
IEEE Aerospace and Electronic Systems Society as a Graduate Student Member
Smart city: an advanced framework for analyzing public sentiment orientation toward recycled water
1. International Journal of Electrical and Computer Engineering (IJECE)
Vol. 14, No. 1, February 2024, pp. 1015~1026
ISSN: 2088-8708, DOI: 10.11591/ijece.v14i1.pp1015-1026 1015
Journal homepage: http://ijece.iaescore.com
Smart city: an advanced framework for analyzing public
sentiment orientation toward recycled water
Mohamed Bahra, Abdelhadi Fennan
LIST Department of Computer Science, Faculty of Sciences and Techniques, Abdelmalek Essaadi University, Tangier, Morocco
Article Info ABSTRACT
Article history:
Received Nov 8, 2022
Revised Jan 19, 2023
Accepted Feb 26, 2023
The coronavirus pandemic of the past several years has had a profound
impact on all aspects of life, including resource utilization. One notable
example is the increased demand for freshwater, a lifeblood of our planet, on
the other hand, the smart city vision aims to attain a smart water
management goal by investing in innovative solutions such as recycled water
systems. However, the problem lies in the public’s sentiment and willingness
to use this new resource which discourages investors and hinders the
development of this field. Therefore, in our work, we applied sentiment
analysis using an extended version of the fuzzy logic and neural network
model from our previous work, to find out the general public opinion
regarding recycled water and to assess the effects of sentiments on the
public’s readiness to use this resource. Our analysis was based on a dataset
of over 1 million text content from 2013 to 2022. The results show, from
spatio-temporal perspectives, that sentiment orientation and acceptance-
behavior towards using recycled water have increased positively.
Additionally, the public is more concerned in areas driven by the smart city
vision than in areas of medium and low economic development, where
investment in sensibilization campaigns is needed.
Keywords:
Fuzzy logic
Neural network
Ontology
Recycled water
Sentiment analysis
Sentiment orientation
Smart city
This is an open access article under the CC BY-SA license.
Corresponding Author:
Mohamed Bahra
LIST Department of Computer Science, Faculty of Science and Techniques, Abdelmalek Essaadi
University
Km 10, Ziaten, BP 416, Old Airport Road, Tangier, Morocco
Email: bahra002@gmail.com
1. INTRODUCTION
The coronavirus disease 2019 (COVID-19) that we have witnessed and which was recognized as a
worldwide pandemic on March 11, 2020, has drastically affected our everyday lives, especially due to the
implementation of lockdowns as one of the main precautions used to curb the spread of the disease. Many
sectors and resources have been immediately impacted, both in terms of consumption and production, such as
energy, industry, and food supply, to name a few. Water consumption was not the exception as it was
considered one of the most effective mitigation measures against COVID-19 transmission through
handwashing [1], and sanitization. The United Nations Economic and Social Commission for Western Asia
(ESCWA) has cited in its Policy Brief.5 that the household water demand will represent in the Arab region
only, an average increase of 5%, a value equivalent to 4-5 million cubic meters per day due to COVID-19.
The global population’s growth and increasing demands for safe water in agriculture, industry, and
municipalities have amplified the need for freshwater, as noted in [2]. This escalating demand has led to a
significant water supply-demand gap, a grave threat that [3] emphasizes cannot be mitigated solely by
existing groundwater and water supply resources. Effective solutions demand comprehensive strategies,
conservation, and innovative technology, necessitating collaborative efforts for sustainable water security.
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Smart city on the other hand, aims through the usage of information and communication
technologies to enhance people welfare [4], [5], and efficiently manage economy, living, mobility, people,
governance, and environment that include waste water management [6]. To this end, governments and many
world organizations have started giving more attention to water scarcity, naming the Organization for
Economic Co-operation and Development (OECD), by working with regions and countries to reform water
policies and exchange international community best practices, innovations, and effective approaches for
better water management, as well as to raise awareness among citizens about this challenge and the
importance of recycled water usage. But the issue is with the acceptance and the scale of usage of this new
resource, which is still low even with the quoted quality standard reached by advanced purification
technologies such as biofilm [7]. Many research and studies of people’s behavior agreed that emotions,
sentiment preferences and opinions directly affect a person’s behavior towards a subject [8], [9], and this may
be the case of public willingness to use recycled water.
Through our work, we aim first to enhance the approach used in our previous work [10] by
including domain ontology to extract domain-specific data from social media platforms. Additionally, we
added a sentiment word embedding layer that use fuzzy logic linguistic functions [11] to the word embedding
layer used by long-shirt-term-memory (LSTM) model. Also, we provide a good explanation of each step of
our proposed framework to help future researchers who want to apply fuzzy logic and deep learning in
sentiment analysis. Second, we wanted to explore the impact of public sentiment towards recycled water
reuse, by benefiting from the immense data published through social media platforms, which gives people the
freedom of expression, anonymously and without any external pressure or social barrier.
Our remaining work is structured as follows: The background research for our study is described in
section 2, the key concepts used in our work are presented in section 3, and our sentiment analysis system is
described in section 4, followed by section 5, in which we present the results and discuss public sentiment
orientation, and finally, we conclude our work and highlight our perspectives.
2. RELATED WORK
2.1. Water scarcity and recycled water alternative
Addressing water scarcity has long been, and continues to be, an area of research and development,
due to it is connection to the global vision of transitioning to green energy [12], challenges posed by climate
change, and the increasing demand caused by the rising global population, to name a few. Srinivasan et al.,
[13] examined the causes and nature of the world’s water dilemma, by applying a qualitative comparison
analysis (QCA) to 22 case studies conducted in different regions, their results show that water crisis issues
are grouped into six syndromes that falls into “demand changes”, “supply changes”, “governance systems”,
and “infrastructure/technology” categories. Mancuso et al., [14] discuss the value of recycled water as a
strategy for overcoming the problem of water scarcity, particularly as a supply for irrigation. Another
research in [15] also draw attention on using reclaimed water for agriculture, however, the authors point to
the impact of irrigation water on food crops and human health, due to the widespread consumption of raw
fruits and vegetables, which can cause public health risks, and increase the doubt about using this resource.
The COVID-19 pandemic has also influenced people’s behavior and increased public sensitivity to alleged
health dangers [16], [17]. Vakula and Kolli [18] emphasize the importance of utilizing recycled water in the
development of smart cities and outlined the stages of treatment for recycled water. They also suggest
incorporating sensors to automate the process at each stage, resulting in more efficient water management.
2.2. Impact of sentiment preferences on recycled water use
Emotions and sentiment preferences are known to be factors that directly affect people’s behavior
[19]. Accepting the usage of reclaimed water by citizens requires from governments to sensibilize and
involve the public through promotion methods that describe the processes and technologies used in this field.
To do so, it is crucial to understand the current state of public sentiment orientation towards recycled water.
In both [20], [21], Nkhoma et al. analyze the potential permissive factors for treated water and the effect of
the ‘yuck factor’ or the disgust emotion related to it, their finding show that ethnicity, education level and the
disgust factor in public psyche influence the number of recycled water supporters. Disgust sensitivity and
psychological aspect were addressed in [22], based on the analysis of two surveys in which question-answer
methods were used, their results show that people’s intuition and feeling can contradict their rational self-
interest, which makes recycled water acceptance a psychological issue. Another work by Leong [23] supports
the previously mentioned work by using the Q technique to look at how emotions affect drinking recycled
water, his findings show that narratives including disgust, anger and fear, emphasize the negativity bubble
related to recycled water use, and these emotions can affect ecological policy making and discourage
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stakeholders. In [24] a sentiment analysis was applied on text content from social media for exploring
public’s attention and current status regarding the adoption of recycled water use in China.
2.3. Methods used for sentiment analysis
The work by Medhat et al. [25] provide through a list of articles analysis, an exhaustive explanation
of sentiment analysis field, including its methodologies, classification techniques, related fields, and the trend
of researchers using these techniques. In [26], [27] Malviya et al. highlighted algorithms namely k-nearest
neighbors (KNN), multilayer perceptron (MLP), naive Bayes (NB), and support-vector machine (SVM),
when discussing machine learning techniques applied in sentiment analysis (SA), they also presented a
comparison of the performance of these algorithms for SA tasks. Deep learning, as described in [28], is a
more in-depth technique of machine learning that can also be applied to sentiment analysis [29]. In [30], the
authors applied LSTM model for sentiment analysis on text reviews. They constructed a model consisting of
a dense layer, an LSTM layer, and an embedding layer, which was then trained and tested using Amazon and
the internet movie database (IMDB) datasets, and the findings indicate that the LSTM model had an accuracy
of 85%. The work in [31] addresses the issue that most pre-trained word embeddings for sentiment analysis
confront., i.e., two words with alike contexts can be close in term of linguistic properties in word
embeddings, yet they could have opposite feelings (e.g., good and bad) [32], which reduces words
discrimination and leads to poor performance of these models. The authors propose two approaches to tackle
this problem. The first method entails adding sentiment polarity to already-trained word embeddings, while
the second method is based on learning word embeddings from contexts, and consider contextual
relationships and sentiment associations between words. Fu et al., [33] also highlight the problem
encountered by word embeddings, and propose a model that incorporates a sentiment lexicon into LSTM,
adding sentiment information to word’s representation. Fuzzy logic for sentiment analysis was proposed in
[34], where the authors discuss the implementation of a model that can analyses social media content in order
to capture users perceptions and opinions regarding products and services.
The application of sentiment analysis using social media content poses a challenge related to
extracting domain-specific data. In [35], Wongthongtham and Salih address this task by proposing an
ontology-based method to semantically analyze and extract social content, their experiments show that using
ontology to capture domain knowledge yield better results. Some of the related studies cited in this work are
compiled in Table 1.
Table 1. Summary of cited studies
Reference # Proposed Finding Comments related to our work
Mancuso
et al. [14]
Investigate the importance of using
reclaimed water to cope with the
problem of freshwater scarcity in the
Mediterranean area.
Based on the information related to
wastewater in the Mediterranean area,
authors confirm the necessity of reclaimed
water use to lower the pressure on
freshwater.
The study ignores to highlight the importance of the
population factor in determining whether or not
recycled water resources will be accepted and used.
Nia et al.
[16]
The investigation examines how
psychological behavior is affected
by anxiety and fear associated with
COVID-19.
According to the research, individuals'
psychological behavior. Is impacted by
anxiety sentiments and fear of COVID-19
affect.
Highlights the importance of considering sentiment
analysis in studies related to finding individual
behaviors regarding a subject (e.g., recycled water).
Vakula
and Kolli
[18]
Treats the necessity of wastewater
treatment for smart cities, and the
usage of sensors for the automation
of these treatments.
The proposition of using sensors in every
stage of wastewater treatment and
providing flowchart automation of the
treatment plant.
Authors confirm the importance of using recycled
water for the development of smart cities but lack to
provide limitations that could be associated with
people’s acceptance of using this resource.
Rozin
et al. [22]
Analyzing recycled water rejection
based on psychological aspects i.e.,
disgust, contamination, and
purification.
Accepting recycled water usage is a
psychological matter, and most people can
accept it, while a minority refuse this water
resource because of the emotion of disgust
and contamination.
The questionnaires used in the analysis were
distributed to individuals in public spaces, which
may have limited the respondents’ freedom to
express their true opinions and potentially influenced
the results due to the presence of others.
Li et al.
[24]
Using social media text content for
text mining analysis to gather public
opinion and attention on recycled
water.
Results show that the overall sentiment
regarding reclaimed water is positive,
however, a part of the public lacks
knowledge about it and still holds negative
attitudes.
The analysis focused only on the country of China,
whereas in our work, we provide a worldwide vision
of the people’s sentiment orientation toward recycled
water and also provide a detailed and advanced
framework for sentiment analysis that can aid the
future researcher in the sentiment analysis field.
Murthy
et al. [30]
The utilization of LSTM model for
text reviews' sentiment analysis.
The study provides a detailed explanation
of LSTM model and shows that the model
gives better performance in sentiment
analysis tasks with an accuracy of 85%.
The proposed model misses the implementation of
the text cleaning phase, as the content shared on
social networking platforms (e.g., Facebook,
Twitter) is usually noised. Also, the word embedding
used does not consider the sentiment factor in its
word’s representation.
Fu et al.
[33]
Using a sentiment lexicon to extract
and add sentiment information to
word representation and feed the
LSTM model with a combination of
word embedding and its associated
sentiment embedding.
Incorporating sentiment information into
word embeddings improves the accuracy of
the LSTM model for sentiment analysis
tasks
We were inspired by this work to add sentiment
word embedding to word embedding and we
included fuzzy logic linguistic functions to extract
the degree of sentiment expressed.
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3. MAIN CONCEPTS
3.1. Ontology
For any given data analysis to produce relevant and meaningful results, the quality of the data used
is a major factor. In social media platforms, Twitter only takes a part of more than 12 Terabytes of data
generated daily, which is immense and touches almost every domain. And here where ontology comes in
handy. The definition of ontology has various meanings depending on the domain where it is solicited. In
data science, the most cited definition of ontology is “An explicit specification of a conceptualization” [36].
The ontology’s main purpose is to gather domain specifics concepts, objects, and entities and describe the
relations between them in a way that form a domain knowledge base, shared, and understood by human and
machine without semantic ambiguation.
3.2. Sentiment analysis
Sentiment analysis, often referred to as opinion mining [37], is a crucial facet of natural language
processing. This research area aims to investigate human emotions present in text content by using different
approaches and algorithms for extracting the sentiment expressed and categorize it as positive, negative, or
neutral. In Figure 1, advanced methods employed by researchers and developers are depicted, illustrating
their efforts to address the challenges inherent in sentiment analysis.
3.3. Fuzzy logic
As human being, our cognition and thinking process does not follow strict binary patterns, but
rather, approximate reasoning, many decisions we make in our life are not of absolute value (i.e., true, or
false). This idea was the major foundation for the establishment of fuzzy logic theory. In [38], Zadeh, who is
acknowledged as the “father of fuzzy logic,” established the idea of fuzzy sets, which expanded upon the
traditional binary logic system of zero and one, into a set that takes into account the values in between. Fuzzy
logic aims to mimic the human decision process through fuzzy sets and membership functions that help to
quantify the degree of truthfulness and falseness [39]. By projecting this concept to the sentiment analysis
field, fuzzy logic can be used to define the degree of sentiment expressed, i.e., moving from the absolute
values “Good” or “Bad” to more sentiment degree values e.g., “Very good”, “Good”, “Neutral”, “Bad”,
“Very bad”. Forward we present some fuzzy logic components that we incorporate in our work.
Figure 1. Well-known approaches used in sentiment analysis field
a. Fuzzy set: A fuzzy set, rooted in fuzzy set theory, represents a broader concept than a conventional set. It
employs a membership function to establish a class of entities, wherein each element possesses a degree
of belongingness to the class, ranging from zero to one. This nuanced approach allows for a more flexible
and nuanced representation of uncertainty and vagueness in data and decision-making processes.
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b. Membership function: It represents a characteristic function that define the membership level of an entity
z in the class A belonging to the universe of discourse U. In an ordinary set, the characteristic function
𝑓
𝐴(𝑧) will have only two values, which are 0 or 1, however in a fuzzy set, the function characteristic will
be defined by (1).
{
𝑓
𝐴(𝑧) = 0, 𝑖𝑓 𝑧 𝑖𝑠 𝑛𝑜𝑡 𝑖𝑛 𝐴
𝑓
𝐴(𝑧): 𝑈 → [0,1]; 𝑓
𝐴(𝑧) = 1, 𝑖𝑓 𝑧 𝑖𝑠 𝑡𝑜𝑡𝑎𝑙𝑦 𝑖𝑛 𝐴
0 < 𝑓
𝐴(𝑧) < 1, 𝑖𝑓 𝑧 𝑖𝑠 𝑝𝑎𝑟𝑡𝑖𝑎𝑙𝑙𝑦 𝑖𝑛 𝐴
(1)
c. Linguistic variable: In his study [40], Zadeh examines and defines the linguistic variable as one with
words or phrases as values as opposed to numbers. For a given ‘Age’ variable, the values will be
represented by “very young”, “young”, “not young”, “quite young”, in place of number values e.g., 14,
20, 40, .... in our work, we incorporated this concept as a sentiment embedding feature.
d. Linguistic hedges: presented in [41], they represent terms that can be treated as operators for their
operands. Terms such as “very”, “quiet”, “Not”, “much”, “more or less” can act on the fuzzy sets defining
the meaning of the associated operands. Many operations are associated with linguistic hedges, such as
accentuation, convex intensification, intersection, concentration, complementation, and dilation. In our
analysis, we focused only on the last three operations.
e. Concentrator modifier: In the context of linguistic hedges, the hedge modifiers such as “very, extremely,
positively” are identified as intensifiers that can reinforce the characterization of their operands. Applying
a concentration operation to a fuzzy set A in the universe of discourse U, is denoted by CON(A)=A2 and
defined in the (2):
{ 𝑈𝐶𝑂𝑁(𝐴)(𝑦) = 𝑈𝐴
2(𝑦), 𝑦 ∈ 𝑈 (2)
f. Complement modifier: correspond to negation operation. For a fuzzy set A in U, the complement of A is
denoted by -A and defined by the (3):
{ 𝑈−𝐴(𝑦) = 1 − 𝑈𝐴(𝑦), 𝑦 ∈ 𝑈 (3)
g. Dilator modifier: also called, weakening modifiers, (e.g., “more or less”, “negatively”) represent the
opposite effect of the concentrators, thus decreasing the characterization of their operands. According to
this modifier, applying a dilation operator on a fuzzy set A, results in a fuzzy set indicated by
DIL(A)=A0.5
, defined in (4):
{ 𝑈𝐷𝐼𝐿(𝐴)(𝑦) = √𝑈𝐴(𝑦), 𝑦 ∈ 𝑈 (4)
3.4. Long shirt-term memory network (LSTM)
The long shirt-term memory (LSTM) is a type of recurrent neural network (RNN), developed by
Hochreiter and Schmidhuber [42] in 1997 to address the exploding and vanishing gradients issues
encountered by the RNN [43]. This network can hold information in the memory for a lengthy period using a
“memory cell” which makes it a context-aware network that is suitable for problems such as speech
recognition, machine translation, and natural language processing (e.g., sentiment analysis). The LSTM
model consists of a cell state, also called “memory cell” that maintains data for an extended periods, and
three gates i.e., input, forget, and output gates that regulate adding and removing data from the cell state [44].
4. PROPOSED FRAMEWORK
Our sentiment analysis framework consists of four principal modules, each of which is composed of
multiple stages, organized in a specific pipeline: data extraction module, text pre-processing module, content
vectorization, fuzzy sentiment scoring module, and modal training and analytics console module. An
overview of our framework's architecture can be found in Figure 2. We shall outline each component that
each module in our architecture is made up of in the ensuing subsection.
4.1. Data extraction
In our framework, the data extraction module is the part that focuses on gathering all the data we
used for our sentiment analysis. Knowing that social big data is scattered and diversified, it is challenging to
get fine and domain content specific. To this end, we incorporated a domain ontology component in which
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we define the searching keywords related to recycled water. Figure 3 represents our recycled water domain
ontology used to collect data from social media Twitter platform.
Forward, we used social media extractor component which is responsible for setting up the
connection with the social media application programming interface (API). We used an academic research
application for Twitter, which gives us free access to all Twitter APIs, including the full-archive search
endpoint, which allows retrieving Twitter historical data. We customized the API request to focus on getting
the following tweet attributes ‘id’ of the tweet, ‘created_at’, ‘text’, ‘source’, ‘username’, ‘location’, and
‘country’. Table 2 shows some data samples. Finally, we stored the collected data in our database for further
processing.
Figure 2. Global architecture of proposed framework
Figure 3. Recycled water domain ontology
Table 2. Samples of tweets collected using social media twitter API
Tweet Id Username Text
1572409035273699329 BurbankH2OPower Today was the last day for the Recycled H2O to GO fill station!
nnThank you to more than 100 residents who used recycled water
to keep their plants healthy. We had over 500 visits with more than
25,000 gallons of recycled water distributed .nn#recycledwater
#bwp #burbankh2opower https://t.co/qzWgUW7zMJ
1564788076160876544 ManchesterNews8 #British official: people should give up being disgusted & drink
treated sewage water.nhttps://t.co/Hy1EXnPFPg
666387525003407360 albertvilarino Did you know that today, there are more than 100K wastewater
treatment plants worldwide. #water #technology
https://t.co/kQt3mieQXt
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4.2. Text preprocessing
Users of social media platforms have the freedom of expression, reason for which the content
generated is noisy and contain symbols, Uniform resource locator (URL), hashtags, and repeated letters, so
for us to get better accurate results, we included in this module the most used techniques in natural language
pre-processing that involves, cleaning the text from URLs, extra whitespaces, numbers and screen names,
then, substitute emojis by their text representation, replacing abbreviation (e.g., gr8 replaced by Great), along
with handling contraction (e.g., don’t become “do not” hasn’t become “has not”). We also proceed by
removing stop words (e.g., on, the, and it.). Finally, we lowercase and lemmatize the outputted text content.
4.3. Features extraction and fuzzy sentiment scoring
In the process of developing our model, we prepared in this stage the dataset and features required
for us to examine the public’s sentiment orientation toward recycled water. We utilized the cleaned text from
the previous stage as input for word embeddings in order to represent text vocabulary and capture words
relations, syntactics and semantic information [45], for this matter, we exploited an open-source python
library called Gensim [46] and Word2Vec [47] algorithm to vectorize our text and use the results as input
weight for our model. However, as word embeddings helps learning words semantics and relations but not
sentiment, we proceed by incorporation a fuzzy sentiment scoring as a sentiment embedding of words,
denoted st, that will add up to word embeddings, denoted et (i.e., wt=st ⊕ et), for sentiment-oriented text
representation.
For fuzzy sentiment scoring calculation for a given text input, we start by tagging each word using
Part-of-Speech tagger, and for every opinionated word found, we look in the lexical resource SentiWordNet
[48] for the initial polarity value µ(s). If not present, we seek in WordNet (i.e., a large dictionary database) to
get the first matched synonym and look back in SentiWordNet for the associated value. This initial score
value can be modified using the fuzzy functions mentioned earlier, whether by inverting the value, increment
it, or by decrementing it based on the existence of a compliment, concentrator, or dilator hedge, respectively.
The final fuzzy word sentiment embedding is concatenated with its corresponding word embedding is used as
the LSTM model’s final input.
4.4. Model training and sentiment analysis
As we mentioned earlier, we used the LSTM algorithm to tackle sentiment analysis. And we used
the IMDB dataset (i.e., a well-known movie reviews dataset used for natural language processing) for our
model training and testing processes. Initially, we cleaned this dataset based on the same pipeline from our
framework, then we used the fuzzy functions along with SentiWordNet and WordNet to construct word
sentiment embeddings. Forward we apply word embeddings using Word2Vec and pass the results as input to
the LSTM model. After we experimented with the network hyperparameters using a trial-and-error process,
we fixed the dimension of word embeddings to 300 and set the max_features to 3,000 as it provides a good
variety of captured keywords, also we set a spacialDropout1D layer to 0.3 to avoid overfitting, we used
Adam as the optimizer. We experimented also batches size of 32 and 64, and we fixed the value to 32 as it
requires less memory and yield good performance, and we choose the accuracy metric for performance
evaluation. We trained our model on 66% of the IMDB reviews dataset, and we set the number of epochs to
15 because we notice that after this number the validation accuracy began to decrease and the model overfit.
With this tunning we got a final accuracy of 92.3%. Lastly, we applied our model to the dataset we collected
from Twitter API related to recycled water subject and the results are shown in the section below.
5. RESULTS AND DISCUSSION
5.1. Spatial results of public participation in recycled water subject
Our conducted sentiment analysis on social media content reveals a significant disparity among
countries in terms of public engagement and interaction with the topic of recycled water, as illustrated in
Figure 4. To further investigate this, we compared our findings with the geolocation data of smart cities
worldwide, as depicted in Figure 5. This comparison allows us to observe the correlation between public
participation in the recycled water discourse and countries with smart city initiatives.
The United States topped the list of countries that had the most engagement with the topic of
recycled water, followed by Canada, which can be attributed to the growing challenges of freshwater scarcity
faced by the country [49]. India ranked next, while African countries were found to have limited participation
in discussions about recycling water. The comparison of our world map results with the finding of [50]
presented in Figure 5 where the author reveals the geo-location places of smart and digital cities, shows that
countries with more smart city vision and advanced digital implementation. The citizens are relatively active
regarding the subject of recycled water.
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Figure 4. Results of public participation to recycled water
Figure 5. Digital and smart cities geo-location on the world map
5.2. Temporal results of public participation in recycled water subject
Utilizing data gathered from the Twitter platform spanning the years 2013 to 2022, we conducted an
analysis of public engagement with the subject of recycled water. Our findings clearly indicate a substantial
increase in public interest in this topic. This upward trend is visually evident in Figure 6, which illustrates the
growing volume of publications and discussions related to recycled water over this extended timeframe.
Figure 6. Public posts on Twitter regarding recycler water subject
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5.3. Public sentiment orientation
The objective of our sentiment analysis in this paper is to extract and assess public sentiment toward
recycled water. Additionally, we aim to gauge the public’s willingness to engage in the development of their
cities, aligning with the smart city vision for intelligent water management. Based on the results shown in
Figure 7, we found that in countries with higher public participation in the recycled water subject, the number
of posts expressing positive sentiment is relatively similar to the ones expressing negative sentiment. This
suggests that the fear and negative opinions about this subject may not be as widespread as they appear.
Additionally, as shown in Figure 8, we also noticed that the number of positive.
Figure 7. Public sentiment orientation by country
Figure 8. Public sentiment orientation by year
Sentiments towards recycled water have been on the rise over the years. In 2013, the percentage of
positive posts among users was 21.85%, but by 2022, this percentage had increased to 27.87%. This
represents a 6.02% increase between 2013 and 2022. These results suggest that people are becoming more
aware of the challenges posed by water shortage, and the potential of recycled water to address this issue.
Furthermore, it may serve as an incentive for governments and stakeholders to invest more in the execution
of reclaimed water projects.
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To better understand the public’s perception of reclaimed water, we analyzed the most frequently
used words in both positive and negative text content from our dataset. We found that the words “health”,
“worries”, “safety”, “radioactive”, “disgust”, “S**t”, “Covid”, and “worse” had the highest frequencies in
negative text content. This suggests that the motivation behind recycled water disapproval by the public’s is
related mostly to the worries about safety, rather than disgust. In contrast, in positive text content, we found
words such as “sensors”, “enhance”, “IoT”, “data” and “forward” as shown in Figure 9, indicating that the
public is optimistic and trusts the advancements in technology to improve recycled water solutions.
Figure 9. High frequency words from positive text content
6. CONCLUSION
In our work, we focused on two main elements. Firstly, we aimed to enhance the sentiment analysis
model we used in our previous papers by incorporating a domain ontology to collect domain-specific data,
and using a combination of word embedding along with a sentiment word embedding. Also, we tried to give
a step-by-step explanation of our framework to help future researchers who are concerned about utilizing
fuzzy logic and deep learning for sentiment analysis. Secondly, we aimed through our paper to gain insight
into the global public sentiment towards recycled water and its impact on citizen’s acceptance and intension
to use this new water resource, so we can help investors and governments direct their sensibilization
campaigns towards removing the ‘Yuck sentiment’ barrier attached to recycled water and attain the smart
water management goals.
Our findings reveal that public engagement is more pronounced in countries with advanced
economic development and active smart city initiatives. Notably, we observed a rising trend in the percentage
of positive sentiment related to recycled water over the years. Simultaneously, the growing concern among
the public is oriented more towards the safety of this new resource in comparison to the disgust sentiment,
which can highlight that overcoming the “yuck factor” barrier is possible through advancements in research,
development, and the implementation of smart city visions for intelligent water management systems.
In our work, we encountered certain limitations, including the time-intensive nature of data
collection from the Twitter API and model training. Additionally, we did not incorporate demographic
information linked to Twitter user accounts, such as educational background, age, and gender, into our
research. Including these details could enhance the analysis and provide deeper insights into public
awareness of the potential of recycled water.
In our future research, we intend to delve into the technologies employed in the recycled water
domain. Our goal is to assess whether citizens possess sufficient knowledge about these technologies, their
processes, and their efficacy. Additionally, we plan to incorporate demographic data into our analysis of
public acceptance of reclaimed water use. By doing so, we aim to enable governments and companies to
tailor their awareness campaigns more effectively, targeting specific demographic groups and fostering
increased investment in recycled water solutions.
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BIOGRAPHIES OF AUTHORS
Mohamed Bahra a software engineer and currently in the last year as a Ph.D
student, his field of research is related to big data, smart city, and data science. He teached
data science modules as a temporary teacher during his period of Ph.D. research, also he
worked as a software engineer at the Ministry of Interior of Morocco, and he supervised
students for the realization of their end-of-study projects at the Computer Science
Department of Abdelmalek Essadi University, Morocco. His skills are related to sentiment
analysis, information extraction, social network analysis, semantic web, ontologies, natural
language processing, machine and deep learning. He can be contacted at email:
bahra002@gmail.com and mohamed.bahra@etu.uae.ac.ma. His profile can be found at
https://www.researchgate.net/profile/Mohamed-Bahra.
Abdelhadi Fennan he is currently works at the Computer Science Department
of Abdelmalek Essaâdi University, Morocco. Abdelhadi does research in artificial
intelligence, information systems, and software engineering. His disciplines are related to
artificial intelligence, software engineering, information systems, higher education,
educational technology, curriculum theory, and his skills are of the fields of e-learning,
online learning, software engineering, artificial intelligence, semantic web, sentiment
analysis, homogenization, technology enhanced learning, and competitive intelligence. He
can be contacted at email: afennan@gmail.com. His profile can be found at
https://www.researchgate.net/profile/Abdelhadi-Fennan.