Climate services involve the timely production, translation, and delivery of useful climate data, information
and knowledge for societal decision making. In order to create climate services for farmers that are truly
integrated with user-centric design into the development process in an African context, the study has
finished an important and crucial step by conducting a literature review and designing a prototype for the
application. The goal of this study was to create climate services for farmers in an African context that are
genuinely integrated with user-centric design. This led to the co-design and development and integration
of a mobile application that provide climate and weather information as well as agricultural
information for the main crops such millet, maize and sorghum. The research applied using qualitative
research using interview with 3 farmers in the field using random sampling with the approach to inform
the study.
This document discusses how improved access to climate and weather information can help farmers adapt to climate change. It provides an example of a World Bank project that developed agroweather decision support systems in Kenya and Ethiopia. The project uses ICT tools like SMS, smartphones, and radio to disseminate seasonal forecasts, advisories, and early warnings to farmers. It aims to increase farmers' adaptive capacity by helping them make more informed management decisions about planting, fertilizing, and choosing crops. The document also outlines challenges to accessing weather data and how ICT can help address issues of data availability, usability, and timeliness to provide localized information for farmers' micro-environments.
2Final_Roles of ICT in Agriculture Africa _send.pptxHappyness Mkumbo
The document discusses the role of ICT in improving agriculture in Africa. It notes that agriculture makes up a large portion of Africa's GDP and workforce but faces challenges from climate change and outdated practices. ICT can help address this by providing farmers access to weather data, market prices, financial services, and best practices via cell phones and platforms. Examples discussed include M-Farm in Kenya and Tigo Kilimo in Tanzania. The document recommends establishing an agricultural hub, building human capacity, and empowering women to further support the use of ICT in African agriculture.
ICTs have the potential to transform African agriculture by making practices more efficient and data-driven. They can provide farmers with access to information on weather, markets, finances, and best practices. Examples discussed include M-Fesa for financial services, Tigo Kilimo for agricultural advisories via mobile phones, and e-Soko for connecting farmers to buyers. Challenges to adoption include lack of infrastructure in rural areas, low farmer incomes, and gender inequality. Overall, ICTs show promise for increasing yields, reducing risks, and supporting smallholder farmers if these challenges can be addressed.
Establishing a platform for dialogue among key Departments at the national an...Soksophors yim
Participatory platforms enable the co-production process of climate services (CS) and provide an
opportunity to strengthen the link between the DoM and technical departments of MAFF through
regular exchange of climate information and understanding of the CS demand from agriculture
sector to develop tailored agro-advisories for planning and decision-making.
•
Effective dissemination of agro-advisories to last-mile users requires a combination of approach
(LTAC), enhancement of decision-support tool (CDT + SESAME), and utilization of various
communication channels (printed posters, Telegram, face-to-face meetings) compounded with
multi-stakeholder cooperation including government, private sector, NGOs, relevant programs and
farmer organizations, among others.
•
Collaboration with national hydromet center is critical for timely access to official seasonal climate
and short-term weather forecasts for the translation into agro-advisory. However, this necessitates
improved capacity of hydromet to provide reliable and accurate downscaled climate information
which entails further technical and financial support from government, potential donors, and private
sector cooperation to deliver agro advisory that is most appropriate to farmers’ needs on the ground.
This paper proposes a fuzzy logic-based individual crop advisory system that provides crop-specific advisories to farmers based on weather input data. The system utilizes expert agricultural knowledge and weather data to generate automatic advisories tailored to a farmer's specific crop type, location, and growth stage. It was developed using PHP for the front-end and MATLAB for the GUI. The system was tested on both realistic and randomly generated weather data, and the success rates for providing accurate advisories with both data types were calculated. The system aims to provide more specific advisories to farmers compared to existing region-based advisory services.
Applying Climate Information to Achieve the Sustainable Development GoalsGreg Benchwick
The document discusses how improving climate information and early warning systems in Africa could help achieve the UN Sustainable Development Goals. It outlines how better weather data can boost agricultural production, protect lives from extreme weather like lightning strikes, and support climate-resilient development. Providing this information to vulnerable groups like smallholder farmers has the potential to increase incomes, food security and education opportunities on the continent.
Authors are invited to submit theoretical or empirical papers in all aspects of management, including strategy, human resources, marketing, operations, technology, information systems, finance and accounting, business economics, and public sector management. IJMRR is an international forum for research that advances the theory and practice of management. The journal publishes original works with practical significance and academic value.
This document discusses how improved access to climate and weather information can help farmers adapt to climate change. It provides an example of a World Bank project that developed agroweather decision support systems in Kenya and Ethiopia. The project uses ICT tools like SMS, smartphones, and radio to disseminate seasonal forecasts, advisories, and early warnings to farmers. It aims to increase farmers' adaptive capacity by helping them make more informed management decisions about planting, fertilizing, and choosing crops. The document also outlines challenges to accessing weather data and how ICT can help address issues of data availability, usability, and timeliness to provide localized information for farmers' micro-environments.
2Final_Roles of ICT in Agriculture Africa _send.pptxHappyness Mkumbo
The document discusses the role of ICT in improving agriculture in Africa. It notes that agriculture makes up a large portion of Africa's GDP and workforce but faces challenges from climate change and outdated practices. ICT can help address this by providing farmers access to weather data, market prices, financial services, and best practices via cell phones and platforms. Examples discussed include M-Farm in Kenya and Tigo Kilimo in Tanzania. The document recommends establishing an agricultural hub, building human capacity, and empowering women to further support the use of ICT in African agriculture.
ICTs have the potential to transform African agriculture by making practices more efficient and data-driven. They can provide farmers with access to information on weather, markets, finances, and best practices. Examples discussed include M-Fesa for financial services, Tigo Kilimo for agricultural advisories via mobile phones, and e-Soko for connecting farmers to buyers. Challenges to adoption include lack of infrastructure in rural areas, low farmer incomes, and gender inequality. Overall, ICTs show promise for increasing yields, reducing risks, and supporting smallholder farmers if these challenges can be addressed.
Establishing a platform for dialogue among key Departments at the national an...Soksophors yim
Participatory platforms enable the co-production process of climate services (CS) and provide an
opportunity to strengthen the link between the DoM and technical departments of MAFF through
regular exchange of climate information and understanding of the CS demand from agriculture
sector to develop tailored agro-advisories for planning and decision-making.
•
Effective dissemination of agro-advisories to last-mile users requires a combination of approach
(LTAC), enhancement of decision-support tool (CDT + SESAME), and utilization of various
communication channels (printed posters, Telegram, face-to-face meetings) compounded with
multi-stakeholder cooperation including government, private sector, NGOs, relevant programs and
farmer organizations, among others.
•
Collaboration with national hydromet center is critical for timely access to official seasonal climate
and short-term weather forecasts for the translation into agro-advisory. However, this necessitates
improved capacity of hydromet to provide reliable and accurate downscaled climate information
which entails further technical and financial support from government, potential donors, and private
sector cooperation to deliver agro advisory that is most appropriate to farmers’ needs on the ground.
This paper proposes a fuzzy logic-based individual crop advisory system that provides crop-specific advisories to farmers based on weather input data. The system utilizes expert agricultural knowledge and weather data to generate automatic advisories tailored to a farmer's specific crop type, location, and growth stage. It was developed using PHP for the front-end and MATLAB for the GUI. The system was tested on both realistic and randomly generated weather data, and the success rates for providing accurate advisories with both data types were calculated. The system aims to provide more specific advisories to farmers compared to existing region-based advisory services.
Applying Climate Information to Achieve the Sustainable Development GoalsGreg Benchwick
The document discusses how improving climate information and early warning systems in Africa could help achieve the UN Sustainable Development Goals. It outlines how better weather data can boost agricultural production, protect lives from extreme weather like lightning strikes, and support climate-resilient development. Providing this information to vulnerable groups like smallholder farmers has the potential to increase incomes, food security and education opportunities on the continent.
Authors are invited to submit theoretical or empirical papers in all aspects of management, including strategy, human resources, marketing, operations, technology, information systems, finance and accounting, business economics, and public sector management. IJMRR is an international forum for research that advances the theory and practice of management. The journal publishes original works with practical significance and academic value.
A Proposed Model for Mobile Cloud Computing in Agricultureijsrd.com
This paper presents the recent development and application of mobile phones and cloud computing in agriculture. Basic concepts and technologies associated with mobile phones and cloud computing is highlighted. For better communication, sharing of information and profitability in agriculture, there is need for collaboration of cloud computing and mobile technology. This paper presents a framework in which a farmer can utilize mobile cloud computing on their handsets using various applications, to assist them for relatively better cultivation and marketing. The main application of this proposed framework is focused on to eliminate the problem of data storage, computational processing and sharing of information
Internet of Things Hydroponics Agriculture (IoTHA) Using Web/Mobile ApplicationsIRJET Journal
This document discusses using Internet of Things (IoT) technology to develop an automated hydroponics system using web and mobile applications. The system would monitor and control nutritional and environmental parameters to optimize plant growth without soil. Specifically, it details a study that developed an IoT-driven hydroponics testbed to cultivate tomatoes and collect data on their nutrient requirements and productivity. The results showed the plants grew well based on computer vision and visual analysis. Adopting this type of hydroponics farming using IoT could help address limited agricultural land and increase production capacity by allowing year-round farming.
Drought is possibly the most complex and least understood of natural hazards. The effects of drought accumulate slowly and linger for years. It is estimated that 380 million people, 38% of the world’s rural poor, live in the arid and semi-arid tropics (SAT). Of those who are vulnerable to drought, more than 90% are either smallholder farmers or landless laborers. The Committee on Science and Technology for the United Nations Convention to Combat Desertification, in its fifth session last year, issued a note on strategies for communicating relevant information on combating the effects of drought.
Factors Influencing Adoption of New Irrigation Technologies on Farms in Moroc...Agriculture Journal IJOEAR
The objective of this article is to identify the determinants of the adoption of new irrigation technologies in Moroccan agriculture. The research is carried out on a sample of 82 farmers from the Souss-Massa region (Morocco). The results from the estimation of a binary logit model show that the variables: Age, level of education, non-farm income, perceived utility, possession of a computer, farm size, access to credit, ease of use, influence the probability of adoption of new irrigation technologies among farmers. The theoretical and managerial implications of this research are discussed.
This document summarizes a case study assessing the socio-economic benefits of user-tailored early warning systems for coffee and maize farmers in Cusco, Peru. It finds that the socio-economic benefits of enhanced climate services for the two crops over 10 years would be approximately $10 million for the Cusco region and over $100 million for Peru. The study uses a stated preference methodology involving surveys of over 60 smallholder farmers to estimate their willingness to pay for hypothetical early warning systems. The systems would provide alerts for coffee rust outbreaks and frost/heat waves to help farmers implement preventative measures and reduce crop losses from climate impacts. The results indicate climate services could significantly increase resilience and benefits for farmers, but awareness
Analysis and Design of a Tea Farming Information SystemIRJET Journal
This document analyzes and designs a tea farming information system to address limitations of existing systems and meet the information needs of tea farmers. It identifies farmers' key information needs including inputs, technologies, marketing and credit. Existing systems like extension officers, media, and mobile apps are found to have weaknesses like limited reach, high costs, and unreliable information. The proposed system is designed using an agile methodology to iteratively deliver a flexible software product that provides timely, targeted information to farmers to improve decision making, productivity and profits.
Internet of things (IoT) smart technology enables new digital agriculture. Technology has become necessary to address today's challenges, and many
sectors are automating their processes with the newest technologies. By maximizing fertiliser use to boost plant efficiency, smart agriculture, which is based on IoT technology, intends to assist producers and farmers in
reducing waste while improving output. With IoT-based smart farming, farmers may better manage their animals, develop crops, save costs, and
conserve resources. Climate monitoring, drought detection, agriculture and production, pollution distribution, and many more applications rely on the weather forecast. The accuracy of the forecast is determined by prior
weather conditions across broad areas and over long periods. Machine learning algorithms can help us to build a model with proper accuracy. As a result, increasing the output on the limited acreage is important. IoT smart farming is a high-tech method that allows people to cultivate crops cleanly
and sustainably. In agriculture, it is the use of current information and
communication technologies.
Climate Information for Resilient Development and Adaptation (CIRDA) and its ...NAP Events
Presentation by: Bonizella Biagini
4.1 Climate services in support of NAPs
This event will bring together experts involved in the provision of climate services and testimony from countries of how climate services are being used to support decision-making and effective adaptation. The event will start with brief statements, and will be followed by a panel discussion, where participants from the floor will have the opportunity to engage the panelists with questions or comments. The panel will demonstrate the practical benefits of climate services in support of climate risk management and adaptation to climate variability and change. It will also provide lessons learned through various activities being implemented at regional and national level.
Using Weather and Climate Information for Agricultural Insurance in AfricaGreg Benchwick
This document discusses how improved weather and climate information can help foster resilience for vulnerable populations in Africa through agricultural insurance programs. It notes that most farmers in developing countries face significant weather risks but lack affordable insurance options. Index-based insurance that pays out based on weather station data, rather than individual farm assessments, has potential to address this by lowering costs. However, such programs require reliable, long-term weather and agricultural data, as well as effective communication systems. Regional initiatives like the African Risk Capacity pool sovereign risk across countries to provide emergency funding in response to large-scale disasters. Overall, successful agricultural insurance requires a holistic risk management approach incorporating multiple strategies at national and local levels.
Presented by Younis Gismalla (HRC), Yasir Mohamed (HRC), Gijs Simons (eLEAF), Maurits Voogt(eLEAF), Bharat Sharma (IWMI), Giriraj amarnath (IWMI) and Vladimir Smakhtin (IWMI) at the 4th Nile Basin Development Forum, 6-7 October 2014, Nairobi, Kenya.
Fuzzy Logic Modelling for Disease Severity Prediction in Cotton Crop using We...IRJET Journal
This document describes a study that developed a fuzzy logic model to predict the severity of cotton leaf curl disease (CLCuD) based on weather parameters. The model used data on maximum and minimum temperature, relative humidity, rainfall, and sunshine collected weekly over 4 years along with corresponding disease incidence and severity levels. 89 fuzzy rules were generated to relate the weather input variables to the disease severity output. The model achieved 90% accuracy in predicting disease severity based on a test dataset, demonstrating its ability to capture complex relationships between weather and disease. A sensitivity analysis identified the most influential weather parameters on disease severity prediction. The fuzzy logic approach provided a flexible way to model this uncertain, non-linear agricultural problem.
application of datascience in agriculture.pdfarchana gupthan
The document discusses how data science can help address various challenges facing the agriculture industry. It outlines challenges such as climate change, water scarcity, soil degradation, pests/diseases, and food security that impact productivity and profitability. It then describes how data science techniques like precision agriculture using sensors and drones, soil analysis, satellite imagery, and disease/pest detection algorithms can help farmers optimize inputs, increase yields, and ensure food safety and security. Overall, the document advocates that data science has great potential to revolutionize agriculture by making it more efficient and sustainable.
A New Vision for Weather and Climate Services in Africa - Executive SummaryGreg Benchwick
The collection, analysis and distribution of reliable climate and weather information has the potential to greatly benefit efforts by African nations to reduce poverty, build resilience and adapt to a changing climate. An upcoming UNDP publication will examine the climate information and services space in sub-Saharan Africa, taking a critical look at what hasn’t worked, why it’s important and possible solutions.
This comprehensive peer-reviewed report is being prepared by the UNDP’s Programme on Climate Information for Resilient Development in Africa (CIRDA), a four-year programme supporting work in 11 African Least Developed Countries with $50 million from the Global Environment Facility’s Least Developed Countries Fund (LDCF). As such it builds on the expertise of the CIRDA technical team, the products of several workshops, and initial consultations between CIRDA experts and public and private representatives in partner countries.
The full report is due out soon. To receive the full report, email Greg Benchwick at gregory.benchwick@undp.org.
Big data approaches can help rice farmers in Latin America adapt to climate change by providing real-time climate and cropping advice. A pilot program in Colombia combined rice yield and weather data to identify climate patterns and recommend optimal planting times. Farmers who followed the advice had successful harvests, while those who did not lost their crops and inputs. The program aims to scale this approach to other major rice producers in Latin America, including Argentina, Brazil, and Uruguay. Doing so may help reduce yield losses, increase adaptive capacity, and revolutionize agricultural advisory services.
1) Smart ICT technologies like mobile phones and web portals can provide smallholder farmers in Africa with weather, water, and agricultural advisories to help improve resilience to climate change.
2) The International Water Management Institute has developed systems to provide near real-time climate, vegetation, and water information via SMS and online to help farmers, irrigation boards, and others make better management decisions.
3) The concept involves monitoring crop conditions in registered farmer fields using high-resolution satellite data and sending simple regular advisories on water and inputs via SMS to optimize farm profits.
The information and communication is a vital resource for agriculture and may contribute considerably to make sure food security and property by making awareness and talent development through access to information. The initial and most distinguished player of information delivery is public sector extension services that from past few years are sometimes criticized for their ineffective targeting, poor reach and also the vast body value of delivering information. Since past few years, the forceful increase in mobile penetration even in rural areas has result in evolution of ICT-based extension services models to publicize agriculture connected information. The goal of discrimination the mobile phone-enabled info delivery mechanism is to possess inclusive growth by reducing the information gap between enormous and little farmers and by making awareness. With this end, this paper analysis specific objectives excluding distinguishing potential desires of data and also the existing sources, includes the meta analysis of mobile impact studies chiefly in India in terms of up farmers socio-economic conditions by being higher connected to extension services, improved access to markets and higher science info.
KPI Deployment for Enhanced Rice Production in a Geo-Location Environment us...ijwmn
Rice production plays a significant role in food security in the globe. The automation of rice production remains the paradigm shift to meet up with the consumer demand considering the tremendous increase in consumption rate. The paper aimed at implementing some selected key performance indicators (KPIs) for enhanced rice production by addressing five major challenges that face rice farmers, especially in Nigeria. The Non-availability of water/rain for year-round cultivation, disproportionate application of fertilizer, weed control/prevention, pest/disease control, and rodents and bird’s invasion are outlined as observed constraints. A Zigbee-based Enhanced Wireless Sensor Network (eWSN) was used to model various network scenarios to demonstrate data sensing of different environmental variables in a given farm land. This was achieved by varying network devices at different scenarios using OPNET simulator and understudying the network performances. Each new set of network devices was integrated to a Zigbee Coordinator (ZC) which assigns an address to its members and forms a personal area network (PAN), thus representing data sensing of a particular environmental variable. Three different scenarios were designed and simulated in the study. Each of the temperature and humidity, motion and soil nutrient sensors generated about 29bps of traffic. At the Coordinators, steady stream of traffic was received. The temperature and humidity Coordinators, received a traffic of 64bps each, while the soil nutrient Coordinator received data traffic of 96bps. The outcome of the design demonstrates effective communication between different network components and provides insight on how WSN could be used simultaneously to monitor a number of different environmental variables on a farm field. By implementing the KPIs, the simulation result provided an estimated yield increase from 2.2 to 8.7 metric ton per hectare of a rice farm.
KPI DEPLOYMENT FOR ENHANCED RICE PRODUCTION IN A GEO-LOCATION ENVIRONMENT USI...ijwmn
Rice production plays a significant role in food security in the globe. The automation of rice production
remains the paradigm shift to meet up with the consumer demand considering the tremendous increase in
consumption rate. The paper aimed at implementing some selected key performance indicators (KPIs) for
enhanced rice production by addressing five major challenges that face rice farmers, especially in Nigeria.
The Non-availability of water/rain for year-round cultivation, disproportionate application of fertilizer,
weed control/prevention, pest/disease control, and rodents and bird’s invasion are outlined as observed
constraints. A Zigbee-based Enhanced Wireless Sensor Network (eWSN) was used to model various
network scenarios to demonstrate data sensing of different environmental variables in a given farm land.
This was achieved by varying network devices at different scenarios using OPNET simulator and
understudying the network performances. Each new set of network devices was integrated to a Zigbee
Coordinator (ZC) which assigns an address to its members and forms a personal area network (PAN), thus
representing data sensing of a particular environmental variable. Three different scenarios were designed
and simulated in the study. Each of the temperature and humidity, motion and soil nutrient sensors
generated about 29bps of traffic. At the Coordinators, steady stream of traffic was received. The
temperature and humidity Coordinators, received a traffic of 64bps each, while the soil nutrient
Coordinator received data traffic of 96bps. The outcome of the design demonstrates effective
communication between different network components and provides insight on how WSN could be used
simultaneously to monitor a number of different environmental variables on a farm field. By implementing
the KPIs, the simulation result provided an estimated yield increase from 2.2 to 8.7 metric ton per hectare
of a rice farm.
IoT-oriented software platform applied to sensors-based farming facility with...journalBEEI
This work describes the design of innovative IoT-oriented farm management system that employs low-cost WSN for detecting soil, environmental and crops parameters that properly processed, in combination with weather forecasts, are used to determine future farming activities based on agronomic models implemented in the software platform. Goals of carried out research activity are to guarantee production both qualitatively and quantitatively of cultivated crops, to increase company income and reduce environmental impacts; achieving these objectives is a prerequisite for implementing of sustainable agriculture. Connection between traditional cropping systems and innovative technologies is achieved through the utilization of low-cost wireless electronic modules for acquiring data from connected sensors. The fertigation system operation is supported by solar-powered low-cost WSN capable of constantly monitoring soil and environmental parameters; thanks to sensor nodes properly positioned in cultivated land or greenhouse, interest parameters of both air and soil are detected and transmitted to on-cloud database, to allow monitoring and remote control from enabled users (farmer or agronomist). For this aim, an application specifically realized and tested during the different fertigation system’s functional tests, allows users to visualize and eventually remotely intervene by using a smart-phone or tablet.
This document discusses emerging opportunities to deliver relevant weather and climate information and services to smallholder farmers at scale. It outlines the need for spatially and temporally detailed historical, monitored, predicted, and projected climate data. Participatory approaches like PICSA can help communicate this information and support farmers' decision making. Effective partnerships are needed between meteorological agencies, researchers, extension services, and the private sector to generate localized climate data, train intermediaries, and ensure information reaches farmers through various communication channels. With improved access to actionable climate information and support systems, smallholder farmers' food security and livelihoods can be enhanced.
Home security is of paramount importance in today's world, where we rely more on technology, home
security is crucial. Using technology to make homes safer and easier to control from anywhere is
important. Home security is important for the occupant’s safety. In this paper, we came up with a low cost,
AI based model home security system. The system has a user-friendly interface, allowing users to start
model training and face detection with simple keyboard commands. Our goal is to introduce an innovative
home security system using facial recognition technology. Unlike traditional systems, this system trains
and saves images of friends and family members. The system scans this folder to recognize familiar faces
and provides real-time monitoring. If an unfamiliar face is detected, it promptly sends an email alert,
ensuring a proactive response to potential security threats.
In the era of data-driven warfare, the integration of big data and machine learning (ML) techniques has
become paramount for enhancing defence capabilities. This research report delves into the applications of
big data and ML in the defence sector, exploring their potential to revolutionize intelligence gathering,
strategic decision-making, and operational efficiency. By leveraging vast amounts of data and advanced
algorithms, these technologies offer unprecedented opportunities for threat detection, predictive analysis,
and optimized resource allocation. However, their adoption also raises critical concerns regarding data
privacy, ethical implications, and the potential for misuse. This report aims to provide a comprehensive
understanding of the current state of big data and ML in defence, while examining the challenges and
ethical considerations that must be addressed to ensure responsible and effective implementation.
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A Proposed Model for Mobile Cloud Computing in Agricultureijsrd.com
This paper presents the recent development and application of mobile phones and cloud computing in agriculture. Basic concepts and technologies associated with mobile phones and cloud computing is highlighted. For better communication, sharing of information and profitability in agriculture, there is need for collaboration of cloud computing and mobile technology. This paper presents a framework in which a farmer can utilize mobile cloud computing on their handsets using various applications, to assist them for relatively better cultivation and marketing. The main application of this proposed framework is focused on to eliminate the problem of data storage, computational processing and sharing of information
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Drought is possibly the most complex and least understood of natural hazards. The effects of drought accumulate slowly and linger for years. It is estimated that 380 million people, 38% of the world’s rural poor, live in the arid and semi-arid tropics (SAT). Of those who are vulnerable to drought, more than 90% are either smallholder farmers or landless laborers. The Committee on Science and Technology for the United Nations Convention to Combat Desertification, in its fifth session last year, issued a note on strategies for communicating relevant information on combating the effects of drought.
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The objective of this article is to identify the determinants of the adoption of new irrigation technologies in Moroccan agriculture. The research is carried out on a sample of 82 farmers from the Souss-Massa region (Morocco). The results from the estimation of a binary logit model show that the variables: Age, level of education, non-farm income, perceived utility, possession of a computer, farm size, access to credit, ease of use, influence the probability of adoption of new irrigation technologies among farmers. The theoretical and managerial implications of this research are discussed.
This document summarizes a case study assessing the socio-economic benefits of user-tailored early warning systems for coffee and maize farmers in Cusco, Peru. It finds that the socio-economic benefits of enhanced climate services for the two crops over 10 years would be approximately $10 million for the Cusco region and over $100 million for Peru. The study uses a stated preference methodology involving surveys of over 60 smallholder farmers to estimate their willingness to pay for hypothetical early warning systems. The systems would provide alerts for coffee rust outbreaks and frost/heat waves to help farmers implement preventative measures and reduce crop losses from climate impacts. The results indicate climate services could significantly increase resilience and benefits for farmers, but awareness
Analysis and Design of a Tea Farming Information SystemIRJET Journal
This document analyzes and designs a tea farming information system to address limitations of existing systems and meet the information needs of tea farmers. It identifies farmers' key information needs including inputs, technologies, marketing and credit. Existing systems like extension officers, media, and mobile apps are found to have weaknesses like limited reach, high costs, and unreliable information. The proposed system is designed using an agile methodology to iteratively deliver a flexible software product that provides timely, targeted information to farmers to improve decision making, productivity and profits.
Internet of things (IoT) smart technology enables new digital agriculture. Technology has become necessary to address today's challenges, and many
sectors are automating their processes with the newest technologies. By maximizing fertiliser use to boost plant efficiency, smart agriculture, which is based on IoT technology, intends to assist producers and farmers in
reducing waste while improving output. With IoT-based smart farming, farmers may better manage their animals, develop crops, save costs, and
conserve resources. Climate monitoring, drought detection, agriculture and production, pollution distribution, and many more applications rely on the weather forecast. The accuracy of the forecast is determined by prior
weather conditions across broad areas and over long periods. Machine learning algorithms can help us to build a model with proper accuracy. As a result, increasing the output on the limited acreage is important. IoT smart farming is a high-tech method that allows people to cultivate crops cleanly
and sustainably. In agriculture, it is the use of current information and
communication technologies.
Climate Information for Resilient Development and Adaptation (CIRDA) and its ...NAP Events
Presentation by: Bonizella Biagini
4.1 Climate services in support of NAPs
This event will bring together experts involved in the provision of climate services and testimony from countries of how climate services are being used to support decision-making and effective adaptation. The event will start with brief statements, and will be followed by a panel discussion, where participants from the floor will have the opportunity to engage the panelists with questions or comments. The panel will demonstrate the practical benefits of climate services in support of climate risk management and adaptation to climate variability and change. It will also provide lessons learned through various activities being implemented at regional and national level.
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This document discusses how improved weather and climate information can help foster resilience for vulnerable populations in Africa through agricultural insurance programs. It notes that most farmers in developing countries face significant weather risks but lack affordable insurance options. Index-based insurance that pays out based on weather station data, rather than individual farm assessments, has potential to address this by lowering costs. However, such programs require reliable, long-term weather and agricultural data, as well as effective communication systems. Regional initiatives like the African Risk Capacity pool sovereign risk across countries to provide emergency funding in response to large-scale disasters. Overall, successful agricultural insurance requires a holistic risk management approach incorporating multiple strategies at national and local levels.
Presented by Younis Gismalla (HRC), Yasir Mohamed (HRC), Gijs Simons (eLEAF), Maurits Voogt(eLEAF), Bharat Sharma (IWMI), Giriraj amarnath (IWMI) and Vladimir Smakhtin (IWMI) at the 4th Nile Basin Development Forum, 6-7 October 2014, Nairobi, Kenya.
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This document describes a study that developed a fuzzy logic model to predict the severity of cotton leaf curl disease (CLCuD) based on weather parameters. The model used data on maximum and minimum temperature, relative humidity, rainfall, and sunshine collected weekly over 4 years along with corresponding disease incidence and severity levels. 89 fuzzy rules were generated to relate the weather input variables to the disease severity output. The model achieved 90% accuracy in predicting disease severity based on a test dataset, demonstrating its ability to capture complex relationships between weather and disease. A sensitivity analysis identified the most influential weather parameters on disease severity prediction. The fuzzy logic approach provided a flexible way to model this uncertain, non-linear agricultural problem.
application of datascience in agriculture.pdfarchana gupthan
The document discusses how data science can help address various challenges facing the agriculture industry. It outlines challenges such as climate change, water scarcity, soil degradation, pests/diseases, and food security that impact productivity and profitability. It then describes how data science techniques like precision agriculture using sensors and drones, soil analysis, satellite imagery, and disease/pest detection algorithms can help farmers optimize inputs, increase yields, and ensure food safety and security. Overall, the document advocates that data science has great potential to revolutionize agriculture by making it more efficient and sustainable.
A New Vision for Weather and Climate Services in Africa - Executive SummaryGreg Benchwick
The collection, analysis and distribution of reliable climate and weather information has the potential to greatly benefit efforts by African nations to reduce poverty, build resilience and adapt to a changing climate. An upcoming UNDP publication will examine the climate information and services space in sub-Saharan Africa, taking a critical look at what hasn’t worked, why it’s important and possible solutions.
This comprehensive peer-reviewed report is being prepared by the UNDP’s Programme on Climate Information for Resilient Development in Africa (CIRDA), a four-year programme supporting work in 11 African Least Developed Countries with $50 million from the Global Environment Facility’s Least Developed Countries Fund (LDCF). As such it builds on the expertise of the CIRDA technical team, the products of several workshops, and initial consultations between CIRDA experts and public and private representatives in partner countries.
The full report is due out soon. To receive the full report, email Greg Benchwick at gregory.benchwick@undp.org.
Big data approaches can help rice farmers in Latin America adapt to climate change by providing real-time climate and cropping advice. A pilot program in Colombia combined rice yield and weather data to identify climate patterns and recommend optimal planting times. Farmers who followed the advice had successful harvests, while those who did not lost their crops and inputs. The program aims to scale this approach to other major rice producers in Latin America, including Argentina, Brazil, and Uruguay. Doing so may help reduce yield losses, increase adaptive capacity, and revolutionize agricultural advisory services.
1) Smart ICT technologies like mobile phones and web portals can provide smallholder farmers in Africa with weather, water, and agricultural advisories to help improve resilience to climate change.
2) The International Water Management Institute has developed systems to provide near real-time climate, vegetation, and water information via SMS and online to help farmers, irrigation boards, and others make better management decisions.
3) The concept involves monitoring crop conditions in registered farmer fields using high-resolution satellite data and sending simple regular advisories on water and inputs via SMS to optimize farm profits.
The information and communication is a vital resource for agriculture and may contribute considerably to make sure food security and property by making awareness and talent development through access to information. The initial and most distinguished player of information delivery is public sector extension services that from past few years are sometimes criticized for their ineffective targeting, poor reach and also the vast body value of delivering information. Since past few years, the forceful increase in mobile penetration even in rural areas has result in evolution of ICT-based extension services models to publicize agriculture connected information. The goal of discrimination the mobile phone-enabled info delivery mechanism is to possess inclusive growth by reducing the information gap between enormous and little farmers and by making awareness. With this end, this paper analysis specific objectives excluding distinguishing potential desires of data and also the existing sources, includes the meta analysis of mobile impact studies chiefly in India in terms of up farmers socio-economic conditions by being higher connected to extension services, improved access to markets and higher science info.
KPI Deployment for Enhanced Rice Production in a Geo-Location Environment us...ijwmn
Rice production plays a significant role in food security in the globe. The automation of rice production remains the paradigm shift to meet up with the consumer demand considering the tremendous increase in consumption rate. The paper aimed at implementing some selected key performance indicators (KPIs) for enhanced rice production by addressing five major challenges that face rice farmers, especially in Nigeria. The Non-availability of water/rain for year-round cultivation, disproportionate application of fertilizer, weed control/prevention, pest/disease control, and rodents and bird’s invasion are outlined as observed constraints. A Zigbee-based Enhanced Wireless Sensor Network (eWSN) was used to model various network scenarios to demonstrate data sensing of different environmental variables in a given farm land. This was achieved by varying network devices at different scenarios using OPNET simulator and understudying the network performances. Each new set of network devices was integrated to a Zigbee Coordinator (ZC) which assigns an address to its members and forms a personal area network (PAN), thus representing data sensing of a particular environmental variable. Three different scenarios were designed and simulated in the study. Each of the temperature and humidity, motion and soil nutrient sensors generated about 29bps of traffic. At the Coordinators, steady stream of traffic was received. The temperature and humidity Coordinators, received a traffic of 64bps each, while the soil nutrient Coordinator received data traffic of 96bps. The outcome of the design demonstrates effective communication between different network components and provides insight on how WSN could be used simultaneously to monitor a number of different environmental variables on a farm field. By implementing the KPIs, the simulation result provided an estimated yield increase from 2.2 to 8.7 metric ton per hectare of a rice farm.
KPI DEPLOYMENT FOR ENHANCED RICE PRODUCTION IN A GEO-LOCATION ENVIRONMENT USI...ijwmn
Rice production plays a significant role in food security in the globe. The automation of rice production
remains the paradigm shift to meet up with the consumer demand considering the tremendous increase in
consumption rate. The paper aimed at implementing some selected key performance indicators (KPIs) for
enhanced rice production by addressing five major challenges that face rice farmers, especially in Nigeria.
The Non-availability of water/rain for year-round cultivation, disproportionate application of fertilizer,
weed control/prevention, pest/disease control, and rodents and bird’s invasion are outlined as observed
constraints. A Zigbee-based Enhanced Wireless Sensor Network (eWSN) was used to model various
network scenarios to demonstrate data sensing of different environmental variables in a given farm land.
This was achieved by varying network devices at different scenarios using OPNET simulator and
understudying the network performances. Each new set of network devices was integrated to a Zigbee
Coordinator (ZC) which assigns an address to its members and forms a personal area network (PAN), thus
representing data sensing of a particular environmental variable. Three different scenarios were designed
and simulated in the study. Each of the temperature and humidity, motion and soil nutrient sensors
generated about 29bps of traffic. At the Coordinators, steady stream of traffic was received. The
temperature and humidity Coordinators, received a traffic of 64bps each, while the soil nutrient
Coordinator received data traffic of 96bps. The outcome of the design demonstrates effective
communication between different network components and provides insight on how WSN could be used
simultaneously to monitor a number of different environmental variables on a farm field. By implementing
the KPIs, the simulation result provided an estimated yield increase from 2.2 to 8.7 metric ton per hectare
of a rice farm.
IoT-oriented software platform applied to sensors-based farming facility with...journalBEEI
This work describes the design of innovative IoT-oriented farm management system that employs low-cost WSN for detecting soil, environmental and crops parameters that properly processed, in combination with weather forecasts, are used to determine future farming activities based on agronomic models implemented in the software platform. Goals of carried out research activity are to guarantee production both qualitatively and quantitatively of cultivated crops, to increase company income and reduce environmental impacts; achieving these objectives is a prerequisite for implementing of sustainable agriculture. Connection between traditional cropping systems and innovative technologies is achieved through the utilization of low-cost wireless electronic modules for acquiring data from connected sensors. The fertigation system operation is supported by solar-powered low-cost WSN capable of constantly monitoring soil and environmental parameters; thanks to sensor nodes properly positioned in cultivated land or greenhouse, interest parameters of both air and soil are detected and transmitted to on-cloud database, to allow monitoring and remote control from enabled users (farmer or agronomist). For this aim, an application specifically realized and tested during the different fertigation system’s functional tests, allows users to visualize and eventually remotely intervene by using a smart-phone or tablet.
This document discusses emerging opportunities to deliver relevant weather and climate information and services to smallholder farmers at scale. It outlines the need for spatially and temporally detailed historical, monitored, predicted, and projected climate data. Participatory approaches like PICSA can help communicate this information and support farmers' decision making. Effective partnerships are needed between meteorological agencies, researchers, extension services, and the private sector to generate localized climate data, train intermediaries, and ensure information reaches farmers through various communication channels. With improved access to actionable climate information and support systems, smallholder farmers' food security and livelihoods can be enhanced.
Similar to The Development of Climate Agrometeorological Application for Farmers in Namibia (20)
Home security is of paramount importance in today's world, where we rely more on technology, home
security is crucial. Using technology to make homes safer and easier to control from anywhere is
important. Home security is important for the occupant’s safety. In this paper, we came up with a low cost,
AI based model home security system. The system has a user-friendly interface, allowing users to start
model training and face detection with simple keyboard commands. Our goal is to introduce an innovative
home security system using facial recognition technology. Unlike traditional systems, this system trains
and saves images of friends and family members. The system scans this folder to recognize familiar faces
and provides real-time monitoring. If an unfamiliar face is detected, it promptly sends an email alert,
ensuring a proactive response to potential security threats.
In the era of data-driven warfare, the integration of big data and machine learning (ML) techniques has
become paramount for enhancing defence capabilities. This research report delves into the applications of
big data and ML in the defence sector, exploring their potential to revolutionize intelligence gathering,
strategic decision-making, and operational efficiency. By leveraging vast amounts of data and advanced
algorithms, these technologies offer unprecedented opportunities for threat detection, predictive analysis,
and optimized resource allocation. However, their adoption also raises critical concerns regarding data
privacy, ethical implications, and the potential for misuse. This report aims to provide a comprehensive
understanding of the current state of big data and ML in defence, while examining the challenges and
ethical considerations that must be addressed to ensure responsible and effective implementation.
Cloud Computing, being one of the most recent innovative developments of the IT world, has been
instrumental not just to the success of SMEs but, through their productivity and innovative contribution to
the economy, has even made a remarkable contribution to the economic growth of the United States. To
this end, the study focuses on how cloud computing technology has impacted economic growth through
SMEs in the United States. Relevant literature connected to the variables of interest in this study was
reviewed, and secondary data was generated and utilized in the analysis section of this paper. The findings
of this paper revealed that there have been meaningful contributions that the usage of virtualization has
made in the commercial dealings of small firms in the United States, and this has also been reflected in the
economic growth of the country. This paper further revealed that as important as cloud-based software is,
some SMEs are still skeptical about how it can help improve their business and increase their bottom line
and hence have failed to adopt it. Apart from the SMEs, some notable large firms in different industries,
including information and educational services, have adopted cloud computing technology and hence
contributed to the economic growth of the United States. Lastly, findings from our inferential statistics
revealed that no discernible change has occurred in innovation between small and big businesses in the
adoption of cloud computing. Both categories of businesses adopt cloud computing in the same way, and
their contribution to the American economy has no significant difference in the usage of virtualization.
Energy-constrained Wireless Sensor Networks (WSNs) have garnered significant research interest in
recent years. Multiple-Input Multiple-Output (MIMO), or Cooperative MIMO, represents a specialized
application of MIMO technology within WSNs. This approach operates effectively, especially in
challenging and resource-constrained environments. By facilitating collaboration among sensor nodes,
Cooperative MIMO enhances reliability, coverage, and energy efficiency in WSN deployments.
Consequently, MIMO finds application in diverse WSN scenarios, spanning environmental monitoring,
industrial automation, and healthcare applications.
The AIRCC's International Journal of Computer Science and Information Technology (IJCSIT) is devoted to fields of Computer Science and Information Systems. The IJCSIT is a open access peer-reviewed scientific journal published in electronic form as well as print form. The mission of this journal is to publish original contributions in its field in order to propagate knowledge amongst its readers and to be a reference publication. IJCSIT publishes original research papers and review papers, as well as auxiliary material such as: research papers, case studies, technical reports etc.
With growing, Car parking increases with the number of car users. With the increased use of smartphones
and their applications, users prefer mobile phone-based solutions. This paper proposes the Smart Parking
Management System (SPMS) that depends on Arduino parts, Android applications, and based on IoT. This
gave the client the ability to check available parking spaces and reserve a parking spot. IR sensors are
utilized to know if a car park space is allowed. Its area data are transmitted using the WI-FI module to the
server and are recovered by the mobile application which offers many options attractively and with no cost
to users and lets the user check reservation details. With IoT technology, the smart parking system can be
connected wirelessly to easily track available locations.
Welcome to AIRCC's International Journal of Computer Science and Information Technology (IJCSIT), your gateway to the latest advancements in the dynamic fields of Computer Science and Information Systems.
Computer-Assisted Language Learning (CALL) are computer-based tutoring systems that deal with
linguistic skills. Adding intelligence in such systems is mainly based on using Natural Language
Processing (NLP) tools to diagnose student errors, especially in language grammar. However, most such
systems do not consider the modeling of student competence in linguistic skills, especially for the Arabic
language. In this paper, we will deal with basic grammar concepts of the Arabic language taught for the
fourth grade of the elementary school in Egypt. This is through Arabic Grammar Trainer (AGTrainer)
which is an Intelligent CALL. The implemented system (AGTrainer) trains the students through different
questions that deal with the different concepts and have different difficulty levels. Constraint-based student
modeling (CBSM) technique is used as a short-term student model. CBSM is used to define in small grain
level the different grammar skills through the defined skill structures. The main contribution of this paper
is the hierarchal representation of the system's basic grammar skills as domain knowledge. That
representation is used as a mechanism for efficiently checking constraints to model the student knowledge
and diagnose the student errors and identify their cause. In addition, satisfying constraints and the number
of trails the student takes for answering each question and fuzzy logic decision system are used to
determine the student learning level for each lesson as a long-term model. The results of the evaluation
showed the system's effectiveness in learning in addition to the satisfaction of students and teachers with its
features and abilities.
In the realm of computer security, the importance of efficient and reliable user authentication methods has
become increasingly critical. This paper examines the potential of mouse movement dynamics as a
consistent metric for continuous authentication. By analysing user mouse movement patterns in two
contrasting gaming scenarios, "Team Fortress" and "Poly Bridge," we investigate the distinctive
behavioral patterns inherent in high-intensity and low-intensity UI interactions. The study extends beyond
conventional methodologies by employing a range of machine learning models. These models are carefully
selected to assess their effectiveness in capturing and interpreting the subtleties of user behavior as
reflected in their mouse movements. This multifaceted approach allows for a more nuanced and
comprehensive understanding of user interaction patterns. Our findings reveal that mouse movement
dynamics can serve as a reliable indicator for continuous user authentication. The diverse machine
learning models employed in this study demonstrate competent performance in user verification, marking
an improvement over previous methods used in this field. This research contributes to the ongoing efforts to
enhance computer security and highlights the potential of leveraging user behavior, specifically mouse
dynamics, in developing robust authentication systems.
The AIRCC's International Journal of Computer Science and Information Technology (IJCSIT) is devoted to fields of Computer Science and Information Systems. The IJCSIT is a open access peer-reviewed scientific journal published in electronic form as well as print form. The mission of this journal is to publish original contributions in its field in order to propagate knowledge amongst its readers and to be a reference publication.
Image segmentation and classification tasks in computer vision have proven to be highly effective using neural networks, specifically Convolutional Neural Networks (CNNs). These tasks have numerous
practical applications, such as in medical imaging, autonomous driving, and surveillance. CNNs are capable
of learning complex features directly from images and achieving outstanding performance across several
datasets. In this work, we have utilized three different datasets to investigate the efficacy of various preprocessing and classification techniques in accurssedately segmenting and classifying different structures
within the MRI and natural images. We have utilized both sample gradient and Canny Edge Detection
methods for pre-processing, and K-means clustering have been applied to segment the images. Image
augmentation improves the size and diversity of datasets for training the models for image classification
The AIRCC's International Journal of Computer Science and Information Technology (IJCSIT) is devoted to fields of Computer Science and Information Systems. The IJCSIT is a open access peer-reviewed scientific journal published in electronic form as well as print form. The mission of this journal is to publish original contributions in its field in order to propagate knowledge amongst its readers and to be a reference publication.
This research aims to further understanding in the field of continuous authentication using behavioural
biometrics. We are contributing a novel dataset that encompasses the gesture data of 15 users playing
Minecraft with a Samsung Tablet, each for a duration of 15 minutes. Utilizing this dataset, we employed
machine learning (ML) binary classifiers, being Random Forest (RF), K-Nearest Neighbors (KNN), and
Support Vector Classifier (SVC), to determine the authenticity of specific user actions. Our most robust
model was SVC, which achieved an average accuracy of approximately 90%, demonstrating that touch
dynamics can effectively distinguish users. However, further studies are needed to make it viable option
for authentication systems. You can access our dataset at the following
link:https://github.com/AuthenTech2023/authentech-repo
This paper discusses the capabilities and limitations of GPT-3 (0), a state-of-the-art language model, in the
context of text understanding. We begin by describing the architecture and training process of GPT-3, and
provide an overview of its impressive performance across a wide range of natural language processing
tasks, such as language translation, question-answering, and text completion. Throughout this research
project, a summarizing tool was also created to help us retrieve content from any types of document,
specifically IELTS (0) Reading Test data in this project. We also aimed to improve the accuracy of the
summarizing, as well as question-answering capabilities of GPT-3 (0) via long text
In the realm of computer security, the importance of efficient and reliable user authentication methods has
become increasingly critical. This paper examines the potential of mouse movement dynamics as a
consistent metric for continuous authentication. By analysing user mouse movement patterns in two
contrasting gaming scenarios, "Team Fortress" and "Poly Bridge," we investigate the distinctive
behavioral patterns inherent in high-intensity and low-intensity UI interactions. The study extends beyond
conventional methodologies by employing a range of machine learning models. These models are carefully
selected to assess their effectiveness in capturing and interpreting the subtleties of user behavior as
reflected in their mouse movements. This multifaceted approach allows for a more nuanced and
comprehensive understanding of user interaction patterns. Our findings reveal that mouse movement
dynamics can serve as a reliable indicator for continuous user authentication. The diverse machine
learning models employed in this study demonstrate competent performance in user verification, marking
an improvement over previous methods used in this field. This research contributes to the ongoing efforts to
enhance computer security and highlights the potential of leveraging user behavior, specifically mouse
dynamics, in developing robust authentication systems.
Image segmentation and classification tasks in computer vision have proven to be highly effective using neural networks, specifically Convolutional Neural Networks (CNNs). These tasks have numerous
practical applications, such as in medical imaging, autonomous driving, and surveillance. CNNs are capable
of learning complex features directly from images and achieving outstanding performance across several
datasets. In this work, we have utilized three different datasets to investigate the efficacy of various preprocessing and classification techniques in accurssedately segmenting and classifying different structures
within the MRI and natural images. We have utilized both sample gradient and Canny Edge Detection
methods for pre-processing, and K-means clustering have been applied to segment the images. Image
augmentation improves the size and diversity of datasets for training the models for image classification.
This work highlights transfer learning’s effectiveness in image classification using CNNs and VGG 16 that
provides insights into the selection of pre-trained models and hyper parameters for optimal performance.
We have proposed a comprehensive approach for image segmentation and classification, incorporating preprocessing techniques, the K-means algorithm for segmentation, and employing deep learning models such
as CNN and VGG 16 for classification.
- The document presents 6 different models for defining foot size in Tunisia: 2 statistical models, 2 neural network models using unsupervised learning, and 2 models combining neural networks and fuzzy logic.
- The statistical models (SM and SHM) are based on applying statistical equations to morphological foot data.
- The neural network models (MSK and MHSK) use self-organizing Kohonen maps to cluster foot data and model full and half sizes.
- The fuzzy neural network models (MSFK and MHSFK) incorporate fuzzy logic into the neural network learning process to better account for uncertainty in foot sizes.
The security of Electric Vehicle (EV) charging has gained momentum after the increase in the EV adoption
in the past few years. Mobile applications have been integrated into EV charging systems that mainly use a
cloud-based platform to host their services and data. Like many complex systems, cloud systems are
susceptible to cyberattacks if proper measures are not taken by the organization to secure them. In this
paper, we explore the security of key components in the EV charging infrastructure, including the mobile
application and its cloud service. We conducted an experiment that initiated a Man in the Middle attack
between an EV app and its cloud services. Our results showed that it is possible to launch attacks against
the connected infrastructure by taking advantage of vulnerabilities that may have substantial economic and
operational ramifications on the EV charging ecosystem. We conclude by providing mitigation suggestions
and future research directions.
The AIRCC's International Journal of Computer Science and Information Technology (IJCSIT) is devoted to fields of Computer Science and Information Systems. The IJCSIT is a open access peer-reviewed scientific journal published in electronic form as well as print form. The mission of this journal is to publish original contributions in its field in order to propagate knowledge amongst its readers and to be a reference publication.
The AIRCC's International Journal of Computer Science and Information Technology (IJCSIT) is devoted to fields of Computer Science and Information Systems. The IJCSIT is a open access peer-reviewed scientific journal published in electronic form as well as print form. The mission of this journal is to publish original contributions in its field in order to propagate knowledge amongst its readers and to be a reference publication.
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.
Design and optimization of ion propulsion dronebjmsejournal
Electric propulsion technology is widely used in many kinds of vehicles in recent years, and aircrafts are no exception. Technically, UAVs are electrically propelled but tend to produce a significant amount of noise and vibrations. Ion propulsion technology for drones is a potential solution to this problem. Ion propulsion technology is proven to be feasible in the earth’s atmosphere. The study presented in this article shows the design of EHD thrusters and power supply for ion propulsion drones along with performance optimization of high-voltage power supply for endurance in earth’s atmosphere.
Introduction- e - waste – definition - sources of e-waste– hazardous substances in e-waste - effects of e-waste on environment and human health- need for e-waste management– e-waste handling rules - waste minimization techniques for managing e-waste – recycling of e-waste - disposal treatment methods of e- waste – mechanism of extraction of precious metal from leaching solution-global Scenario of E-waste – E-waste in India- case studies.
Null Bangalore | Pentesters Approach to AWS IAMDivyanshu
#Abstract:
- Learn more about the real-world methods for auditing AWS IAM (Identity and Access Management) as a pentester. So let us proceed with a brief discussion of IAM as well as some typical misconfigurations and their potential exploits in order to reinforce the understanding of IAM security best practices.
- Gain actionable insights into AWS IAM policies and roles, using hands on approach.
#Prerequisites:
- Basic understanding of AWS services and architecture
- Familiarity with cloud security concepts
- Experience using the AWS Management Console or AWS CLI.
- For hands on lab create account on [killercoda.com](https://killercoda.com/cloudsecurity-scenario/)
# Scenario Covered:
- Basics of IAM in AWS
- Implementing IAM Policies with Least Privilege to Manage S3 Bucket
- Objective: Create an S3 bucket with least privilege IAM policy and validate access.
- Steps:
- Create S3 bucket.
- Attach least privilege policy to IAM user.
- Validate access.
- Exploiting IAM PassRole Misconfiguration
-Allows a user to pass a specific IAM role to an AWS service (ec2), typically used for service access delegation. Then exploit PassRole Misconfiguration granting unauthorized access to sensitive resources.
- Objective: Demonstrate how a PassRole misconfiguration can grant unauthorized access.
- Steps:
- Allow user to pass IAM role to EC2.
- Exploit misconfiguration for unauthorized access.
- Access sensitive resources.
- Exploiting IAM AssumeRole Misconfiguration with Overly Permissive Role
- An overly permissive IAM role configuration can lead to privilege escalation by creating a role with administrative privileges and allow a user to assume this role.
- Objective: Show how overly permissive IAM roles can lead to privilege escalation.
- Steps:
- Create role with administrative privileges.
- Allow user to assume the role.
- Perform administrative actions.
- Differentiation between PassRole vs AssumeRole
Try at [killercoda.com](https://killercoda.com/cloudsecurity-scenario/)
Prediction of Electrical Energy Efficiency Using Information on Consumer's Ac...PriyankaKilaniya
Energy efficiency has been important since the latter part of the last century. The main object of this survey is to determine the energy efficiency knowledge among consumers. Two separate districts in Bangladesh are selected to conduct the survey on households and showrooms about the energy and seller also. The survey uses the data to find some regression equations from which it is easy to predict energy efficiency knowledge. The data is analyzed and calculated based on five important criteria. The initial target was to find some factors that help predict a person's energy efficiency knowledge. From the survey, it is found that the energy efficiency awareness among the people of our country is very low. Relationships between household energy use behaviors are estimated using a unique dataset of about 40 households and 20 showrooms in Bangladesh's Chapainawabganj and Bagerhat districts. Knowledge of energy consumption and energy efficiency technology options is found to be associated with household use of energy conservation practices. Household characteristics also influence household energy use behavior. Younger household cohorts are more likely to adopt energy-efficient technologies and energy conservation practices and place primary importance on energy saving for environmental reasons. Education also influences attitudes toward energy conservation in Bangladesh. Low-education households indicate they primarily save electricity for the environment while high-education households indicate they are motivated by environmental concerns.
AI for Legal Research with applications, toolsmahaffeycheryld
AI applications in legal research include rapid document analysis, case law review, and statute interpretation. AI-powered tools can sift through vast legal databases to find relevant precedents and citations, enhancing research accuracy and speed. They assist in legal writing by drafting and proofreading documents. Predictive analytics help foresee case outcomes based on historical data, aiding in strategic decision-making. AI also automates routine tasks like contract review and due diligence, freeing up lawyers to focus on complex legal issues. These applications make legal research more efficient, cost-effective, and accessible.
Digital Twins Computer Networking Paper Presentation.pptxaryanpankaj78
A Digital Twin in computer networking is a virtual representation of a physical network, used to simulate, analyze, and optimize network performance and reliability. It leverages real-time data to enhance network management, predict issues, and improve decision-making processes.
VARIABLE FREQUENCY DRIVE. VFDs are widely used in industrial applications for...PIMR BHOPAL
Variable frequency drive .A Variable Frequency Drive (VFD) is an electronic device used to control the speed and torque of an electric motor by varying the frequency and voltage of its power supply. VFDs are widely used in industrial applications for motor control, providing significant energy savings and precise motor operation.
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.
Advanced control scheme of doubly fed induction generator for wind turbine us...
The Development of Climate Agrometeorological Application for Farmers in Namibia
1. International Journal of Computer Science & Information Technology (IJCSIT) Vol 15, No 2, April 2023
DOI:10.5121/ijcsit.2023.15204 39
THE DEVELOPMENT OF CLIMATE
AGROMETEOROLOGICAL APPLICATION FOR
FARMERS IN NAMIBIA
Valerianus Hashiyana, Nalina Suresh and Abel Natangwe Mwedihanga
Department of Computing, Mathematical and Statistical Sciences, University ofNamibia,
Windhoek, Namibia
ABSTRACT
Climate services involve the timely production, translation, and delivery of useful climate data, information
and knowledge for societal decision making. In order to create climate services for farmers that are truly
integrated with user-centric design into the development process in an African context, the study has
finished an important and crucial step by conducting a literature review and designing a prototype for the
application. The goal of this study was to create climate services for farmers in an African context that are
genuinely integrated with user-centric design. This led to the co-design and development and integration
of a mobile application that provide climate and weather information as well as agricultural
information for the main crops such millet, maize and sorghum. The research applied using qualitative
research using interview with 3 farmers in the field using random sampling with the approach to inform
the study. A survey has been administered to find out how people understand climate services, Agro
meteorology and help enhance the mobile application’s user experience. A Results shows that farmers are
determined and ready to use and excited with the application. These innovations helped farmers to reduce
the cost, increase crop capacity and profit. A hypothesis was set that there is a need forintegrating AI into
a farmer’s application for making farming process more progressive and efficient farming and the
integration of Market Place (MP) for farmer’s application to market and sell their product the integration
of notification system that allows farmers to receive real-time data and IOT for real-time data. The data
collected and the survey results demonstrated that the research objectives were being met. The study aims
to develop the application that would be scalable, durable and fault tolerant for farmers to use the
application successfully.
KEYWORDS
Climate services for farmers, Co-design, Mobile application, Artificial Intelligence, Internet of Things
1. INTRODUCTION
Agriculture is one of the fastest growth in the economics and it is not an exception for Namibia.
Since it contributes to provision of capital, provision of labour, provision of wage goods these all
factors increase the growth of agriculture in the economy of a certain country. Agriculture
provides the benefit of food security, supply of food as well as fodder, source of raw material.
The fact that there’s lack of information transfer in between farmers can lead to great impact on
farmers in rural areas and commercial. Information on agriculture, markets, and weather is
essential for increasing agricultural output, especially to reduce the risk and uncertainty
associated with disease and extreme weather events [1].
There implementation of a software tool aid farmers with preparedness of avoiding the risk of
crop failure using the agricultural information, to measure the farmers crop temperature, to
measure the humidity of the crops of the farmers, to measure the rainfall of the particular area of
2. International Journal of Computer Science & Information Technology (IJCSIT) Vol 15, No 2, April 2023
40
the farmers. Climate services involve the timely production, translation, delivery of useful
climate data, information and knowledge for societal decision making. Those services are
depending on several expertise and support by research in climate and related sciences in
agriculture, water resources, health, energy and a number of social science fields. In Agriculture,
farmers need accessible and usable climate services to manage climate risks in the constantly
changing environment. For the benefit of the agricultural sector and farmers, the climate services
offer crop tracking, agro-meteorological advisories, weather forecasting, seasonal climate
forecasting, climate change projections, statistical assessments of the frequency of extreme
weather and climate events in the future, and weather forecasting. Farmers looking for real-time
data and strive to ensure enough agricultural inputs to meet the requirements of the crop while
taking advantage of the data already present on the farm. Weather data including precipitation,
relative humidity, wind speeds, temperatures, and solar radiation will be gathered because these
variables have an influence on irrigation. This data can collect from the existing regional
Authorities e.g. National Meteorological Authority Centre as well as the weather station
neighbouring farms.
The proposed approach used different issues to improve the involvement of users during different
technical forums and meeting within a small group and evaluative sessions of the mobile
application. The outcome of the research indicated that clients and developers benefited the
interaction of the product as it met the clients need. Throughout the development of the
application the software had reduced number of errors in the final version of the application.
According to [2] stated that, in developing countries the rural areas’ farmers face challenge
competing in the global marketplace and global forces beyond their control due to lack of access
to information and communications to make decisions and reach new markets. Due to low
literacy and low access to required information, there is no sharing knowledge and experience
end-to-end between producers and consumers. Market information such as coordinating the
sale, movement, and distributions of products, is essential for decision making. Lacking irrigation
or dependence on unpredictability of changing global weather is resulting many farmers'
population migration from rural to urban centers for a more stable livelihood, losing their land
and their culture and selling out their farm land to builders.
2. OBJECTIVES
To develop an Agro-meteorological application that will combine real-time weather information
according to the profiles of small-scale farmers in Namibia and integrating a Mobile Application
to send notification to the Farmers.
3. RELATED WORK
According to [3] Weather and climate play an important role in agricultural production. It has a
profound influence on crop growth, development and yields; on the incidence of pests and
diseases; on water needs; and on fertilizer requirements. Accurate understanding of extreme
meteorological parameters is crucial for farmers to generate more. This information is also useful
for modifying the crop environment, taking precautions against frost and powerful winds, and
planning irrigation, all of which help to effectively control water usage and prepare for droughts.
In addition, droughts and floods are two examples of extreme weather that can ruin crops and
lower output. The emphasis on introducing a digital system is on the proper well documented
feasibility study and the quality and integrity of data and involvement of stakeholders which are
farmers, that allows the software to meet its needs [3].
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According to the author [4], A means of getting new technologies, better farming methods, and
better management knowledge to farmers is through agricultural extension. There aren't enough
extension agents, and there isn't enough time, especially in emergencies like weather- or pest-
related ones. As a consequence, radio has gained recognition as a very efficient technology for
distributing knowledge, instruction, and technology in rural areas. The poorer segments of the
population can now afford low-cost transistor radios that run on batteries, while other
communication tools like television stay in the hands of a small minority. Furthermore, there is
no literacy requirement for using radio as a contact medium. Additionally, barriers are being
removed by the growing shift to local radio program creation and broadcasting. Language and
dialect boundaries are also disappearing as local radio programming becomes more prevalent.
Due to the local population's typically high vulnerability, there are negative effects on food and
water security when drought directly affects agriculture and water resources over such large
spatial and temporal scales [4].
As aforementioned, Downy Mildew (Plasmopara Viticola), which can develop and spreadrapidly
and result in significant crop losses in some years depending on the weather, is one ofthe most
significant vineyard diseases in the Western Cape. In an effort to define the weather
circumstances favoring the disease outbreak, researchers from the Agricultural Research Council
(ARC) collaborated with growers. Over a number of years, they kept an eye on the weather on
the fields as well as any downy mildew outbreaks in the vineyards. The producers must choose
which agrochemicals to use, how often to apply them, and whether or not to spray. They need to
avoid crop failure due to infection while balancing the number of applications in accordance with
economics, minimizing the impacts of pollution. Donsige Skimmel Vroeg- Waarskuwingsmodel
(DSVW), which stands for "Downy Mildew Early Warning Model" in Afrikaans, was developed
as a result [5]. It offers a user-friendly graphical output of past weather variables (up to three
weeks), as well as a three-color indication of a high, medium, and low chance of potential
favorable periods for the occurrence of both primary and secondary infections. The model must
be run with the daily hourly weather data that is downloaded via telephone modem from the
automatic weather stations as input. The model's result is then sentto the growers via email or
fax. [5].
According to [6], Although there are many advantages to using satellite remote sensing to
supplement low density in situ observations, there are a number of issues that must be resolved
before they can fully contribute to drought tracking. These typically include changes to satellite
sensors that can cause temporal inhomogeneities, the relatively brief record lengths of satellite
products, and the indirect nature of the retrievals of physical variables. They should be used
with care, in particular, due to errors in individual products, inconsistencies between products,
and nonclosure of the water budget. Droughts cause less than 20% of all natural disasters in Sub-
Saharan Africa (SSA), but they affect more than 80% of the region's people (UN/ISDR 2009).
Because a large portion of the region relies on rain-fed agriculture, it is especially vulnerable to
climate change. On average, agriculture accounts for 25% of the continent's gross domestic
product (GDP) and employs close to 70% of the labor population [6].
There is no proof that historical climatic data given through any agricultural project for
meteorological purposes is integrated into the agricultural sector in Sub-Saharan African
countries. It demonstrates that many MNOs that run agro-meteorological services are
unimpressed with the various services provided to farmers and the insufficient weather services
given to farmers. Instead, India has created a sophisticated system for sending farmers agro
meteorological warnings, some of which are done so via mobile devices. RegionalMeteorological
Centers transmit weather information to 130 AMFUs which are located in each of the Agro-
climatic zones. They then create Agro-advisory information in collaboration with agricultural
specialists, which incorporates weather data with crop and soil recommendations and offers
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recommendations for reducing losses and maximizing inputs [7].
Summer cyclones frequently have a windy component. Rainwater splashing causes infections and
worsens disease when wolfberry stems are in motion and scratch fruits and other plant parts. In
a year with a high incidence of disease, the proportion of diseased fruits results in a 50% loss in
output, with a sharp decline in market price because of the poorer fruit quality. Meteorological
conditions play a key role in the occurrence and development of this fungus disease. The fungus
disease of the wolfberry will spread rapidly if the rainfall is around 40 mm for that same time
criterion. 50 to 80 percent of crops will now be impacted or turn black.
Comprehensive preventative and control methods were discovered, and forecasting and alert
models were developed. To determine the signs of the fungus disease in its early stages, the
severity of the epidemic disease is divided into five categories based on the field epidemic state.
[8].
This agricultural method improves water infiltration while lowering soil moisture evaporation
and water runoff in these (semi-)arid regions, which receive the majority of their rain in the late
summer and fall. Using the information in [9] [10], we have briefly described and discussed the
example of watermelons grown in a better microclimate made by covering sandy soil with eight
to ten cm of pebbles dug up from river beds, explaining the wind erosion protection, the soil
surface evaporation prevention, and the warming of the seed bed so created. It has been observed
that, especially at night, the soil surface temperatures at the bottom of such covered cavities can
be up to five degrees warmer than those at the pebble surface. Due to the length of the growing
season and the significance of early sowing, this can be a crucial frost protection problem for the
method. In the early stages, plastic can help shield seeds and seedlings from frost, but not all
farmers use it because of location issues. Further details are also in [11]. With the approval of the
China Meteorological Administration, Beijing, a Provincial Government Meteorological Service
provided the policy support for this capacity development in microclimate improvement. [12].
Compax has years of experience applying integrated Control and SCADA/DCS systems, and it
provides a mature range of products and services. With projects in Israel, South America, Europe,
and the Caspian area, it specializes in Water and Waste Water, Oil and Gas, andProcess
applications. Their expertise lies in integrating cutting-edge software tools, data acquisition,
process management, and advanced communications (data voice and video over wireless cellular
satellite fiber, etc.) into a synchronized operation that maximizes productivity and profit for their
clients. The range of capabilities includes everything from providing full turn-key systems to
providing expert guidance on integrating complicated industrial computerized systems. Here are
some examples of some of its completed projects: SCADA technology for monitoring and
controlling Bogota's urban water distribution, sewage collection, and wastewater treatment is
provided by the EAAB Bogota Municipality. The water departmentof the city of TEL AVIV uses
the SUPERVISOR CONTROL PACKAGE (SCP) to command and control the city's water
supply. Monitoring system for the Kishon River maintained by the Kishon River Authority. The
Barcelona Flood Water Management System is mainly impactedby rain in Spain. Technology
includes: Customer-developed designs and construction of municipal command and control
centers; feasibility studies and system analyses. Management of Risk and Water Safety
Implementation for Wastewater Treatment Plant Management and Potable Water Plant
Management vast city complexes Create and design networks Cost- and energy-saving measures
Contemporary Technology (Industrial equip IT Communication) intelligent use of water
resources [13].
According to [14], when utilizing info on the local climate There are two options available to
agrometeorologists when presenting historical observational data: they can either show the
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derivatives or by-products of these historical data. They leave it up to farmers to evaluate and
interpret the data if they opt to only show the raw data. Sadly, the majority of smallholder farmers
lack the skills and equipment required to evaluate raw data. Therefore, this choice is not
significantly different from blocking access to agro-meteorological information. If the
agrometeorologists choose the latter option, they will need to stress the inherent uncertainty in
statistical derivatives of historical data in order to retain their credibility. Seasonal outlook
prediction literature provides some insight into this problem.
4. METHODOLOGY
A researcher can easily implement the best design for the research because the study used a
quantitative research design. The aim is to collect, analyze, find pattern and averages, make
prediction, and test the relationship on how it can be successful to implement the
Agrometeorological application for farmers in Namibia.
4.1. Research Design
The study employed a quantitative methodology, and a review of prior research materials, journal
articles, conference papers, articles, blogs, books, webpages, and academic tools was conducted.
Research was done regarding on which particular software package that will be suitable for Agro
meteorological application building to meet the requirement of researchproject objectives. The
study is further divided into stages that were followed to complete the project. Here are the stages
that were followed.
4.2. Data Analysis
The study focused on two types of data analysis which are predictive analysis and descriptive
analysis. The study analyzed the data by predicting the weather forecasting in 3 days, the study
made a prediction of informing the farmers the right time to sow, harvest, planting by predicting
the particular weather. In addition, the study developed a system that send this information to the
farmers through their mobile devices. Further, the study used qualitative data analysis by
developing the system by coding using the Microsoft Visual Studio C# with the use of
descriptive data analysis by collecting huge amount of data that need to be summarized and
interpreted. The questionnaire used random stratified sampling, a population of 8 participant’s
part taken 4 students from University of Namibia (UNAM) and 4 farmers from Naumbabale
Village in Ohangwena region, further the survey question can be found on the appendix, the
survey provided the following results. The result made the study to be researched on, 87.50%
understand the terminology of the term Agro-meteorology, where 12.50% participants do not
understand the terminology. 87.50% participants concluded that they have not used the
application in their farm before and 12.50% concluded that they have used the application before
in their farm. 87.50% participants concluded using an Agro-meteorological application may
require training and 12.50% stated is less accessible in their environment. All participants agreed
on this question shows 100% people agreed there’s a need to develop an Agrometeorological
application for farmers. Participants on this question 50% of them stated meteorology to farmers
is significant for real-time and forecast weather information, and 25% ofeach agreed on the other
two answers. All participants answer this question by stating their own views on how they see the
effectiveness and the need to develop an application for farmers.
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4.3. Software Developmental Methodology
The study focused on deciding which development life cycle is suitable to implement the
Agrometeorological application with mobile notification system integrated in the software since
the nature of the study used different data collection methods to complete the development of the
software as in Figure 1. Using incremental prototyping in a managed project setting, the Dynamic
System Development Method (DSDM) is an agile software development method that offers a
framework for creating and maintaining systems that adhere to strict time constraints. [15]. He
further stated that the modified Pareto principle served as the inspiration for the DSDMideology.
Only enough work is needed for each increment to enable to the next increment environment, so
an application can be delivered in 80% of the time it would take to deliver the full 100%
application. The main practices in DSDM involve feasibility study, requirement gathering,
planning, designing, and testing. In addition, it allows for improvement of the prototype each
time it goes through iteration.
Figure 1. Dynamic System Development Method (DSDM)
4.3.1. Hardware and Software requirements
The overall conceptual System Architecture is shown in Figure 2. The software tools needed to
build a desktop application integrated with mobile application are listed below. Firstly, one needs
to install Microsoft Visual Studio and SQL Server 2014 Management Studio. In this case, the
developers used Microsoft Visual Studio 2015 C#, the developer used Twilio Network Service
Provider for farmers to receive notification from the system. Additionally, all of the accounts that
were registered during the application's signup period were stored in the SQL database, which
served as the main backend database. Figma, UXpin, WireframePro, Canva used for graphical
user interface design. To create a desktop application and a mobile application, the following
hardware was set up: a laptop with standard configurations and 4 mobile IOS and Android
smartphones, one of which was used to evaluate the application and the other to serve as a target
user device.
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Figure 2. Conceptual System Architecture
4.3.2. Testing and Evaluation
The program underwent testing to see if user needs are satisfied and if it performs as intended. To
make sure the program operates flawlessly as elicited from the requirement specification gathered
from the small-scale farmers, four different types of testing were finished. Unit testing,combined
testing, system testing, and acceptance testing are the four testing phases. Figure 3 -9 shows the
screenshots for the running system.
The sign-up screen in Figure 3 is the first point of interaction between the system and the user
and the log in screen. In order to access the home page or the dashboard, you must check in with
your user login and sign-up credentials, such as your username and password. A user can
navigate the system by selecting the elements in Figure 4 that are depicted in the form. The user
selects part of the system to enter the system has four features which are Weather Center for
providing real time data, Information Center for providing user agricultural information,
Notification Center to allow the user to receive their notification through their mobile phones.
Figure 5 allows the user to enter their village/town to receive their weather information and
forecast weather information in real time. Figure 6 allows the user to receive their information
regarding the guideline on how to farm their crops and read information online about agricultural
worldwide standard for trading services. Figure 7 allows the administrator to send notification to
the farmer through their mobile devices about real time data of weather and agriculture. Figure 8
tells the user that they received their notification through their mobile devices. Figure 9 allows
the user to query their information regarding about Agro-meteorology and receive their answer at
the same time.
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Figure 3. Sign-up Page
Figure 4. Dashboard
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Figure 5. Weather Center
Figure 6. Information Center
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Figure 7. Notification System
Figure 8. Mobile Phone Receiving Notification
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Figure 9. ChatBot
4.3.3. Survey Result
Figure 10. Farmers Participating with the Developed Application
In Figure 10, shows that Farmers real time data provided is accurate and 100% of the participant
are happy with provision of real time data, 97% of the participant indicated that their agricultural
information were provided, 96% indicated that there were able to query information from the
system furthermore 97% indicated that that data are saved in the database their able to log in into
the system.
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5. CONCLUSION
In conclusion, more of Agro-meteorology application need to be implemented in Namibia that
describe different topics in Agro-meteorology. Different farming system needs to be improved
to achieve a quality crop growth any wrong doing during sowing, planting and harvesting will
leads to crop failure, poisoned crops attacked from fungal disease and pest, wrong cropping
pattern, which leads to high cost of living and deteriorate the livelihoods of the farmers. Using
API (Application Programming Interface), AI, Twilio integration in the application made it easier
for farmers to receive, communicate and sell their product which helps to enhance the livelihood
of the farmers and upgraded their farming techniques. Integration of Twilio system in the
application helps the bulk system notification in the future. There were no enough fund to
implement the weather station design which made the project to scale down and no enough
funds to implement the bulk notification to enable all farmers to receive notification messages
which made only 10 user to be registered to receive notification message. The lack of IOT
devices to integrate them in the system to detect weather and climate which made the project to
scale down due to lack of funds.
6. RECOMMENDATION
Agrometeorology is broad topic with a growing interest in research fields, because it has variety
of fields such as. Hydrology, soil, pest outbreak planning, drought management, crop growth
simulation modelling. This project mainly focused on creating an Agro-meteorology application
for farmers in Namibia integrated with mobile notification system where user can receive their
real time data of weather and climatic information and sell their product on the system. The
project can further extend on features such as the detection of fungal disease on particular plants
and present their fungicides, implementation of a weather station for an Agro-meteorology
application, integration of IOT physical devices into the application, implementation of crop
zonation and crop planning. Different software modules currently being build that will shape the
success extending of features to the project in future are GRASS(Geographic Analysis
Supporting System), OSSIM(Open Source Software Image Map), Map Server. This module will
help developers to create application by using the recommendation stated above or may lead to
new interesting discoveries.
REFERENCES
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[2] Anjum, R. (2015). Design of mobile phone services to support farmers in developing countries.
[3] Chattopadhyay, N., Ghosh, K., & Chandras, S. V. (2016). Agrometeorological advisory to assist the
farmers in meeting the challenges of extreme weather events. Mausam, 67(1), 277-288.
[4] Nyareza, S., & Dick, A. L. (2012, September). Use of community radio to communicate agricultural
information to Zimbabwe's peasant farmers. In Aslib Proceedings. Emerald Group Publishing
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AUTHORS
Valerianus Hashiyana is a Senior Lecturer at Department of Computing, Mathematical
& Statistical Sciences under Faculty of Agriculture, Engineering and Natural Sciences,
University of Namibia. His areas of Research are Cybersecurity, Networking &
Security, IOT, E-Health and Next generation Computing. Tel: +264 812830277, Email:
vhashiyana@unam.na / vhashiyana@gmail.com.
Nalina Suresh is currently a Senior Lecturer in the Department of Computing,
Mathematical & Statistical Sciences under Faculty of Agriculture, Engineering and Natural
Sciences, University of Namibia. Her area of research are Networking and Security,
Computational Theory and modelling, IoT, AI, Robotics, ML, DSP, Educational
technologies and Emerging Technologies. Tel: +264812229533, nsuresh@unam.com;
nalina.kss@gmail.com.
Mwedihanga Abel NN graduated with his bachelors of science in computer science
honours his research work was based on the development of climate agrometeorological
application for farmers in Namibia at University of Namibia. Technology is altering the
way how farmers live their lives and opening many challenges as their heritages and their
traditions as their representation to the digital world.