I was honored to be able to give a short presentation in Markus Sunela's dissertation party about artificial intelligence in water sector. Such an interesting topic that we yet know so little. How would you utilize an AI in water sector?
Seven Most tenable applications of AI o Water Resources ManagementMrinmoy Majumder
AI or Artificial Intelligence is a pioneering technique that has enabled the creation of intelligent machines.or smart machines which has the power to self adapt based on the situation presented to it. It requires situations whose response is known and based on this training data set it learns the problems which it has to solve when it is ready. Due to the alarming success with AI in robotics, electronics etc fields the same technique is now used to solve the problems of water resource management.. This ppt shows seven most notable use of AI in water resources-based problems where satisfactory improvement has encouraged further application of the technique.
This document provides an overview of a tutorial on using AI for data-driven decisions in water management. The tutorial was presented at the AAAI conference in 2017. It discusses the importance of water resources and the potential for AI to help manage water. The tutorial aimed to make researchers aware of opportunities in this area and demonstrate how AI can be used with open water data to help decision makers like farmers, tourists, and policymakers. It provides examples of water management initiatives from different parts of the world and potential use cases for analytics. The document also includes an outline of the tutorial presentations on topics like motivating examples, water basics, and potential solutions using data and AI techniques.
Groundwater models are simplified representation of large and real hydrogeologic systems like river basins or watersheds. GWM is attempted to analyse the mechanisms which control the occurrence and movement of groundwater and to evaluate the policies, actions and designs which may affect the systems. These models are less complex prototypes of complex hydrogeologic systems developed using spatially varying aquifer parameters, hydrologic properties, geologic boundary conditions and positions of withdrawal wells or recharging structures. These are designed to compute how pumping or recharge might affect the local or regional groundwater levels.
Motivated Machine Learning for Water Resource Managementbutest
The document discusses challenges in water resource management and the potential for embodied intelligence and motivated machine learning to help address these challenges. It proposes using a goal creation system in embodied intelligence to motivate a machine to learn how to efficiently interact with its environment. This approach could help integrate modeling and decision making to support sustainable water policies that consider various social, economic and environmental factors. The document outlines some key challenges in water management and argues that embodied intelligence trained with a goal creation mechanism may help overcome limitations of traditional machine learning models to better adapt to changing real-world environments.
Soil health analysis for crop suggestions using machine learningEditorIJAERD
Indian economy is depending on agriculture. Agriculture is the main source of income for most of the
population. So farmers are always curious about yield prediction. Many factors are responsible like soil, weather, rain,
fertilizers and pesticides to increase yield production. Agriculture being a soil-based industry, an increase in yield can
only be attained by ensuring that the soil provides a balanced and an adequate supply of nutrients. Soil testing is pivotal
in understanding the deficiencies in soil and avoiding nutrient imbalance. This survey and study focuses on the different
soil types, crop types and soil test reports. Soils are complex mixtures of air, water, minerals, organic matter, and
countless organisms that are the decaying remains of once-living things. We can say soil is an important ingredient of
agriculture. There are several types of soils and each type of soil can have different kinds of features and different kinds
of crops grow on different types of soils. We must know which type of crop is go better in our soil. We can apply machine
learning techniques to classify soil and to predict the crop suitable.
The document provides an outline for a presentation on the SWAT (Soil and Water Assessment Tool) hydrological model. It begins with an introduction to hydrological modeling and the development and utilities of the SWAT model. It describes the data requirements, model framework, and step-by-step procedure to run the model. A case study applying the SWAT model to the Simly Dam watershed in Pakistan is summarized. The limitations and future developments of the SWAT model are briefly discussed, followed by references.
Iirs overview -Remote sensing and GIS application in Water Resources ManagementTushar Dholakia
Remote sensing and GIS application in Water Resources Management- By S.P. Aggarval spa@iirs.gov.in Indian Institute of Remote sensing ISRO, Department of space, Dehradun
Seven Most tenable applications of AI o Water Resources ManagementMrinmoy Majumder
AI or Artificial Intelligence is a pioneering technique that has enabled the creation of intelligent machines.or smart machines which has the power to self adapt based on the situation presented to it. It requires situations whose response is known and based on this training data set it learns the problems which it has to solve when it is ready. Due to the alarming success with AI in robotics, electronics etc fields the same technique is now used to solve the problems of water resource management.. This ppt shows seven most notable use of AI in water resources-based problems where satisfactory improvement has encouraged further application of the technique.
This document provides an overview of a tutorial on using AI for data-driven decisions in water management. The tutorial was presented at the AAAI conference in 2017. It discusses the importance of water resources and the potential for AI to help manage water. The tutorial aimed to make researchers aware of opportunities in this area and demonstrate how AI can be used with open water data to help decision makers like farmers, tourists, and policymakers. It provides examples of water management initiatives from different parts of the world and potential use cases for analytics. The document also includes an outline of the tutorial presentations on topics like motivating examples, water basics, and potential solutions using data and AI techniques.
Groundwater models are simplified representation of large and real hydrogeologic systems like river basins or watersheds. GWM is attempted to analyse the mechanisms which control the occurrence and movement of groundwater and to evaluate the policies, actions and designs which may affect the systems. These models are less complex prototypes of complex hydrogeologic systems developed using spatially varying aquifer parameters, hydrologic properties, geologic boundary conditions and positions of withdrawal wells or recharging structures. These are designed to compute how pumping or recharge might affect the local or regional groundwater levels.
Motivated Machine Learning for Water Resource Managementbutest
The document discusses challenges in water resource management and the potential for embodied intelligence and motivated machine learning to help address these challenges. It proposes using a goal creation system in embodied intelligence to motivate a machine to learn how to efficiently interact with its environment. This approach could help integrate modeling and decision making to support sustainable water policies that consider various social, economic and environmental factors. The document outlines some key challenges in water management and argues that embodied intelligence trained with a goal creation mechanism may help overcome limitations of traditional machine learning models to better adapt to changing real-world environments.
Soil health analysis for crop suggestions using machine learningEditorIJAERD
Indian economy is depending on agriculture. Agriculture is the main source of income for most of the
population. So farmers are always curious about yield prediction. Many factors are responsible like soil, weather, rain,
fertilizers and pesticides to increase yield production. Agriculture being a soil-based industry, an increase in yield can
only be attained by ensuring that the soil provides a balanced and an adequate supply of nutrients. Soil testing is pivotal
in understanding the deficiencies in soil and avoiding nutrient imbalance. This survey and study focuses on the different
soil types, crop types and soil test reports. Soils are complex mixtures of air, water, minerals, organic matter, and
countless organisms that are the decaying remains of once-living things. We can say soil is an important ingredient of
agriculture. There are several types of soils and each type of soil can have different kinds of features and different kinds
of crops grow on different types of soils. We must know which type of crop is go better in our soil. We can apply machine
learning techniques to classify soil and to predict the crop suitable.
The document provides an outline for a presentation on the SWAT (Soil and Water Assessment Tool) hydrological model. It begins with an introduction to hydrological modeling and the development and utilities of the SWAT model. It describes the data requirements, model framework, and step-by-step procedure to run the model. A case study applying the SWAT model to the Simly Dam watershed in Pakistan is summarized. The limitations and future developments of the SWAT model are briefly discussed, followed by references.
Iirs overview -Remote sensing and GIS application in Water Resources ManagementTushar Dholakia
Remote sensing and GIS application in Water Resources Management- By S.P. Aggarval spa@iirs.gov.in Indian Institute of Remote sensing ISRO, Department of space, Dehradun
This document describes using an artificial neural network (ANN) model to predict groundwater levels 30 days in the future near a public well field in Montville Township, New Jersey. The ANN model uses inputs like daily pumping rates, precipitation, and temperature. Analysis of historical data showed climatic factors influence water levels over short periods. The ANN was trained on data from 1999-2001 and accurately predicted water levels in testing and validation data, outperforming a linear regression model. A sensitivity analysis found initial water level and precipitation were the most important predictors of future water levels. The conclusions state ANNs can accurately predict water levels for areas with limited data and do not require expensive aquifer tests.
This document describes the process of conducting watershed analysis in ArcGIS. It involves creating a digital elevation model (DEM), then generating flow direction, flow accumulation, and stream network rasters from the DEM. Sinks in the DEM are identified and filled. The stream network is converted to stream links and assigned stream orders. Finally, watersheds are delineated by pouring points using the stream links raster. The overall process allows for comprehensive watershed analysis and delineation of drainage basins.
GIS Application in Water Resource Management by Engr. Ehtisham HabibEhtisham Habib
GIS (Geographic Information System): computer information system that can input, store, manipulate, analyze, and display geographically referenced (spatial) data to support decision making processes.
Here we have discussed some general GIS application in water resource management.
Sustainable Water Management Powerpoint Presentation SlidesSlideTeam
Introducing Sustainable Water Management PowerPoint Presentation Slides. This Water resource system PowerPoint slideshow can be used to explain the overview of market size, growth rate, and capital expenditure of the water industry. You can discuss the process of planning, developing, and managing the optimum use of water. The survey data for determining water quality can be easily presented by using a water cycle management PowerPoint slideshow. Demonstrate the division of the wastewater treatment market by editing our content-ready water quality monitoring PowerPoint slide deck. You can easily edit our water resources presentation to highlight the natural processes and human processes that affect water quality. Key trends that will influence the water industry in the future such as increasing regulation, failing infrastructure, greater conservation, and efficiency, etc. can also be presented with the help of our ready-to-use water management PPT visuals. It is possible to present the features that describe a suitable location for the monitoring program. It is easy to explain topics like wastewater treatment process, wastewater reuse, global wastewater reuse by sector, treated wastewater quality parameter, etc by downloading this sustainable water management PowerPoint slide deck. https://bit.ly/3tEV5qm
drought monitoring and management using remote sensingveerendra manduri
Monitoring drought and its management became easier with the help of remote sensing..several drought monitoring indices can be used to monitor drought condition. this ppt consists of information regarding droughts in relation to agriculture and their monitoring with the help of remotely sense based indices.
4 Ways Artificial Intelligence Can Help Save the PlanetTyrone Systems
As the scale and urgency of the economic and human health impacts from our deteriorating natural environment grows, we have an opportunity to look at how AI can help transform traditional sectors and systems to address climate change, deliver food and water security, build sustainable cities, and protect biodiversity and human wellbeing.
Groundwater modeling has several purposes including understanding aquifer properties, characteristics, and response. It requires collecting hydrological, physical, and boundary condition data. Common groundwater modeling software includes MODFLOW and Sutra. The modeling process involves defining the problem, collecting data, choosing a code, running simulations, verifying results match field data through calibration, and using the model to inform management decisions.
Climate change impact assessment on hydrology on river basinsAbhiram Kanigolla
The document discusses applying remote sensing and GIS techniques to assess the impacts of climate change on hydrology in river basins. It describes using the SWAT hydrological model to simulate the water balance of the Krishna River basin in India under current and future climate scenarios from regional climate models. Key steps involved gathering spatial data on terrain, land use and soils, calibrating and validating SWAT using historical weather data, and running the model for control and climate change scenarios to analyze changes in stream flows, runoff and groundwater. The results show increases in annual discharge and surface runoff in the basin in future climate scenarios.
Water Resource Management Powerpoint Presentation SlidesSlideTeam
Discuss the process of planning, developing, and managing the optimum use of water resources by using Water Resource Management PowerPoint Presentation Slides. This Water resource system PowerPoint slideshow can be used to explain the overview of market size, growth rate, and capital expenditure of the water industry. You can present the survey data for determining water quality by using the water cycle management PPT slideshow. Demonstrate the division of the wastewater treatment market by editing our content-ready water quality monitoring PowerPoint slide deck. You can easily edit our water resources presentation to highlight the natural processes and human processes that affect water quality. Showcase the leading factors that will affect the performance of the water technology market by using water quality assurance PowerPoint visuals. Key trends that will influence the water industry in the future such as increasing regulation, failing infrastructure, greater conservation, and efficiency, etc. can also be presented with the help of our ready-to-use water management PPT visuals. Discuss how you can design an effective water quality monitoring program by downloading our professionally designed water resource management PowerPoint slides. https://bit.ly/3fb5ExJ
This document presents a case study of coupling surface water and groundwater models in the Netravathi river basin located in southern India. It summarizes the data collected and methodology used. Key data included a digital elevation model, soil data, land use/land cover maps, rainfall and weather data, hydrological data including streamflow, and groundwater levels. The methodology involved using SWAT to model surface water hydrology and estimate groundwater recharge, then coupling the SWAT outputs to a MODFLOW groundwater model to allow a more complete analysis of the regional hydrological system.
Predicting crop yield and response to Nutrients from soil spectra at WCSS 201...CIAT
This document presents a study that uses soil spectroscopy to predict crop yields and response to fertilizers in sub-Saharan Africa. The study collected soil spectra and yield data from plots in Tanzania and Malawi. Statistical models like partial least squares regression and random forest were used to determine how much of the variance in yield and response could be explained by soil spectra alone and in combination with other soil, topographic, and weather data. The models were able to explain up to 65% of the variance in yield, with soil spectra and additional data like rainfall and topography each contributing. The study aims to refine yield predictions and help smallholder farmers apply optimal fertilizer levels based on cheap soil spectral analyses.
Flood risk mapping using GIS and remote sensingRohan Tuteja
This document presents a study on flood risk mapping in the Kalyan-Dombivli area of India using GIS techniques. It outlines the scope of the study, aim and objectives which are to identify low-lying areas and analyze flood risk factors. The methodology includes generating GIS data like land use/cover maps from remote sensing data and field surveys. Flood risk is assessed based on physical, demographic, and socioeconomic vulnerability indicators as well as hazard indicators like rainfall. The results found increased risk areas due to changes in land use/cover, improper drainage networks, and population growth. Recommendations include mainstreaming disaster risk reduction and using remote sensing for database management.
Application of RS and GIS in Groundwater Prospects ZonationVishwanath Awati
This document discusses using remote sensing and GIS techniques to map groundwater prospects zones. It presents a case study of applying these methods in Bata Valley, Himachal Pradesh, India. The methodology involves developing thematic maps of factors like geology, land use, and water levels. These maps are then overlaid and analyzed in GIS to identify zones of good, moderate, or poor groundwater potential. The study concludes these techniques can effectively map groundwater prospects and inform management plans.
The document discusses integrated water resources management (IWRM) in Nepal. It begins by defining IWRM and outlining its key principles. It then describes Nepal's water resources and the various ways water is used. The document also discusses the challenges facing water management in Nepal and outlines the tools and approaches used in IWRM, including water assessments, impact assessments, and performance evaluation. It analyzes Nepal's policies and institutions related to IWRM and concludes that while IWRM principles have been adopted, developing effective local institutions remains a challenge.
The following presentation was delivered by Robert Morrison, Principal Consultant at Esri Ireland, at the 2019 NICS ICT Conference in October 2019.
The presentation focuses on taking a geographic approach to machine learning to help you "see what other's can't".
Imagery and remotely sensed data is a valuable resource for many organisations who have made substantial investment obtaining the data. The field of Machine Learning is both broad and deep and is constantly evolving. Using ArcGIS and Machine Learning allows organisations to derive valuable new content.
ArcGIS is an open, interoperable platform that allows for the integration of complementary methods and techniques that empower ArcGIS users to solve complex, real-world problems in a fundamentally spatial way.
Learn how by combining powerful built-in Image analysis tools with any machine learning package users can benefit from the spatial validation, geo-enrichment and visualisation. See how this Machine Learning is being applied in real world use-cases from marine farming and crime analysis to agriculture and sustainability.
This document outlines a water security planning case study from Chhuanthar Tlangnuam village in Mizoram, India. It describes the village demographics, 6 springs that supply water, and seasonal water availability. Field visits involved mapping resources and social aspects, surveys of households, and water demand calculations. Analysis found water demand exceeds supply in summer. A water security plan was developed to address the gap.
Climate Change Impact Assessment on Hydrological Regime of Kali Gandaki BasinHI-AWARE
The presentation focuses on the findings of the impact of climate change on the hydrological regime and water balance components of the Kali Gandaki basin in Nepal. The Soil and Water Assessment Tool (SWAT) has been used to predict future projections.
This study explains the use of remote sensing data for spatially distributed hydrological modeling using the MIKE-SHE software used in Tarim River Basin CHINA
This document discusses trend analysis of time series data. It defines time series as measurements of a variable taken at regular intervals over time. Time series can show trends, seasonal variations, cyclical variations, and irregular variations. Trend analysis determines if there is a significant increasing or decreasing trend in the data over time. Linear regression and non-parametric Mann-Kendall tests are common methods used to test for trends and estimate their magnitude. The selection of an appropriate trend analysis method depends on characteristics of the water resources data such as distributions, outliers, and missing values.
DWS15 - Connected Things Forum - Industrial internet today - Vincent Champain...IDATE DigiWorld
1. Jeff Immelt, the CEO of GE, states that industrial companies must now view themselves as software and analytics companies as well due to the rise of the industrial internet.
2. The industrial internet is fueled by innovations in hardware, software, sensors, data science, cloud computing, and mobile technology that have led to massive decreases in costs and increases in capabilities.
3. GE aims to leverage these trends and its data science expertise to generate significant customer savings and business value through services enabled by connecting machines and analyzing industrial data.
Presentation of the project OpenFridge in the Workshop on Big Data and Society Data Economy, Real-Time Mining and Analytics, Mining Techniques for Online and Customer Service in Big data Era Part of the 2013 IEEE International Conference on Big Data (IEEE Big Data 2013) 6-9 October 2013, Silicon Valley, CA, USA
This document describes using an artificial neural network (ANN) model to predict groundwater levels 30 days in the future near a public well field in Montville Township, New Jersey. The ANN model uses inputs like daily pumping rates, precipitation, and temperature. Analysis of historical data showed climatic factors influence water levels over short periods. The ANN was trained on data from 1999-2001 and accurately predicted water levels in testing and validation data, outperforming a linear regression model. A sensitivity analysis found initial water level and precipitation were the most important predictors of future water levels. The conclusions state ANNs can accurately predict water levels for areas with limited data and do not require expensive aquifer tests.
This document describes the process of conducting watershed analysis in ArcGIS. It involves creating a digital elevation model (DEM), then generating flow direction, flow accumulation, and stream network rasters from the DEM. Sinks in the DEM are identified and filled. The stream network is converted to stream links and assigned stream orders. Finally, watersheds are delineated by pouring points using the stream links raster. The overall process allows for comprehensive watershed analysis and delineation of drainage basins.
GIS Application in Water Resource Management by Engr. Ehtisham HabibEhtisham Habib
GIS (Geographic Information System): computer information system that can input, store, manipulate, analyze, and display geographically referenced (spatial) data to support decision making processes.
Here we have discussed some general GIS application in water resource management.
Sustainable Water Management Powerpoint Presentation SlidesSlideTeam
Introducing Sustainable Water Management PowerPoint Presentation Slides. This Water resource system PowerPoint slideshow can be used to explain the overview of market size, growth rate, and capital expenditure of the water industry. You can discuss the process of planning, developing, and managing the optimum use of water. The survey data for determining water quality can be easily presented by using a water cycle management PowerPoint slideshow. Demonstrate the division of the wastewater treatment market by editing our content-ready water quality monitoring PowerPoint slide deck. You can easily edit our water resources presentation to highlight the natural processes and human processes that affect water quality. Key trends that will influence the water industry in the future such as increasing regulation, failing infrastructure, greater conservation, and efficiency, etc. can also be presented with the help of our ready-to-use water management PPT visuals. It is possible to present the features that describe a suitable location for the monitoring program. It is easy to explain topics like wastewater treatment process, wastewater reuse, global wastewater reuse by sector, treated wastewater quality parameter, etc by downloading this sustainable water management PowerPoint slide deck. https://bit.ly/3tEV5qm
drought monitoring and management using remote sensingveerendra manduri
Monitoring drought and its management became easier with the help of remote sensing..several drought monitoring indices can be used to monitor drought condition. this ppt consists of information regarding droughts in relation to agriculture and their monitoring with the help of remotely sense based indices.
4 Ways Artificial Intelligence Can Help Save the PlanetTyrone Systems
As the scale and urgency of the economic and human health impacts from our deteriorating natural environment grows, we have an opportunity to look at how AI can help transform traditional sectors and systems to address climate change, deliver food and water security, build sustainable cities, and protect biodiversity and human wellbeing.
Groundwater modeling has several purposes including understanding aquifer properties, characteristics, and response. It requires collecting hydrological, physical, and boundary condition data. Common groundwater modeling software includes MODFLOW and Sutra. The modeling process involves defining the problem, collecting data, choosing a code, running simulations, verifying results match field data through calibration, and using the model to inform management decisions.
Climate change impact assessment on hydrology on river basinsAbhiram Kanigolla
The document discusses applying remote sensing and GIS techniques to assess the impacts of climate change on hydrology in river basins. It describes using the SWAT hydrological model to simulate the water balance of the Krishna River basin in India under current and future climate scenarios from regional climate models. Key steps involved gathering spatial data on terrain, land use and soils, calibrating and validating SWAT using historical weather data, and running the model for control and climate change scenarios to analyze changes in stream flows, runoff and groundwater. The results show increases in annual discharge and surface runoff in the basin in future climate scenarios.
Water Resource Management Powerpoint Presentation SlidesSlideTeam
Discuss the process of planning, developing, and managing the optimum use of water resources by using Water Resource Management PowerPoint Presentation Slides. This Water resource system PowerPoint slideshow can be used to explain the overview of market size, growth rate, and capital expenditure of the water industry. You can present the survey data for determining water quality by using the water cycle management PPT slideshow. Demonstrate the division of the wastewater treatment market by editing our content-ready water quality monitoring PowerPoint slide deck. You can easily edit our water resources presentation to highlight the natural processes and human processes that affect water quality. Showcase the leading factors that will affect the performance of the water technology market by using water quality assurance PowerPoint visuals. Key trends that will influence the water industry in the future such as increasing regulation, failing infrastructure, greater conservation, and efficiency, etc. can also be presented with the help of our ready-to-use water management PPT visuals. Discuss how you can design an effective water quality monitoring program by downloading our professionally designed water resource management PowerPoint slides. https://bit.ly/3fb5ExJ
This document presents a case study of coupling surface water and groundwater models in the Netravathi river basin located in southern India. It summarizes the data collected and methodology used. Key data included a digital elevation model, soil data, land use/land cover maps, rainfall and weather data, hydrological data including streamflow, and groundwater levels. The methodology involved using SWAT to model surface water hydrology and estimate groundwater recharge, then coupling the SWAT outputs to a MODFLOW groundwater model to allow a more complete analysis of the regional hydrological system.
Predicting crop yield and response to Nutrients from soil spectra at WCSS 201...CIAT
This document presents a study that uses soil spectroscopy to predict crop yields and response to fertilizers in sub-Saharan Africa. The study collected soil spectra and yield data from plots in Tanzania and Malawi. Statistical models like partial least squares regression and random forest were used to determine how much of the variance in yield and response could be explained by soil spectra alone and in combination with other soil, topographic, and weather data. The models were able to explain up to 65% of the variance in yield, with soil spectra and additional data like rainfall and topography each contributing. The study aims to refine yield predictions and help smallholder farmers apply optimal fertilizer levels based on cheap soil spectral analyses.
Flood risk mapping using GIS and remote sensingRohan Tuteja
This document presents a study on flood risk mapping in the Kalyan-Dombivli area of India using GIS techniques. It outlines the scope of the study, aim and objectives which are to identify low-lying areas and analyze flood risk factors. The methodology includes generating GIS data like land use/cover maps from remote sensing data and field surveys. Flood risk is assessed based on physical, demographic, and socioeconomic vulnerability indicators as well as hazard indicators like rainfall. The results found increased risk areas due to changes in land use/cover, improper drainage networks, and population growth. Recommendations include mainstreaming disaster risk reduction and using remote sensing for database management.
Application of RS and GIS in Groundwater Prospects ZonationVishwanath Awati
This document discusses using remote sensing and GIS techniques to map groundwater prospects zones. It presents a case study of applying these methods in Bata Valley, Himachal Pradesh, India. The methodology involves developing thematic maps of factors like geology, land use, and water levels. These maps are then overlaid and analyzed in GIS to identify zones of good, moderate, or poor groundwater potential. The study concludes these techniques can effectively map groundwater prospects and inform management plans.
The document discusses integrated water resources management (IWRM) in Nepal. It begins by defining IWRM and outlining its key principles. It then describes Nepal's water resources and the various ways water is used. The document also discusses the challenges facing water management in Nepal and outlines the tools and approaches used in IWRM, including water assessments, impact assessments, and performance evaluation. It analyzes Nepal's policies and institutions related to IWRM and concludes that while IWRM principles have been adopted, developing effective local institutions remains a challenge.
The following presentation was delivered by Robert Morrison, Principal Consultant at Esri Ireland, at the 2019 NICS ICT Conference in October 2019.
The presentation focuses on taking a geographic approach to machine learning to help you "see what other's can't".
Imagery and remotely sensed data is a valuable resource for many organisations who have made substantial investment obtaining the data. The field of Machine Learning is both broad and deep and is constantly evolving. Using ArcGIS and Machine Learning allows organisations to derive valuable new content.
ArcGIS is an open, interoperable platform that allows for the integration of complementary methods and techniques that empower ArcGIS users to solve complex, real-world problems in a fundamentally spatial way.
Learn how by combining powerful built-in Image analysis tools with any machine learning package users can benefit from the spatial validation, geo-enrichment and visualisation. See how this Machine Learning is being applied in real world use-cases from marine farming and crime analysis to agriculture and sustainability.
This document outlines a water security planning case study from Chhuanthar Tlangnuam village in Mizoram, India. It describes the village demographics, 6 springs that supply water, and seasonal water availability. Field visits involved mapping resources and social aspects, surveys of households, and water demand calculations. Analysis found water demand exceeds supply in summer. A water security plan was developed to address the gap.
Climate Change Impact Assessment on Hydrological Regime of Kali Gandaki BasinHI-AWARE
The presentation focuses on the findings of the impact of climate change on the hydrological regime and water balance components of the Kali Gandaki basin in Nepal. The Soil and Water Assessment Tool (SWAT) has been used to predict future projections.
This study explains the use of remote sensing data for spatially distributed hydrological modeling using the MIKE-SHE software used in Tarim River Basin CHINA
This document discusses trend analysis of time series data. It defines time series as measurements of a variable taken at regular intervals over time. Time series can show trends, seasonal variations, cyclical variations, and irregular variations. Trend analysis determines if there is a significant increasing or decreasing trend in the data over time. Linear regression and non-parametric Mann-Kendall tests are common methods used to test for trends and estimate their magnitude. The selection of an appropriate trend analysis method depends on characteristics of the water resources data such as distributions, outliers, and missing values.
DWS15 - Connected Things Forum - Industrial internet today - Vincent Champain...IDATE DigiWorld
1. Jeff Immelt, the CEO of GE, states that industrial companies must now view themselves as software and analytics companies as well due to the rise of the industrial internet.
2. The industrial internet is fueled by innovations in hardware, software, sensors, data science, cloud computing, and mobile technology that have led to massive decreases in costs and increases in capabilities.
3. GE aims to leverage these trends and its data science expertise to generate significant customer savings and business value through services enabled by connecting machines and analyzing industrial data.
Presentation of the project OpenFridge in the Workshop on Big Data and Society Data Economy, Real-Time Mining and Analytics, Mining Techniques for Online and Customer Service in Big data Era Part of the 2013 IEEE International Conference on Big Data (IEEE Big Data 2013) 6-9 October 2013, Silicon Valley, CA, USA
An Ecosystem Approach to Artificial IntelligenceAlex Liu
Dr. Alex Liu proposes an ecosystem approach to artificial intelligence to address high failure rates of AI projects. An AI ecosystem has three elements: 1) a data portal to share raw and preprocessed data, 2) a computing platform to share expertise and automate tasks, and 3) a data scientist community to collaborate. By bringing together data, algorithms, scientists, and organizations in an orchestrated way, an AI ecosystem can deliver more value than any individual entity alone.
Aws keynote oil and gas calgary industry day - jon guidrozAmazon Web Services
Jon is the head of worldwide Business Development for Energy and Utilities Industries at Amazon Web Services. He presents the State of the Oil and Gas Industry, and how business, engineering, and operations support applications, are solved using the AWS Cloud.
How Can AI and IoT Power the Chemical Industry?Xiaonan Wang
AI, IoT and Blockchain tech briefing to the industry to showcase our research at NUS.
by Dr. Xiaonan Wang
Assistant Professor
NUS Department of Chemical & Biomolecular Engineering
This document provides an overview of the Internet of Things presented by Daeyoung Kim, the Director of Auto-ID Labs at KAIST. It discusses several case studies and research projects around healthcare applications, smart agriculture and food traceability. It also covers the role of standards from GS1 and technologies developed at Auto-ID Labs like Oliot, SNAIL, and EPCIS that aim to realize the vision of connecting everything to the Internet and supporting the exchange of information.
Steven Reese at Seattle Technology Leadership SummitSeattleSIM
This document discusses the Internet of Things (IoT) and the Internet of Everything (IoE). It begins with definitions of IoT and examples of connected "things". It then explains how IoE is transforming consumer interactions and the opportunity it presents. The document discusses Presidio, an infrastructure provider, and their "OASIS" vehicle solution. It calls on readers to consider how IoT/IoE could apply to their own business, such as for reducing shrinkage, enabling new business models, and physical security applications. The presentation aims to be collaborative and cover key topics like the $19 trillion market opportunity and next steps for capturing value.
This presentation discusses using EPCIS (Electronic Product Code Information Services) and distributed storage and processing platforms like Oliot, Cassandra, and Storm for managing real-time IoT data from RFID and sensor devices. It proposes extending EPCIS standards to support additional IoT device event types and using Cassandra for distributed storage and Storm for real-time analytics of large volumes of continuous IoT data streams.
Sensing-as-a-Service - An IoT Service Provider's PerspectivesDr. Mazlan Abbas
UM-MCMC Connected Communities and Internet of Things (IoT): Building Value through Visibility
at Universiti Malaya (UM)
Wednesday, December 10, 2014 from 8:00 AM to 4:00 PM (MYT)
Kuala Lumpur, Malaysia
Streaming Analytics for IoT-Oriented ApplicationsDATAVERSITY
This document discusses streaming analytics for IoT applications. It begins by outlining how IoT is generating new sources of data and value. It then discusses streaming analytics as an approach to analyze data in motion from IoT sensors. The document reviews open source streaming analytics platforms and commercial solutions, highlighting vendors in the emerging streaming analytics as a service space. It concludes by offering tips for organizations to evaluate how streaming analytics can create value from their IoT data.
This document discusses big data and cloud computing. It describes how data volumes are growing exponentially and will increase 44-fold by 2020. It also discusses how cloud infrastructure provides unlimited computational power to process large and diverse data sources to gain statistically significant insights. Finally, it promotes a big data cloud service that aims to reduce friction for business users.
This document discusses service systems and their impact on quality of life. It begins by outlining different types of systems that focus on (A) flows of things humans need like transportation and supply chains, (B) human activities like retail, banking, and education, and (C) human governance systems like cities, states, and nations. It then provides more depth on these systems and the disciplines that support them. The document emphasizes that quality of life results from quality of service systems as well as quality jobs and investment opportunities. It concludes by stating the best way to predict the future is to inspire students to build it better.
MAKING SENSE OF IOT DATA W/ BIG DATA + DATA SCIENCE - CHARLES CAIBig Data Week
Charles Cai has more than two decades of experience and track records of global transformational programme deliveries – from vision, evangelism to end-to-end execution in global investment banks, and energy trading companies, where he excels at designing and building innovative, large scale, Big Data systems in high volume low latency trading, global Energy Trading & Risk Management, and advanced temporal and geospatial predictive analytics, as Chief Front Office Technical Architect and Head of Data Science. He’s also a frequent speaker at Google Campus, Big Data Innovation Summit, Cloud World Forum, Data Science London, QCon London and MoD CIO Symposium etc, to promote knowledge and best practice sharing, with audience ranging from developers, data scientists, to CXO level senior executives from both IT and business background. He has in-depth knowledge and experience Scala, Python, C# / F#, C++, Node.js, Java, R, Haskell programming languages in Mobile, Desktop, Hadoop/Spark, Cloud IoT/MCU and BlockChain etc, and TOGAF9, EMC-DS, AWS CNE4 etc. certifications.
In this talk I gave an overview of some of the tools that Microsoft Azure offers to researchers. I spoke about Microsoft's Big Data platform, called HDInsight, that allows for creating Spark and Hadoop applications; about Azure ML Studio, a GUI for developing machine learning models very quickly; and about the Data Science Virtual Machine (DSVM), a VM targeted to data scientists and machine learning professionals, which contains all the needed software to create any machine learning system.
Internet of Things and the Value of Tracking EverythingPaul Barsch
This presentation was given to an executive MBA session at UCSD in April 2016. The session reviewed big data, internet of things, and how companies are gaining value from location, sensor, manufacturing and other data to make better business decisions.
The document discusses artificial intelligence (AI) and data analytics opportunities in the oil and gas industry. It provides examples of how AI can be used for virtual assistants, video analytics, fleet management, production optimization, preventative maintenance, and precision drilling. The benefits of these applications include increased profitability, risk mitigation, improved agility, and cost reductions. It also discusses Dell Technologies AI and HPC solutions that can enable oil and gas companies to leverage AI for applications like reservoir modeling and autonomous vehicles.
The document summarizes the evolution of the semantic grid from its origins in 2001 to the present. It describes how early work on the semantic grid aimed to close the gap between grid applications and the vision of global e-science collaboration. Key developments included linking grid services with semantic web technologies to enable automation and advanced functionality through machine-processable descriptions. The semantic grid is now seen as an important approach for virtual research environments that support both formal and informal scientific processes through collaborative tools and persistent representations of discussions.
Citizen Actuation For Lightweight Energy ManagementEdward Curry
In this work, we aim to utilise the concept of citizen sensors but also introduce the theory of citizen actuation. Citizen sensors observe, report, and collect data – we propose by supporting these citizen sensors with methods to affect their surroundings we enable them to become citizen actuators. We outline a use case for citizen actuation in the Energy Management domain, propose an architecture (a Cyber-Physical Social System) built on previous work in Energy Management with Twitter integration, use of Complex Event Processing (CEP), and perform an experiment to test this theory. We motivate the need for citizen actuation in Building Management Systems due to the high cost of actuation systems. We define the concept of citizen actuation and outline an experiment that shows a reduction in average energy usage of 24%. The experiment supports the concept of citizen actuation to improve energy usage within the experimental environment and we discuss future research directions in this area.
CHINA’S GEO-ECONOMIC OUTREACH IN CENTRAL ASIAN COUNTRIES AND FUTURE PROSPECTjpsjournal1
The rivalry between prominent international actors for dominance over Central Asia's hydrocarbon
reserves and the ancient silk trade route, along with China's diplomatic endeavours in the area, has been
referred to as the "New Great Game." This research centres on the power struggle, considering
geopolitical, geostrategic, and geoeconomic variables. Topics including trade, political hegemony, oil
politics, and conventional and nontraditional security are all explored and explained by the researcher.
Using Mackinder's Heartland, Spykman Rimland, and Hegemonic Stability theories, examines China's role
in Central Asia. This study adheres to the empirical epistemological method and has taken care of
objectivity. This study analyze primary and secondary research documents critically to elaborate role of
china’s geo economic outreach in central Asian countries and its future prospect. China is thriving in trade,
pipeline politics, and winning states, according to this study, thanks to important instruments like the
Shanghai Cooperation Organisation and the Belt and Road Economic Initiative. According to this study,
China is seeing significant success in commerce, pipeline politics, and gaining influence on other
governments. This success may be attributed to the effective utilisation of key tools such as the Shanghai
Cooperation Organisation and the Belt and Road Economic Initiative.
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/)
KuberTENes Birthday Bash Guadalajara - K8sGPT first impressionsVictor Morales
K8sGPT is a tool that analyzes and diagnoses Kubernetes clusters. This presentation was used to share the requirements and dependencies to deploy K8sGPT in a local environment.
Batteries -Introduction – Types of Batteries – discharging and charging of battery - characteristics of battery –battery rating- various tests on battery- – Primary battery: silver button cell- Secondary battery :Ni-Cd battery-modern battery: lithium ion battery-maintenance of batteries-choices of batteries for electric vehicle applications.
Fuel Cells: Introduction- importance and classification of fuel cells - description, principle, components, applications of fuel cells: H2-O2 fuel cell, alkaline fuel cell, molten carbonate fuel cell and direct methanol fuel cells.
3. Artificial Intelligence
TERMINOLOGY
27.11.2017 Kalervo Kylätie / Fluidit LTD
Algorithm
These are the building blocks of an any
A.I and a computer program.
AlgorithmAlgorithm
Neural Networks
For storing data and
processing data relations
MachineLearning
Supervised Learning
“A Cat” “A Cat”
“A Cat”
“A Cat”
Reinforced learning
Deep Learning
0% Cat 10% Cat 25% Cat 75% Cat
100% Cat
Learning in use. A.I. starts to learn why something is
a cat. “Animal, four legs, whiskers….."
“Not a
cat”
4. WHAT IS A.I. USED FOR ALREADY?
27.11.2017 Kalervo Kylätie / Fluidit LTD
Bottom line is, that A.I. is
used to enhance and
transform human labor.
Education Finance Heavy industry Healthcare
Marketing and
Sales
Customer
service
Transportation Infrastructure –
Water sector?
My hypothesis:
1 doctor does one diagnosis in
1 hour.
1 doctor aided with A.I pre-
diagnosis could do 10-30
diagnoses in 1 hour.
5. WHAT COULD BE THE POSSIBLE USABLE
APPLICATIONS IN WATER INDUSTRY?
27.11.2017 Kalervo Kylätie / Fluidit LTD
Difficulty
Advantage
Billing
Customer
service
Pipe connection
application process
Monitoring water
quality
Maintaining and
updating network
information
Monitoring overall
health of a network
and it’s systems
Optimizing water
production
Planning new
pipelines
Auto repair bots
Automated
excavation
Predicting effects of
different events (human or
environmental related)
Leak detection
Communications
Forecastig failures
Optimizing
maintenance routines
Automated investment
optimization
Online simulations
6. LEARNING MATERIALS FOR
WATER SECTOR A.I.
27.11.2017 Kalervo Kylätie / Fluidit LTD
Planning
standards
Best
practices
Scada data
Billing data
Electricity
price
Groundwate
r levels Social media
behavior
Events in the
area
Google
analytics
Network
models
Network
information system
Planning
information
Pipe and machinery
prices
Material
Stock
Financial
information
Human
resources
Soil
information
Weather
information
Emergency
center
Supervised Learning
Reinforced learning
Deep Learning
“Ok sure, no problem.”
Point cloud and
height models “Ah…too much data.”
+Much more+
7. UTILIZATION: NETWORK PLANNING
AI PLANTRON
27.11.2017 Kalervo Kylätie / Fluidit LTD
Algorithms and
Neural networks
Supervised Learning
Reinforced Learning
Learning in action – Deep Learning
Hello
World!
• Daily consumption = 120 l/ person (get
data from SCADA.AI)
• Average velocity in pipes: 0.6 m/s (try to
keep it)
• Depth depends on frost / other infra (ask
infra data from infra AI)
• Cost of pipes per meters is listed here.
(GoogleIT)
• These are all the earlier plans that have
been made
…
Plantron.message
(“Hello World!”)
“Plantron: What is
the best water main
plan for this area?”
“With my current
calculations:”
8. UTILIZATION: NETWORK PLANNING
AI PLANTRON
27.11.2017 Kalervo Kylätie / Fluidit LTD
“With my current
calculations:”
“How about this?” “How about this?” “How about this?”
“No”
“No” “Accepted”“No”
Education
“Ashok Goel created a teaching assistant for his class in artificial Intelligence. After some tinkering by the research team, Jill found her groove and soon was answering questions with 97 percent certainty.”
Finance
Robot trading, no need for people running and screaming in stock exchanges.
Heavy industry
Assembly robots and automatons, Machine vision to spot failures, or welding bots and testing bots.
Automatized harbours – In Tampere Kalmar has pilot Inland in Rusko.
Hospitals and medicine
A.I. Diagnosis based on persons behavior and symptoms compared to all data in all over the world yields better results than single persons opinion.
Predict best cancer treatment for a patient based on his/hers medical data (Microsoft)
Human Resources & Recruiting
A.I. that generates specific question patterns based on candidates CV for preliminary job interview
Marketing and sales
Google, Facebook countless A.I. implementations
Vainu.io – Business lead A.I.
Online and telephone customer service
Customer Helpdesk robots that regocnize specific keywords and forward people to right subsites
Siri etc.
Transportation
Autonomous cars that can operate without a driver (24 000 driverless cars to Uber from Volvo)