This document summarizes a review of 134 studies from the past 25 years on modeling residential water consumption and informing water demand management strategies. The studies analyzed how smart meter technology, which provides near-continuous water usage data at high spatial and temporal resolution, has advanced the ability to characterize, model and design user-oriented strategies. While previous research focused on specific aspects, there was limited integration of specialized methodologies; the review provides a framework to classify residential water demand modeling studies and identify trends and future opportunities. Growing populations, constrained water supplies and climate change will require more integrated procedures to effectively support modeling and management across many countries.
Australia with a Drying Climate - Sustainable urban water management. By what...SmartH2O
The document discusses sustainable urban water management strategies for Perth, Western Australia as the region experiences drying climate conditions and declining rainfall. It outlines three levels of strategies: 1) behavioral change programs like H2omesmart, 2) improved efficiency standards for appliances, and 3) new technologies such as decentralized seawater desalination plants and dual reticulation systems. Case studies on these initiatives show potential for significant water savings through community-based social marketing, more efficient devices, and alternative water sources. Future research is proposed on developing new urban villages with integrated water recycling and renewable energy systems.
ICT solutions for highly-customized water demand management strategiesSmartH2O
1) Smart metering technologies and big data analytics can help water utilities better understand residential water usage patterns and identify different consumption profiles.
2) Gamification approaches, like the SmartH2O project's "DropTheQuestion" app, show potential for inducing behavioral change and reducing household water consumption. Preliminary results from SmartH2O indicate water savings of 10% on average.
3) Further analysis of smart meter data from over 11,000 households in Valencia, Spain identified common daily, weekly, and hourly water usage patterns and helped classify households into consumption categories from very high to low users.
Developing a stochastic simulation model for the generation of residential wa...SmartH2O
This document reviews literature on using smart water meters to model and manage residential water demand. It discusses how smart meter data collected at high temporal and spatial resolution has advanced the ability to characterize, model, and design water conservation strategies. However, research thus far has focused on these aspects separately without much integration. The review provides a framework to classify water demand modeling studies and identifies trends and future challenges, such as supporting more integrated modeling and management approaches to address growing populations, limited water resources, and climate change impacts across many countries.
Smart metering, water pricing and social media to stimulate residential water...SmartH2O
The document discusses the SmartH2O project which aims to stimulate residential water efficiency through smart metering, water pricing, and social media. The project will understand current water consumption behaviors, predict how behaviors can be influenced by social awareness campaigns, dynamic water prices, and then raise consumer awareness of their habits to encourage water reduction. Smart meters will measure the impact of different policies on consumption while social networks, feedback apps, and competitive pricing schemes will engage consumers to conserve water. The project will test these approaches through case studies in the UK and Switzerland.
This document summarizes a review of 134 studies from the past 25 years on modeling residential water consumption and informing water demand management strategies. The studies analyzed how smart meter technology, which provides near-continuous water usage data at single households, has advanced the ability to characterize, model and design user-oriented water conservation strategies. While previous research focused on specific aspects, there is limited integration of specialized methodologies. Growing populations, constrained water supplies and climate change will require more integrated procedures to effectively support residential water demand modeling and management worldwide.
Smart metering technologies allow for gathering high resolution water demand data in the residential sector, opening up new opportunities for the development of models describing water consumers’ behaviors. Yet, gathering such accurate water demand data at the end-use level is limited by metering intrusiveness, costs, and privacy issues. In this paper, we contribute a stochastic simulation model for synthetically generating high-resolution time series of water use at the end-use level. Each water end-use fixture in our model is characterized by its signature (i.e., its typical single-use pattern), as well as frequency distributions of its number of uses per day, single use duration, time of use during the day, and contribution to the total household water demand. The model relies on statistical data from a real-world metering campaign across 9 cities in the US. Showcasing our model outputs, we demonstrate the potential usability of this model for characterizing the water end-use demands of different communities, as well as for analyzing the major components of peak demand and performing scenario analysis.
Australia with a Drying Climate - Sustainable urban water management. By what...SmartH2O
The document discusses sustainable urban water management strategies for Perth, Western Australia as the region experiences drying climate conditions and declining rainfall. It outlines three levels of strategies: 1) behavioral change programs like H2omesmart, 2) improved efficiency standards for appliances, and 3) new technologies such as decentralized seawater desalination plants and dual reticulation systems. Case studies on these initiatives show potential for significant water savings through community-based social marketing, more efficient devices, and alternative water sources. Future research is proposed on developing new urban villages with integrated water recycling and renewable energy systems.
ICT solutions for highly-customized water demand management strategiesSmartH2O
1) Smart metering technologies and big data analytics can help water utilities better understand residential water usage patterns and identify different consumption profiles.
2) Gamification approaches, like the SmartH2O project's "DropTheQuestion" app, show potential for inducing behavioral change and reducing household water consumption. Preliminary results from SmartH2O indicate water savings of 10% on average.
3) Further analysis of smart meter data from over 11,000 households in Valencia, Spain identified common daily, weekly, and hourly water usage patterns and helped classify households into consumption categories from very high to low users.
Developing a stochastic simulation model for the generation of residential wa...SmartH2O
This document reviews literature on using smart water meters to model and manage residential water demand. It discusses how smart meter data collected at high temporal and spatial resolution has advanced the ability to characterize, model, and design water conservation strategies. However, research thus far has focused on these aspects separately without much integration. The review provides a framework to classify water demand modeling studies and identifies trends and future challenges, such as supporting more integrated modeling and management approaches to address growing populations, limited water resources, and climate change impacts across many countries.
Smart metering, water pricing and social media to stimulate residential water...SmartH2O
The document discusses the SmartH2O project which aims to stimulate residential water efficiency through smart metering, water pricing, and social media. The project will understand current water consumption behaviors, predict how behaviors can be influenced by social awareness campaigns, dynamic water prices, and then raise consumer awareness of their habits to encourage water reduction. Smart meters will measure the impact of different policies on consumption while social networks, feedback apps, and competitive pricing schemes will engage consumers to conserve water. The project will test these approaches through case studies in the UK and Switzerland.
This document summarizes a review of 134 studies from the past 25 years on modeling residential water consumption and informing water demand management strategies. The studies analyzed how smart meter technology, which provides near-continuous water usage data at single households, has advanced the ability to characterize, model and design user-oriented water conservation strategies. While previous research focused on specific aspects, there is limited integration of specialized methodologies. Growing populations, constrained water supplies and climate change will require more integrated procedures to effectively support residential water demand modeling and management worldwide.
Smart metering technologies allow for gathering high resolution water demand data in the residential sector, opening up new opportunities for the development of models describing water consumers’ behaviors. Yet, gathering such accurate water demand data at the end-use level is limited by metering intrusiveness, costs, and privacy issues. In this paper, we contribute a stochastic simulation model for synthetically generating high-resolution time series of water use at the end-use level. Each water end-use fixture in our model is characterized by its signature (i.e., its typical single-use pattern), as well as frequency distributions of its number of uses per day, single use duration, time of use during the day, and contribution to the total household water demand. The model relies on statistical data from a real-world metering campaign across 9 cities in the US. Showcasing our model outputs, we demonstrate the potential usability of this model for characterizing the water end-use demands of different communities, as well as for analyzing the major components of peak demand and performing scenario analysis.
PROFILING RESIDENTIAL WATER USERS’ ROUTINES BY EIGENBEHAVIOR MODELLINGSmartH2O
This document proposes a method of segmenting residential water users into clusters based on their daily water usage routines, or eigenbehaviors, extracted from smart meter data. It involves extracting the eigenbehaviors of individual users through principal component analysis to characterize their typical daily usage patterns. The users are then clustered based on their eigenbehavior profiles. Finally, the clusters are characterized to inform demand management strategies for reducing water consumption. The method is demonstrated on a case study of 175 water users in Locarno, Switzerland monitored over 7 months with hourly smart meter data.
The SmartH2O project and the role of social computing in promoting efficient ...SmartH2O
The document discusses the SmartH2O project which aims to promote efficient residential water use through social computing. The project seeks to understand current water consumer behavior using smart meter data, incorporate behavioral data from a smart app, and create user models. It then aims to raise social awareness of water conservation through social networks and dynamic pricing schemes. A key objective is to stimulate collective behavior changes and social influences on water usage. The role of persuasive games in influencing consumer behavior is also discussed.
Public awareness and feedback – Insights from the SmartH2O project SmartH2O
The document discusses insights from the SmartH2O project on raising public awareness and providing feedback to induce behavior change related to water consumption. It outlines two main challenges of how to present consumption information to users and motivate them to change behavior. It then describes the SmartH2O approach which includes a consumer portal with gamification elements, consumption feedback, tips, goals and rewards to engage users. Initial results from a validation study in Spain show positive user acceptance of the technology and motivation from gamification. Analysis of user activity levels and consumption data also provide early signs that the approach may help influence behaviors.
Visualizing & gamifying water & energy consumption for behavior changeIsabel Micheel
Micheel, I., Novak, J., Fraternali, P., Baroffio, G., Castelletti, A., and Rizzoli, A.-E., "Visualizing & gamifying water & energy consumption for behavior change". Paper presentation at Fostering Smart Energy Applications (FSEA) 2015 workshop at Interact2015. Bamberg, 15 Sep 2015. Workshop proceedings available here: http://it4se.informatik.fh-augsburg.de/FSEA15/proceedings.html
The paper presented in the slides considers the structural similarities in approaches and lessons learned in the development of applications for behavior change in water and energy saving. We show how the domains of water and energy are related and propose a first set of design guidelines for building such solutions, especially regarding visualization and gamification of water and/or energy consumption. We exemplify how such guidelines can be applied with the designs and prototypes of a gamified application for water saving behavior change from our SmartH2O project. Based on feedback from user and stakeholder workshops and online discussions, we discuss how the initial design guidelines synthesized from the literature have been refined. In a next step, we will validate them by deploying the implemented prototype in real- world trials with several thousand smart-metered households in the UK, Switzerland and Spain.
The work presented has come out of the SmartH2O project: EU FP7, No. 619172, 2014-2017. smarth2o- fp7.eu/
Water projects, case studies and experiencesSmartH2O
This document discusses water demand management strategies used by large water utilities. It focuses on London's water supply utility which serves 15 million customers. Key strategies discussed include demand management through technological, financial, legislative, operational and educational approaches. The document also discusses including user modeling and monitoring of water consumption at the individual consumer level to help forecast future water demand. Machine learning techniques like feature extraction, user profiling and clustering are explored to predict consumer water usage based on relevant determinants.
The document summarizes research on integrated water management of the Red-Thai Binh river system in Vietnam under changing conditions. The researchers used optimization methods to design reservoir operating policies that balance multiple objectives like hydropower production, flood control, and water supply. Climate change assessments showed vulnerabilities are amplified by operations and depend on uncertain future scenarios. Further research will introduce socio-economic factors and robust optimization to support adaptation strategy design.
The SmartH2O project receives EU funding to develop technology for improving water efficiency through new business partnerships between water utilities and customers. The project aims to turn smart meter water consumption data into a business intelligence tool to help utilities predict demand, optimize operations, and foster sustainable customer behavior. The technology includes a gamified consumer portal, data analytics for customer segmentation and behavioral change, and serious games for customer engagement. The system has been in alpha testing and will be deployed in London, Valencia, and other locations in 2016-2017.
presentation at European Utility Week, Vienna, Nov. 2015Piero Fraternali
This document discusses using smart water meter data and analytics to improve demand management and customer relationships for water utilities. It describes collecting high frequency consumption data from smart meters, analyzing the data to classify customers and detect usage patterns, and developing a consumer portal with personalized tips, goals, comparisons to peers, and games to motivate more efficient water use. The system is currently being piloted with 400 households in Switzerland and will be deployed in London and Valencia in upcoming years.
The document describes a project called the Integrated Management of the Red Thai Binh river system under change (IMRR) which aims to develop strategies for sustainable management of the Red-Thai Binh River System in Vietnam. The project uses integrated water resources management, participatory planning, and modeling and optimization tools. It also involves capacity building activities like training courses. The project models the river system and reservoirs using various tools and analyzes how climate and water demand changes could impact the system and affect flood damages, water supply, and hydropower production. It explores how policies may need to adapt to different future scenarios.
A CMS based Geoportal targeted to manage information related to water resource management projects, powered with a full FOSS stack. A first application of the Geoportal is on the case study of Red Thai Binh River in Vietnam.
Gamification techniques can be used to encourage water conservation behaviors. The SmartH2O project applied gamification by developing a portal with points, badges, leaderboards and mobile games linked to household water usage data. Initial results from pilot tests in Switzerland and Spain found that gamification and social comparison features helped raise awareness of water consumption and motivated some users to reduce usage. However, gamification approaches may be more effective for some user types and contexts than others. Further evaluation is needed to fully understand the impacts of gamification on long-term water conservation.
Smart Water and Wastewater Management For Smart Cities - Mr. Anjum ParwezIPPAI
The document discusses smart water and wastewater management in Indian cities. It provides data on water availability, sources of drinking water, wastewater treatment, and initiatives to improve services in various cities. It highlights challenges like inadequate and inequitable water supply, high non-revenue water, and lack of sewerage infrastructure. Recent initiatives by organizations like BWSSB and under programs like AMRUT and JnNURM aim to ensure regular water supply, reduce losses, recycle wastewater, and improve cost recovery through measures like metering and tariffs. Public-private partnerships are also being used to enhance water and sanitation services in cities.
The document discusses a conference on water management for smart cities in India. It notes that rapid urbanization is increasing challenges for water management in cities. The Ministry of Urban Development in India approved plans worth over 2 billion rupees for water supply and sewerage projects in 89 cities. The conference aims to bring together stakeholders to discuss challenges and develop smart approaches to deliver robust urban water infrastructure and services. Key issues to be discussed include water distribution challenges, preventative maintenance, smart metering, water quality and treatment technologies.
Policy Tools to Achieve Urban Water SecurityRobert Brears
TRADITIONALLY, URBAN WATER managers, faced with increasing demand for water alongside varying levels of supplies, have relied on largescale, supply-side infrastructural
projects, such as dams and reservoirs, to meet increased demands for water. This supply-side approach, however, is under increasing pressure from climate change, rapid population and economic growth and even land-use changes impacting the availability of good quality water of sufficient quantities. To enhance urban water security, water managers are turning towards demand-side management.
Facilitating behaviour change for the adoption of 'non-treatment' options for the implementation of the 2006 WHO wastewater use guidelines
Pay Drechsel, Hanna Karg and Eline Boelee
Presented at the IWA session "Hygienic Risks of Sanitation Systems" at the networking weekend of "Water and Health: Where Science Meets Policy"
The University of North Carolina at Chapel Hill, USA.
October 23-24, 2010
Presentation hold during EIP Water Conference in Porto, as part of the Porto Water Innovation Week in Session 8a “Water and the circular economy, part 3 – cities and water”
Behaviour change and incentive modelling for water saving: first results fr...SmartH2O
1) The document describes a behavior change and incentive model called SmartH2O that was developed to motivate households to save water through smart meter feedback, consumption visualizations, gamification, and rewards.
2) Preliminary results from a pilot study in Switzerland showed an average water consumption reduction of 33.8% among participants, with the highest reductions in low and medium-high consumption households. Technology acceptance results were also positive.
3) Gamification elements like badges and leaderboards showed promising early engagement from lead users, though the full impact of gamification still needs to be evaluated further. A larger validation study is planned for about 500,000 households in Valencia.
From Smart Water Meters to Demand and Customer Relationship ManagementSmartH2O
This document discusses using smart water meter data and analytics to improve demand management and customer relationships for water utilities. It describes collecting high frequency consumption data from smart meters, analyzing the data to classify customers and detect usage patterns, and developing a consumer portal with personalized tips, goals, comparisons to peers, and games to motivate more efficient water use. The system is currently being piloted with 400 households in Switzerland and will be deployed in London and Valencia in future years.
PROFILING RESIDENTIAL WATER USERS’ ROUTINES BY EIGENBEHAVIOR MODELLINGSmartH2O
This document proposes a method of segmenting residential water users into clusters based on their daily water usage routines, or eigenbehaviors, extracted from smart meter data. It involves extracting the eigenbehaviors of individual users through principal component analysis to characterize their typical daily usage patterns. The users are then clustered based on their eigenbehavior profiles. Finally, the clusters are characterized to inform demand management strategies for reducing water consumption. The method is demonstrated on a case study of 175 water users in Locarno, Switzerland monitored over 7 months with hourly smart meter data.
The SmartH2O project and the role of social computing in promoting efficient ...SmartH2O
The document discusses the SmartH2O project which aims to promote efficient residential water use through social computing. The project seeks to understand current water consumer behavior using smart meter data, incorporate behavioral data from a smart app, and create user models. It then aims to raise social awareness of water conservation through social networks and dynamic pricing schemes. A key objective is to stimulate collective behavior changes and social influences on water usage. The role of persuasive games in influencing consumer behavior is also discussed.
Public awareness and feedback – Insights from the SmartH2O project SmartH2O
The document discusses insights from the SmartH2O project on raising public awareness and providing feedback to induce behavior change related to water consumption. It outlines two main challenges of how to present consumption information to users and motivate them to change behavior. It then describes the SmartH2O approach which includes a consumer portal with gamification elements, consumption feedback, tips, goals and rewards to engage users. Initial results from a validation study in Spain show positive user acceptance of the technology and motivation from gamification. Analysis of user activity levels and consumption data also provide early signs that the approach may help influence behaviors.
Visualizing & gamifying water & energy consumption for behavior changeIsabel Micheel
Micheel, I., Novak, J., Fraternali, P., Baroffio, G., Castelletti, A., and Rizzoli, A.-E., "Visualizing & gamifying water & energy consumption for behavior change". Paper presentation at Fostering Smart Energy Applications (FSEA) 2015 workshop at Interact2015. Bamberg, 15 Sep 2015. Workshop proceedings available here: http://it4se.informatik.fh-augsburg.de/FSEA15/proceedings.html
The paper presented in the slides considers the structural similarities in approaches and lessons learned in the development of applications for behavior change in water and energy saving. We show how the domains of water and energy are related and propose a first set of design guidelines for building such solutions, especially regarding visualization and gamification of water and/or energy consumption. We exemplify how such guidelines can be applied with the designs and prototypes of a gamified application for water saving behavior change from our SmartH2O project. Based on feedback from user and stakeholder workshops and online discussions, we discuss how the initial design guidelines synthesized from the literature have been refined. In a next step, we will validate them by deploying the implemented prototype in real- world trials with several thousand smart-metered households in the UK, Switzerland and Spain.
The work presented has come out of the SmartH2O project: EU FP7, No. 619172, 2014-2017. smarth2o- fp7.eu/
Water projects, case studies and experiencesSmartH2O
This document discusses water demand management strategies used by large water utilities. It focuses on London's water supply utility which serves 15 million customers. Key strategies discussed include demand management through technological, financial, legislative, operational and educational approaches. The document also discusses including user modeling and monitoring of water consumption at the individual consumer level to help forecast future water demand. Machine learning techniques like feature extraction, user profiling and clustering are explored to predict consumer water usage based on relevant determinants.
The document summarizes research on integrated water management of the Red-Thai Binh river system in Vietnam under changing conditions. The researchers used optimization methods to design reservoir operating policies that balance multiple objectives like hydropower production, flood control, and water supply. Climate change assessments showed vulnerabilities are amplified by operations and depend on uncertain future scenarios. Further research will introduce socio-economic factors and robust optimization to support adaptation strategy design.
The SmartH2O project receives EU funding to develop technology for improving water efficiency through new business partnerships between water utilities and customers. The project aims to turn smart meter water consumption data into a business intelligence tool to help utilities predict demand, optimize operations, and foster sustainable customer behavior. The technology includes a gamified consumer portal, data analytics for customer segmentation and behavioral change, and serious games for customer engagement. The system has been in alpha testing and will be deployed in London, Valencia, and other locations in 2016-2017.
presentation at European Utility Week, Vienna, Nov. 2015Piero Fraternali
This document discusses using smart water meter data and analytics to improve demand management and customer relationships for water utilities. It describes collecting high frequency consumption data from smart meters, analyzing the data to classify customers and detect usage patterns, and developing a consumer portal with personalized tips, goals, comparisons to peers, and games to motivate more efficient water use. The system is currently being piloted with 400 households in Switzerland and will be deployed in London and Valencia in upcoming years.
The document describes a project called the Integrated Management of the Red Thai Binh river system under change (IMRR) which aims to develop strategies for sustainable management of the Red-Thai Binh River System in Vietnam. The project uses integrated water resources management, participatory planning, and modeling and optimization tools. It also involves capacity building activities like training courses. The project models the river system and reservoirs using various tools and analyzes how climate and water demand changes could impact the system and affect flood damages, water supply, and hydropower production. It explores how policies may need to adapt to different future scenarios.
A CMS based Geoportal targeted to manage information related to water resource management projects, powered with a full FOSS stack. A first application of the Geoportal is on the case study of Red Thai Binh River in Vietnam.
Gamification techniques can be used to encourage water conservation behaviors. The SmartH2O project applied gamification by developing a portal with points, badges, leaderboards and mobile games linked to household water usage data. Initial results from pilot tests in Switzerland and Spain found that gamification and social comparison features helped raise awareness of water consumption and motivated some users to reduce usage. However, gamification approaches may be more effective for some user types and contexts than others. Further evaluation is needed to fully understand the impacts of gamification on long-term water conservation.
Smart Water and Wastewater Management For Smart Cities - Mr. Anjum ParwezIPPAI
The document discusses smart water and wastewater management in Indian cities. It provides data on water availability, sources of drinking water, wastewater treatment, and initiatives to improve services in various cities. It highlights challenges like inadequate and inequitable water supply, high non-revenue water, and lack of sewerage infrastructure. Recent initiatives by organizations like BWSSB and under programs like AMRUT and JnNURM aim to ensure regular water supply, reduce losses, recycle wastewater, and improve cost recovery through measures like metering and tariffs. Public-private partnerships are also being used to enhance water and sanitation services in cities.
The document discusses a conference on water management for smart cities in India. It notes that rapid urbanization is increasing challenges for water management in cities. The Ministry of Urban Development in India approved plans worth over 2 billion rupees for water supply and sewerage projects in 89 cities. The conference aims to bring together stakeholders to discuss challenges and develop smart approaches to deliver robust urban water infrastructure and services. Key issues to be discussed include water distribution challenges, preventative maintenance, smart metering, water quality and treatment technologies.
Policy Tools to Achieve Urban Water SecurityRobert Brears
TRADITIONALLY, URBAN WATER managers, faced with increasing demand for water alongside varying levels of supplies, have relied on largescale, supply-side infrastructural
projects, such as dams and reservoirs, to meet increased demands for water. This supply-side approach, however, is under increasing pressure from climate change, rapid population and economic growth and even land-use changes impacting the availability of good quality water of sufficient quantities. To enhance urban water security, water managers are turning towards demand-side management.
Facilitating behaviour change for the adoption of 'non-treatment' options for the implementation of the 2006 WHO wastewater use guidelines
Pay Drechsel, Hanna Karg and Eline Boelee
Presented at the IWA session "Hygienic Risks of Sanitation Systems" at the networking weekend of "Water and Health: Where Science Meets Policy"
The University of North Carolina at Chapel Hill, USA.
October 23-24, 2010
Presentation hold during EIP Water Conference in Porto, as part of the Porto Water Innovation Week in Session 8a “Water and the circular economy, part 3 – cities and water”
Behaviour change and incentive modelling for water saving: first results fr...SmartH2O
1) The document describes a behavior change and incentive model called SmartH2O that was developed to motivate households to save water through smart meter feedback, consumption visualizations, gamification, and rewards.
2) Preliminary results from a pilot study in Switzerland showed an average water consumption reduction of 33.8% among participants, with the highest reductions in low and medium-high consumption households. Technology acceptance results were also positive.
3) Gamification elements like badges and leaderboards showed promising early engagement from lead users, though the full impact of gamification still needs to be evaluated further. A larger validation study is planned for about 500,000 households in Valencia.
From Smart Water Meters to Demand and Customer Relationship ManagementSmartH2O
This document discusses using smart water meter data and analytics to improve demand management and customer relationships for water utilities. It describes collecting high frequency consumption data from smart meters, analyzing the data to classify customers and detect usage patterns, and developing a consumer portal with personalized tips, goals, comparisons to peers, and games to motivate more efficient water use. The system is currently being piloted with 400 households in Switzerland and will be deployed in London and Valencia in future years.
Ergebnisse aus dem SmartH2O Projekt: Kundensensibilisierung mit spielerischen...SmartH2O
1) The SmartH2O project aims to increase water consumer awareness and encourage water savings through gamified smart meter applications and incentives.
2) Initial results from a pilot with 400,000 smart meters in Valencia, Spain found that water consumption decreased for 66% of users, with an average reduction of 6.5%.
3) User feedback indicated that the gamification elements like points, badges, tips, and comparisons to others were motivating. Ongoing communication will be needed to sustain user engagement over time.
A convex optimization approach for automated water and energy end use disaggr...SmartH2O
This document presents a convex optimization approach for automated disaggregation of water consumption data into end uses. It proposes modeling each end use as having finite operating modes and piecewise constant consumption profiles. A sparse optimization problem is formulated to minimize the fitting error between modeled and measured consumption, regularized by an L1-norm penalty to promote sparsity. Tests on electricity and water consumption data show the approach can accurately disaggregate consumption into end uses like toilet flushes and showers. Future work includes refinements to handle lower resolution data and tailored numerical solvers.
Persuasive games - concept, state of the art and issues on sustainability app...SmartH2O
This document discusses persuasive games and related concepts like serious games, gamification, and pervasive games. It summarizes several studies on persuasive games for sustainability and environmental issues. Key open problems discussed are how to treat and ensure privacy of massive data collected from players, and how to design games to guarantee long-term behavior change rather than just short-term effects. Retention techniques like casual gameplay, small investments, and frequent rewards are proposed to encourage long-term engagement.
Water Consumption (Evapo-Transpiration- ET), B. Taheri, S.M. Nabavi & MousaviMr.NENAwaterscarcity
Workshop on Operationalizing the Regional Collaborative Platform to Address ‘Water Consumption, Water Productivity and Drought Management’ in Agriculture, 27 - 29 October 2015, Cairo, Egypt
การวิเคราะห์โครงการแหล่งน้ำขนาดเล็กโดยวิธี integrated mental model and projec...Piriya Uraiwong
This document appears to be a presentation on integrating mental models and project lifecycles. It includes sections on failure analysis, stakeholder mental model analysis, and integrating mental models with a project lifecycle perspective. Tables and diagrams are included analyzing factors like finances, public participation, poverty, policy, corruption, and their relationships. The document proposes two scenarios: the current scheme involving issues like budget uncertainty, and a potential beneficiary contribution scheme involving collaboration and life cycle management.
Gray vs. Green: The Role of Watershed-scale Green Infrastructure Systems for ...Mcrpc Staff
This document discusses the role of green infrastructure systems for managing wastewater at a watershed scale. It begins by outlining the historical patterns of water movement through uplands and lowlands, and how contemporary development has reversed these patterns. It then describes various green infrastructure strategies that can replicate natural hydrology, including green roofs, porous pavements, bio-retention systems, rainwater harvesting, wastewater recycling, and native landscaping. The document provides examples of these strategies and concludes by discussing a new paradigm in wastewater treatment using lagoons and floating mats of bacteria to polish wastewater in a low-cost, low-energy manner.
Group 5 sustainable stormwater management(building services1)kohwenqi
This document provides information on sustainable stormwater management. It begins with an introduction on stormwater and the need for management. Examples of stormwater management techniques are then presented, including rain gardens, bioretention areas, vegetated swales, green roofs, and porous pavement. The installation processes for rain gardens and bioretention areas are described in multiple steps. Advantages and disadvantages of stormwater management are listed. The document concludes with references and appendices.
Power Up Your People: Emerging Tech and the Frictionless Employee Experience ...Selena Ricks
This document discusses how improving employee experience (EX) can positively impact customer experience (CX) and business outcomes. It argues that CX and EX are deeply interconnected, and companies that empower employees with frictionless tools see benefits like higher customer satisfaction and lower turnover. Examples are provided of companies that used mobile technologies to simultaneously solve customer and employee problems. The document concludes that co-designing experiences with both CX and EX in mind yields the strongest results, and that empowering employees with consumer-grade technologies gives them the autonomy, mastery and purpose to excel.
This document provides an overview of clinical and non-clinical waste training. It begins by outlining the aims and objectives of understanding waste streams, segregation requirements, handling procedures, and compliance implications. It then details the various types of clinical, hazardous, and domestic waste, and how to properly classify, store, and dispose of each according to regulations. Emphasis is placed on safety, segregation, documentation, and following waste hierarchy principles of prevention, reuse, recycling, recovery and disposal. Non-compliance can result in costs, penalties, legal action, reputational damage and environmental harm.
DEVELOPMENT OF CLEAN WATER DISTRIBUTION NETWORK CAPACITY BY USING WATERCADIAEME Publication
This document describes a study that used WaterCAD software to analyze and develop the clean water distribution network for Kedungkandang District in Malang, Indonesia. The study projected the population to reach 27,284 people by 2031. It determined the average daily clean water need would be 41,763 liters/second and peak hour need would be 65,150 liters/second. Hydraulic simulations found the water pressure would be between 1.6-2.3 atmospheres and velocities between 0.47-1.85 meters/second, meeting design criteria. The study concluded the existing network was sufficient with some pipe diameter changes required for development.
The International Commission on Irrigation and Drainage (ICID) was established as a Scientific, Technical and Voluntary Not-for-profit Non-Governmental International Organization (NGO) with headquarters in New Delhi, India.
This presentation shows information about ICID activities.
Assessing the importance of geo hydrological data acquisition in the developm...Alexander Decker
The document discusses two groundwater flow models developed for Lagos, Nigeria and Birmingham, UK. The Birmingham model had extensive geo-hydrological data including geology, groundwater levels, recharge rates, abstraction data, and aquifer parameters obtained from field tests. This allowed for detailed discretization, calibration, and reliable predictive capabilities. The Lagos model had limited data, requiring interpolation and extrapolation. It had coarse discretization and assumed parameters. This greatly limited its reliability and predictive ability. The document recommends improving Nigeria's geo-hydrological data acquisition and accessibility to enable more effective water resources management planning and modeling.
Smart city: an advanced framework for analyzing public sentiment orientation ...IJECEIAES
The coronavirus pandemic of the past several years has had a profound impact on all aspects of life, including resource utilization. One notable example is the increased demand for freshwater, a lifeblood of our planet, on the other hand, the smart city vision aims to attain a smart water management goal by investing in innovative solutions such as recycled water systems. However, the problem lies in the public’s sentiment and willingness to use this new resource which discourages investors and hinders the development of this field. Therefore, in our work, we applied sentiment analysis using an extended version of the fuzzy logic and neural network model from our previous work, to find out the general public opinion regarding recycled water and to assess the effects of sentiments on the public’s readiness to use this resource. Our analysis was based on a dataset of over 1 million text content from 2013 to 2022. The results show, from spatio-temporal perspectives, that sentiment orientation and acceptance- behavior towards using recycled water have increased positively. Additionally, the public is more concerned in areas driven by the smart city vision than in areas of medium and low economic development, where investment in sensibilization campaigns is needed.
ICT and agricultural development - impacts of information and communication t...Luiz Fernando do Amaral
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EIP Water Action Group City Blueprints September 2013EIP Water
The City Blueprint for Water is a baseline assessment of the sustainability of water management in a city (or other dominantly urban region). The result allows a city to quickly understand how advanced it is in sustainable water management and enables it to compare its status with other leading cities.
This project is one of nine Action Groups selected by the European Commission as an initial EIP Water Action Group.
Sixteen cities/regions have participated so far (August 2013) and many others are being approached. This is an opportunity to take part in a new and innovative programme to help improve city-level water stewardship, in the spirit of smart and sustainable cities.
The basic output is a simple radar chart as shown in the example from Melbourne at the top of this page. The chart provides a quick visual representation of the city’s water stewardship status, and is a tool for easy comparison between cities. It covers 24 key water-related subject areas, such as water footprint, water scarcity, water quality, drinking water availability and wastewater management.
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Development of an Open-Source Water Consumption Meter for HousingIEREK Press
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Presentation by Henry Neufeldt at the World Congress on Integrated Crop-Livestock-Forest Systems, 3rd international symposium on integrated crop-livestock systems. Brazil, July 2015
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Modeling Water Demand in Droughts (in England & Wales)Ben Anderson
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Data-driven behavioural modelling of residential water consumption to inform water demand management strategies
1. Data-driven behavioural modelling of residential water
consumption to inform water demand management strategies
M. Giuliani, A. Cominola, A. Alsahaf, A. Castelletti, M. Anda
EGU General Assembly 2016
2. US
246.2
Urban population in millions
81%
Urban percentage
Mexico
84.392
77%
Colombia
34.3
73%
Brazil
162.6
85%
Argentina
35.6
90%
Ukraine
30.9
68%
Russia
103.6
73%
China
559.2Urban population in millions
42%Urban percentage
Turkey
51.1
68%
India
329.3
29%
Bangladesh
38.2
26%
Philippines
55.0
64%
Indonesia
114.1
50%
S Korea
39.0
81%
Japan
84.7
66%
Egypt
33.1
43%
S Africa
28.6
60%
Canada
26.3
Venezuela
26.0
Poland
23.9
Thailand
21.5
Australia
18.3
Netherlands
13.3
Peru
21.0
Saudi Arabia
20.9
Iraq
20.3
Vietnam
23.3
DR Congo
20.2
Algeria
22.0Morocco
19.4
Malaysia
18.1
Burma
16.5
Sudan
16.3
Chile
14.6
N Korea
14.1
Ethiopia
13.0
Uzbekistan
10.1
Tanzania
9.9
Romania
11.6
Ghana
11.3
Syria
10.2
Belgium
10.2
80%
94%
62%
33%
89%
81%
73%
81%
67%
27%
33%
65%
60%
69%
32%
43%
88%
62%
16%
37%
25%
54%
49%
51%
97%
Nigeria
68.6
50%
UK
54.0
90%
France
46.9
77%
Spain
33.6
77%
Italy
39.6
68%
Germany
62.0
75%
Iran
48.4
68%
Pakistan
59.3
36%
Cameroon
Angola
Ecuador
Ivory
Coast
Kazakh-
stan
Cuba
Afghan-
istan
Sweden
Kenya
Czech
Republic
9.5
9.3
8.7
8.6
8.6
8.5
7.8
7.6
7.6
7.4
Mozam-
bique
Hong
Kong
Belarus
Tunisia
Hungary
Greece
Israel
Guate-
mala
Portugal
Yemen
Dominican
Republic
Bolivia
Serbia &
Mont
Switzer-
land
Austria
Bulgaria
Mada-
gascar
Libya
Senegal
Jordan
Zimbabwe
Nepal
Denmark
Mali
Azerbaijan
Singapore
El
Salvador
Zambia
Uganda
Puerto
Rico
Paraguay
UAE
Benin
Norway
New
Zealand
Honduras
Haiti
Nicaragua
Guinea
Finland
Uruguay
Lebanon
Somalia
Sri Lanka
Cambodia
Slovakia
Costa Rica
Palestine
Kuwait
Togo
Chad
Burkina
Ireland
Croatia
Congo
Niger
Sierra Leone
Malawi
Panama
Turkmenistan
Georgia
Lithuania
Liberia
Moldova
Rwanda
Kyrgyzstan
Oman
Armenia
Bosnia
Tajikistan
CAR
Melanesia
Latvia
Mongolia
Albania
Jamaica
Macedonia
Mauritania Laos
Gabon
Botswana
Slovenia
Eritrea
Estonia
Gambia
Burundi
Papua New Guinea
Namibia
Mauritius
Guinea-Bissau
Lesotho E Timor
Bhutan
Swaziland
Trinidad & Tobago
The earth reaches a momentous
milestone: by next year, for the first time
in history, more than half its population
will be living in cities. Those 3.3 billion
people are expected to grow to 5 billion
by 2030 — this unique map of the world
shows where those people live now
At the beginning of the 20th
century, the world's urban
population was only 220
million, mainly in the west
By 2030, the towns and
cities of the developing
world will make up 80%
of urban humanity
The new urban world
Urban growth, 2005—2010
Predominantly urban
75% or over
Predominantly urban
50—74%
Predominantly rural
25—49% urban
Predominantly rural
0—24% urban
Cities over 10 million people
(greater urban area)
Key
Tokyo
33.4
Osaka
16.6
Seoul
23.2
Manila
15.4
Jakarta
14.9
Dacca
13.8
Bombay
21.3
Delhi
21.1 Calcutta
15.5
Karachi
14.8
Shanghai
17.3
Canton
14.5
Beijing
12.7
Moscow
13.4
Tehran
12.1
Cairo
15.9
Istanbul
11.7
London
12.0
Lagos
10.0
Mexico
City
22.1
New York
21.8
Sao Paulo
20.4
LA
17.9
Rio de
Janeiro
12.2
Buenos
Aires
13.5
3,307,950,000The world’s urban population — from a total of 6,615.9 million SOURCE: UNFPA GRAPHIC: PAUL SCRUTONAfrica Asia Oceania Europe
0.1%
Eastern Europe
-0.4%
Arab States
Latin America
& Caribbean North America
3.2%
2.4%
1.3%
2.8%
1.7%
1.3%
Urban population is growing
Source: United Nations Population Fund, 2007
3. 2000 2030 2050
+130%
Domesticwaterdemand
41 megacities
worldwide
Source: United Nations. Department of Economic and Social Affairs. Population Division, 2010
Leflaive, X., et al. (2012), "Water", in OECD, OECD Environmental Outlook to 2050: The Consequences of Inaction, OECD Publishing, Paris
… and so residential water demand
4. city/district scale
Water demand management strategies
TECHNOLOGICAL (e.g., water efficient devices)
FINANCIAL (e.g., water price schemes, incentives)
LEGISLATIVE (e.g., water usage restrictions)
OPERATION & MAINTENANCE (e.g., leak detection)
EDUCATION (e.g., water awareness campaigns, workshops)
5. city/district scale
Water demand management strategies
TECHNOLOGICAL (e.g., water efficient devices)
FINANCIAL (e.g., water price schemes, incentives)
LEGISLATIVE (e.g., water usage restrictions)
OPERATION & MAINTENANCE (e.g., leak detection)
EDUCATION (e.g., water awareness campaigns, workshops)
customized WDMS
6. What is the current state-of-the-art
of residential Water Demand Management?
9. quarterly / half yearly basis readings
1 kilolitre (=1m3)
Traditional water meters
Traditional vs Smart water meters
10. Smart meters resolution: 72 pulses/L
(=72k pulses/m3 )
Data logging resolution: 5-10 s interval
Information on time-of-day for consumption
Smart water meters
Traditional vs Smart water meters
11. 36%
43%
13%
6%
<1%
Smart meters deployment sites worldwide
134 studies over the last 25 years
Cominola et al. (2015), Benefits and challenges of using smart meters for advancing residential water demand
modeling and management: A review, Enviornmental Modelling & Software.
14. CUSTOMIZED DEMAND
MANAGEMENT
CONSUMERS’
COMMUNITY
WATER
CONSUMPTION
MONITORING
BEHAVIORAL USER
MODELLING
_ SMART METERED WATER CONSUMPTION
_ PSYCHOGRAPHIC DATA
_ RESPONSE TO WDMS
_ technological
_ financial
_ legislative
_ operation and maintenance
_ education
3-step behavioral modelling procedure
SMART METERED
WATER CONSUMPTION
Users’ consumption class
(label)
USERS PROFILING
PREDICTED
CONSUMPTION
PROFILE
HOUSEHOLD and
CONSUMERS’
PSYCHOGRAPHIC DATA
Relevant consumption
determinants subset
BEHAVIORAL MODEL
z
FEATURE EXTRACTION
15. Case Study Application
Source: H2ome smart project (Anda et al., 2013)
Pilbara
Kimberley
3-months resolution
water consumption readings
(Aug 2010 – Feb 2012)
Approx. 730 households
27 user and household features
Dataset
Case study application
16. Dataset
Years of occupancy
House responsibility
# occupants
Resident type
Land use
House type
# toilets
Washing machine type
Toilet type
Shower type
Dishwasher presence
Garden area
Watering method
Watering time
Mulch usage
Native plant presence
Average max temperature
Average min temperature
Average daily precipitation
Pool presence
Pool cover usage
Spa presence
Town
Suburb
Metering period start
Metering period end
Metering period length
Users’ and households’ features
17. USERS PROFILING FEATURE EXTRACTION
Chi-square score
Information Gain
Fast Correlation Based Filter
Correlation Feature Selection
Bayesian Logistic Regression
Sparse Bayesian Multinomial
Logistic Regression
Iterative Input Variable
Selection
Naïve Bayes Classifier
J48 Decision Tree algorithm
Extremely Randomized Trees
BEHAVIORAL MODEL
Cominola et al. (2015), Modelling residential water consumers’ behaviors by feature selection and feature weighting,
In Proceedings of the 36th IAHR world congress
K-means clustering (k=4)
Algorithms
18. USERS PROFILING FEATURE EXTRACTION
Chi-square score
Information Gain
Fast Correlation Based Filter
Correlation Feature Selection
Bayesian Logistic Regression
Sparse Bayesian Multinomial
Logistic Regression
Iterative Input Variable
Selection
Naïve Bayes Classifier
J48 Decision Tree algorithm
Extremely Randomized Trees
BEHAVIORAL MODEL
K-means clustering (k=4)
Algorithms
An evaluation framework for input variable selection algorithms for
environmental data-driven models
Stefano Galelli a, *
, Greer B. Humphrey b
, Holger R. Maier b
, Andrea Castelletti c
,
Graeme C. Dandy b
, Matthew S. Gibbs b, d
a
Pillar of Engineering Systems and Design, Singapore University of Technology and Design, 20 Dover Drive, 138682, Singapore
b
School of Civil, Environmental, and Mining Engineering, University of Adelaide, SA, 5005, Australia
c
Department of Electronics, Information, and Bioengineering, Politecnico di Milano, Piazza L. da Vinci, 32, 20133, Milan, Italy
d
Department of Environment, Water and Natural Resources, GPO Box 2384, Adelaide, SA, 5001, Australia
Contents lists available at ScienceDirect
Environmental Modelling & Software
journal homepage: www.elsevier.com/locate/envsoft
Environmental Modelling & Software 62 (2014) 33e51
http://ivs4em.deib.polimi.it/
20. Relativecontribution
Fscore
ET Largest Class Random
Accuracy 0.75 0.56 0.44
F-score 0.48 0.18 0.25
# users correctly profiled
total # users
True Positive
True Positive + False Negative
True Positive
True Positive + False Positive
Results: behavioral model
21. Take home points
• Smart-meters can improve our understanding of residential water
consumption behaviors at very high spatial and temporal resolution
• Feature extraction algorithms can identify key users’ features
determining the observed water consumption behaviors
• The combination of smart meters and machine learning techniques
has the potential for supporting the development of data-driven
behavioral models
22. LONDON | UK
Thames Water water supply utility
15 million customers served
2.6 Gl/day drinking water distributed
Development plan: 3 Million smart meters installed by 2030
LOCARNO | CH
Società Elettrica Sopracenerina
power supply utility, 80 thousand
customers served
Interested in multi-utility smart metering
(water, energy, gas)
Almost 400 smart water meters installed
VALENCIA | ES
EMIVASA water supply utility
2 million customers served
490,000 water smart meters currently installed
Development plan: 650,000 water smart meters installed by end 2015
Ongoing research
23. _ technological
_ financial
_ legislative
_ operation and maintenance
_ education
CUSTOMIZED DEMAND
MANAGEMENT
CONSUMERS’
COMMUNITY
WATER
CONSUMPTION
MONITORING
BEHAVIORAL USER
MODELLING
_ SMART METERED WATER CONSUMPTION
_ PSYCHOGRAPHIC DATA
_ RESPONSE TO WDMS
Hour the day
0 5 10 15 20 25
Normalizedhouseholdconsumption
0
0.05
0.1
0.15
WATER DATA
END_USE ANALYTICS
47%
12%
9%
8%
23%
HPE
CDE CDE CDE C
HPE HPE Hhighest
contribution
lowest
contribution
garden
shower
toilet
faucet
dishwasher
Ongoing research
24. _ technological
_ financial
_ legislative
_ operation and maintenance
_ education
CUSTOMIZED DEMAND
MANAGEMENT
CONSUMERS’
COMMUNITY
WATER
CONSUMPTION
MONITORING
BEHAVIORAL USER
MODELLING
_ SMART METERED WATER CONSUMPTION
_ PSYCHOGRAPHIC DATA
_ RESPONSE TO WDMS
Ongoing research
CONSUMER PORTAL
ENGAGEMENT AND
BEHAVIOURAL CHANGE