Gamified Approaches for Water Management Systems: An Overview

Water demand is growing worldwide, especially in densely populated areas, as a consequence of population growth [1] and urbanization [2]. The spatial concentration of water demand in urban areas is impacting demand magnitude, peak intensity, share between use sectors, and indoor and outdoor usage [3]. This, coupled with climate change and land use change, is intensifying the stress on finite water resources, creating both operational and environmental challenges to water supply. To cope with this evolving context, traditional supply and management schemes need to be adapted to meet future demand whilst preventing unsustainable resources exploitation. In this context, keeping into account geographical constraints and increasing marginal cost often limiting capacity expansion through infrastructural interventions [4], demand-side management strategies are key to complement supply-side interventions for securing reliable water supply as well as reducing shortages and overall utilities’ costs [5]. The potential of demand-side management interventions has been demonstrated in a number of works (see, for a review, [6] and references therein), especially in the last two decades, fostered by the promotion of several water saving programs worldwide, particularly in areas affected by prolonged droughts (e.g., California [7]) or low-recharge periods (e.g., Australia [5]).

[1]  I. Song,et al.  Analytics over large-scale multidimensional data: the big data revolution! , 2011, DOLAP '11.

[2]  P. Mayer Residential End Uses of Water , 1999 .

[3]  John E. Taylor,et al.  Response–relapse patterns of building occupant electricity consumption following exposure to personal, contextualized and occupant peer network utilization data , 2010 .

[4]  Kelly S. Fielding,et al.  Water demand management research: A psychological perspective , 2010 .

[5]  Rodney Anthony Stewart,et al.  Alarming visual display monitors affecting shower end use water and energy conservation in Australian residential households. , 2010 .

[6]  P. Gleick,et al.  Peak water limits to freshwater withdrawal and use , 2010, Proceedings of the National Academy of Sciences.

[7]  Nels Johnson,et al.  Managing Water for People and Nature , 2001, Science.

[8]  Kebreab Ghebremichael,et al.  Integrated Water Resources Management , 2015 .

[9]  Executive Summary World Urbanization Prospects: The 2018 Revision , 2019 .

[10]  Salvador Santonja-Climent,et al.  ICT as an Enabler to Smart Water Management , 2013 .

[11]  P. Fraternali,et al.  Behaviour change and incentive modelling for water saving: first results from the SmartH2O project , 2016 .

[12]  A. Negrușa,et al.  Exploring Gamification Techniques and Applications for Sustainable Tourism , 2015 .

[13]  Rodney Anthony Stewart,et al.  Smart metering: enabler for rapid and effective post meter leakage identification and water loss management , 2013 .

[14]  J. Minx,et al.  Change 2014: Mitigation of Climate Change. Contribution of Working Group III to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change , 2014 .

[15]  Ian Bogost,et al.  Persuasive Games: The Expressive Power of Videogames , 2007 .

[16]  Oded Nov,et al.  The Persuasive Power of Data Visualization , 2014, IEEE Transactions on Visualization and Computer Graphics.

[17]  Rodney Anthony Stewart,et al.  Intelligent Metering for Urban Water Planning and Management , 2013 .

[18]  Christophe Le Page,et al.  Companion modelling approach: the AtollGame experience in Tarawa atoll (RePublic of Kiribati) , 2005 .

[19]  J. Palutikof,et al.  Climate change 2007: Impacts, Adaptation and Vulnerability. Contribution of Working Group II to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change. Summary for Policymakers. , 2007 .

[20]  S. Freitas,et al.  Societal impact of a serious game on raising public awareness: the case of FloodSim , 2009, Sandbox@SIGGRAPH.

[21]  C. Revenga,et al.  Urban growth, climate change, and freshwater availability , 2011, Proceedings of the National Academy of Sciences.

[22]  A. Raftery,et al.  World population stabilization unlikely this century , 2014, Science.

[23]  Rodney Anthony Stewart,et al.  Demand-side management for supply-side efficiency: Modeling tailored strategies for reducing peak residential water demand , 2016 .

[24]  Birgit Mack,et al.  An analysis of smart metering information systems: A psychological model of self-regulated behavioural change , 2015 .

[25]  Peter Morris,et al.  The Effectiveness of Energy Feedback for Conservation and Peak Demand: A Literature Review , 2013 .

[26]  P. Wesley Schultz,et al.  Personalized Normative Feedback and the Moderating Role of Personal Norms , 2016 .

[27]  Muhammad Ali Imran,et al.  Non-Intrusive Load Monitoring Approaches for Disaggregated Energy Sensing: A Survey , 2012, Sensors.

[28]  Fabian Groh Gamification : State of the Art Definition and Utilization , 2012 .

[29]  Houbing Song,et al.  Cyber-physical systems for water sustainability: challenges and opportunities , 2015, IEEE Communications Magazine.

[30]  Gordon B. Davis,et al.  User Acceptance of Information Technology: Toward a Unified View , 2003, MIS Q..

[31]  J. Gardner,et al.  An experimental test of voluntary strategies to promote urban water demand management. , 2013, Journal of environmental management.

[32]  Rodney Anthony Stewart,et al.  End use water consumption in households: impact of socio-demographic , 2013 .

[33]  Jay R. Lund,et al.  Residential water conservation in Australia and California. , 2013 .

[34]  Tad Hirsch,et al.  Water wars: designing a civic game about water scarcity , 2010, Conference on Designing Interactive Systems.

[35]  Juho Hamari,et al.  Does Gamification Work? -- A Literature Review of Empirical Studies on Gamification , 2014, 2014 47th Hawaii International Conference on System Sciences.

[36]  U. Dahlstrand,et al.  Pro-Environmental Habits: Propensity Levels in Behavioral Change1 , 1997 .

[37]  B. J. Fogg,et al.  Persuasive technology: using computers to change what we think and do , 2002, UBIQ.

[38]  Steve M. Easterbrook,et al.  Climate change: a grand software challenge , 2010, FoSER '10.

[39]  Pierre Mukheibir,et al.  Intelligent Metering for Urban Water: A Review , 2013 .

[40]  Lennart E. Nacke,et al.  Gamification : Toward a Definition , 2022 .

[41]  Tyler Pierce,et al.  Serious games on environmental management , 2017 .

[42]  Kelly S. Fielding,et al.  Determinants of household water conservation: The role of demographic, infrastructure, behavior, and psychosocial variables , 2012 .

[43]  Harri Oinas-Kukkonen,et al.  A foundation for the study of behavior change support systems , 2012, Personal and Ubiquitous Computing.

[44]  J. Palutikof,et al.  Climate change 2007 : impacts, adaptation and vulnerability , 2001 .

[45]  Jesse Schell,et al.  The Art of Game Design: A book of lenses , 2019 .

[46]  Andrea Castelletti,et al.  Smart Metering, Water Pricing and Social Media to Stimulate Residential Water Efficiency: Opportunities for the SmartH2O Project , 2014 .

[47]  Dimitris Charitos,et al.  Enhancing citizens'environmental awareness through the use of a mobile and pervasive urban computing system supporting smart transportation , 2014, 2014 International Conference on Interactive Mobile Communication Technologies and Learning (IMCL2014).

[48]  Corinne Le Quéré,et al.  Climate Change 2013: The Physical Science Basis , 2013 .

[49]  Rachel Cardell-Oliver,et al.  Water use signature patterns for analyzing household consumption using medium resolution meter data , 2013 .

[50]  David Wellington Essaw,et al.  Integrated Water Resources Management , 2012, Global Environmental Careers.

[51]  Marco Kalz,et al.  Pervasive Interventions to Increase Pro-environmental Awareness, Consciousness, and Learning at the Workplace , 2013, EC-TEL.

[52]  Zoran Kapelan,et al.  Using Smart Meters for Household Water Consumption Feedback: Knowns and Unknowns☆ , 2014 .

[53]  Andrea Castelletti,et al.  Benefits and challenges of using smart meters for advancing residential water demand modeling and management: A review , 2015, Environ. Model. Softw..

[54]  Eric C. Larson,et al.  The design and evaluation of prototype eco-feedback displays for fixture-level water usage data , 2012, CHI.

[55]  Piero Fraternali,et al.  The SmartH2O project and the role of social computing in promoting efficient residential water use: a first analysis , 2014 .

[56]  Matteo Giuliani,et al.  Profiling residential water users’ routines by eigenbehavior modelling , 2016 .

[57]  Anas A. Makki,et al.  Novel bottom-up urban water demand forecasting model:Revealing the determinants, drivers and predictors of residential indoor end-use consumption , 2015 .

[58]  Xin Li,et al.  Using Social Psychology to Motivate Contributions to Online Communities , 2005, J. Comput. Mediat. Commun..