Turning Smart Water Meter Data Into Useful Information : A case study on rental apartments in Södertälje
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[1] F. E. Grubbs. Procedures for Detecting Outlying Observations in Samples , 1969 .
[2] R. Yin. The abridged version of case study research: Design and method. , 1998 .
[3] Leandros Tassiulas,et al. Exploring Patterns in Water Consumption by Clustering , 2015 .
[4] Yixing Shan,et al. 13th Computer Control for Water Industry Conference, CCWI 2015 Household Water Consumption: Insight from a Survey in Greece and Poland , 2015 .
[5] Luis A. Hernández Gómez,et al. Smart Cities at the Forefront of the Future Internet , 2011, Future Internet Assembly.
[6] Rachel Cardell-Oliver,et al. Smart Meter Analytics to Pinpoint Opportunities for Reducing Household Water Use , 2016 .
[7] Vanessa Speight,et al. Data driven analysis of customer flow meter data , 2015 .
[8] Hector Malano,et al. Seasonal Demand Dynamics of Residential Water End-Uses , 2015 .
[9] Kevin Ashton,et al. That ‘Internet of Things’ Thing , 1999 .
[10] Rodney Anthony Stewart,et al. Development of an intelligent model to categorise residential water end use events , 2013 .
[11] R. Viertl. On the Future of Data Analysis , 2002 .
[12] Gerhard P. Hancke,et al. The Role of Advanced Sensing in Smart Cities , 2012, Sensors.
[13] Shuang-Hua Yang,et al. A Benchmarking Model for Household Water Consumption Based on Adaptive Logic Networks , 2015 .
[14] Ammar Rayes,et al. The Internet of Things (IoT) , 2020, Energy and Analytics.
[15] Rosa Maria Dangelico,et al. Smart cities: definitions, dimensions, and performance , 2013 .
[16] Zoran Kapelan,et al. Effectiveness of Smart Meter-Based Consumption Feedback in Curbing Household Water Use: Knowns and Unknowns , 2016 .
[17] Petra Perner,et al. Data Mining - Concepts and Techniques , 2002, Künstliche Intell..
[18] Pierre Mukheibir,et al. Urban water conservation through customised water and end-use information , 2016 .
[19] Rodney Anthony Stewart,et al. Smart meter enabled informatics for economically efficient diversified water supply infrastructure planning , 2016 .
[20] Moti Nissani. Ten cheers for interdisciplinarity: The case for interdisciplinary knowledge and research , 1997 .
[21] Rodney Anthony Stewart,et al. Identifying Residential Water End Uses Underpinning Peak Day and Peak Hour Demand , 2014 .
[22] Lawrence A. Machi,et al. The literature review : six steps to success , 2009 .
[23] Kelly S. Fielding,et al. An experimental test of voluntary strategies to promote urban water demand management. , 2013, Journal of environmental management.
[24] Ewa Magiera,et al. ISS-EWATUS Decision Support System - Overview of Achievements , 2017, KES-IDT.
[25] Wendy Olsen,et al. Data Collection: Key Debates and Methods in Social Research , 2011 .
[26] V. C. Broto,et al. Practising interdisciplinarity in the interplay between disciplines: experiences of established researchers , 2009 .
[27] Jennifer E. Rowley,et al. The wisdom hierarchy: representations of the DIKW hierarchy , 2007, J. Inf. Sci..
[28] Lida Xu,et al. The internet of things: a survey , 2014, Information Systems Frontiers.
[29] Line Dubé,et al. Rigor in Information Systems Positivist Case Research: Current Practices , 2003, MIS Q..
[30] E. Brynjolfsson,et al. The Rapid Adoption of Data-Driven Decision-Making , 2016 .
[31] Ewa Magiera,et al. Integrated Support System for Efficient Water Usage and Resources Management (ISS-EWATUS) , 2014 .
[32] Wei Liu,et al. An incremental algorithm for discovering routine behaviours from smart meter data , 2016, Knowl. Based Syst..
[33] Pierre Mukheibir,et al. Intelligent Metering for Urban Water: A Review , 2013 .
[34] 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..
[35] Sarah C. Darby,et al. Smart metering: what potential for householder engagement? , 2010 .
[36] Rodney Anthony Stewart,et al. Smart metering: enabler for rapid and effective post meter leakage identification and water loss management , 2013 .
[37] Tan Yigitcanlar,et al. Smartness that matters: towards a comprehensive and human-centred characterisation of smart cities , 2016 .
[38] Gareth R.T. White,et al. Business Information Management: Improving Performance Using Information Systems , 2004 .
[39] Rodney Anthony Stewart,et al. Web-based knowledge management system: linking smart metering to the future of urban water planning , 2010 .
[40] Dan Koo,et al. Towards Sustainable Water Supply: Schematic Development of Big Data Collection Using Internet of Things (IoT) , 2015 .
[41] Geoffrey W. McCarthy,et al. On Being a Scientist: A Guide to Responsible Conduct in Research, 3rd ed. , 2012 .
[42] R. Ackoff. From Data to Wisdom , 2014 .
[43] Michele Ann Mutchek,et al. Moving Towards Sustainable and Resilient Smart Water Grids: Networked Sensing and Control Devices in the Urban Water System , 2014 .
[44] Daniel Pacheco Lacerda,et al. Design Science Research: A Method for Science and Technology Advancement , 2014 .
[45] Jan Adamowski,et al. Urban water demand forecasting and uncertainty assessment using ensemble wavelet‐bootstrap‐neural network models , 2013 .
[46] Melanie Swan,et al. Sensor Mania! The Internet of Things, Wearable Computing, Objective Metrics, and the Quantified Self 2.0 , 2012, J. Sens. Actuator Networks.
[47] Randy Frank. Understanding Smart Sensors, Second Edition , 2000 .