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Reducing city household water consumption with internet of things devices

Author

Listed:
  • Ioan Florin VOICU

    (ING Tech, Bucharest, Romania)

  • Daniel Constantin DIACONU

    (Faculty of Geography, University of Bucharest, Bucharest, Romania)

Abstract

This research aims to prove that inexpensive Internet of Things devices can be used to monitor domestic water consumption, thus lowering water usage, educating consumers about better water habits and preventing or detecting leaks. Such devices can also expose their information to the local water utility company, which can then use these data points in their decision-making. This paper is built on direct experience and research with Home Assistant, a free and open-source Internet of Things device management system, which allows for detailed statistics to be compiled at database level about water consumption, including the effects of optimizing daily usage. The main method employed was a case study comparing household water consumption before and after sensors and valves were implemented, with 4 stages: 1 - no sensor info, 2 - with sensors but no changes made to habits, 3 - sensor info analysis, 4 - changes made to habits based on the previous analysis, 5 - before/after result comparison. Key results included: 20% water consumption reduction after daily habit changes; broken pipe smartphone notification while residents were away, alongside automatic water closure to the household; detection of leaks which were too small to be visible at water meter level, but nevertheless existed. Implications of the study for smart city practitioners are that even inexpensive water sensors and valves can significantly reduce water usage and prevent incidents, quickly paying for themselves and allowing for a more sustainable level of water consumption at city level. The value of this paper is that it shows how a combination of off-the-shelf sensors and valves and free software can be used at household or even city level to bring intelligent water management to communities which might be suffering from the effects of climate change or other causes of water scarcity.

Suggested Citation

  • Ioan Florin VOICU & Daniel Constantin DIACONU, 2021. "Reducing city household water consumption with internet of things devices," Smart Cities International Conference (SCIC) Proceedings, Smart-EDU Hub, Faculty of Public Administration, National University of Political Studies & Public Administration, vol. 9, pages 367-377, November.
    • Handle: RePEc:pop:procee:v:9:y:2021:p:367-377
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    References listed on IDEAS

    as
    1. Sou-Sen Leu & Quang-Nha Bui, 2016. "Leak Prediction Model for Water Distribution Networks Created Using a Bayesian Network Learning Approach," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 30(8), pages 2719-2733, June.
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    More about this item

    Keywords

    IoT; Water Management; Home Assistant;
    All these keywords.

    JEL classification:

    • O35 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Social Innovation

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