Felix Fl Lin
ABSTRACT
Having access to sufficient water usage data real-time is crucial not only to finding water leaks and preventing water bills (which can cost up to thousands of dollars) but also to tracking water usage and savings. However, to record a California household's water usage, a worker from the respective water district must personally check the water meter in order to update the data at a monthly frequency. This is because the current water infrastructure in California is outdated while also being expensive to replace. Additionally, while certain cities such as San Jose has Advanced Metering Systems for water installed, due to a lack of budget, it can be difficult for government agencies to develop a solution that can be implemented statewide, then nationwide, in an estimated 2-3 years from now. This paper proposes an IoT-based smart water monitor that utilizes computer vision to record water data, then compares the data's deviance from the predicted usage to check for water leaks. We applied our application to monitoring the water usage of my own household and conducted a qualitative evaluation of the approach. The results show that the water monitor is an effective and affordable way to water management.
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Index Terms
- SmartMeter: An Automatic Water Metering System using Computer Vision and ARIMA-based Machine Learning
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