IoT based Retrofitting Model for Data-driven Water Flow Monitoring
Abstract: The monitoring of water flow plays a crucial role in detecting leaks and minimizing water wastage, ultimately enhancing the management and conservation of our valuable water resources. Addressing this challenge calls for the development of an efficient and sustainable water management system. We introduce a solution based on the Internet of Things (IoT) that focuses on retrofitting existing analog water meters with readily available off-the-shelf electronic components to make it smart. Real-time data collection and analysis are seamlessly executed through edge computation using Raspberry-Pi. The water meter images are captured by Raspberry-Pi camera and are processed to estimate the meter readings using machine learning (ML) model. To evaluate the developed solution's reliability and performance, extensive field deployments spanning several months are conducted, enabling the characterization of water usage patterns and fault detection across diverse locations. Additionally, the integration of energy harvesting capabilities into the system reduces maintenance costs and promotes eco-friendly energy practices. In summary, this solution presents a comprehensive and effective approach to achieving efficient and sustainable water management.
Video URL: https://shorturl.at/ikyEL
Repository URL: https://iiitaphyd-my.sharepoint.com/:f:/g/personal/nilesh_bawankar_research_iiit_ac_in/EtAE8qVAMJVAhZKJa7TlDFYBkNKNy-58E7Foe9_WivvA5g?e=TKPFBX
Submission Number: 4
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