Maulesh Tejas Gandhi supervised by Dr. Sachin Chaudhari  received his Master of Science – Dual Degree  in Electronics and Communication Engineering (ECD). Here’s a summary of his research work on IoT and ML Based Water Flow Estimation Using Low-Cost Pressure Sensors: 

This thesis presents a scalable and cost-effective approach to water flow monitoring using low-cost pressure sensors, Internet of Things (IoT) systems, and Machine Learning (ML) techniques. Through real-world deployment at the IIIT-Hyderabad campus and controlled laboratory experiments, the study demonstrates that pressure data alone can accurately estimate water flow without the need for expensive flow meters. Multiple ML models were evaluated, with Convolutional Neural Networks and ensemble methods achieving high prediction accuracy. The research also showed that low-cost sensors can perform comparably to higher-end alternatives when combined with suitable ML algorithms. The proposed framework offers a practical solution for smart water management, leak detection, and sustainable resource monitoring in residential, industrial, and smart-city applications.

May 2026