Solar-Powered Smart Water Leakage Detection System Using Artificial Intelligence

Hemalatha Balakrishnan , Kiruthika A , Narmatha M , Priyadarshini S , Varshini A

Artificial Intelligence, ESP 32 microcontroller, Solar Powered, Sun tracking, Water Leakage Detection

Water leakage in pipeline systems causes significant water wastage, infrastructure damage, and financial losses across residential, industrial, and agricultural sectors. Conventional leakage detection methods rely on manual inspection and periodic monitoring, making them time-consuming and prone to delayed fault identification. This project presents a solar-powered AI-driven water leakage detection system for real-time pipeline monitoring and abnormality classification. The system employs ultrasonic, sound, and MPU6050 vibration sensors to continuously monitor pipeline conditions. Sensor data are acquired through an ESP32 microcontroller and transmitted for Artificial Intelligence-based analysis. The AI model classifies pipeline conditions as normal or abnormal and generates alerts when leakage is detected. The integration of solar power with a sun-tracking mechanism ensures reliable operation in remote and off-grid locations. The proposed system offers an energy-efficient, sustainable, intelligent, and cost-effective solution for smart water management and predictive maintenance.

Published Paper   E-Certificate

"Solar-Powered Smart Water Leakage Detection System Using Artificial Intelligence", JETNR - JOURNAL OF EMERGING TRENDS AND NOVEL RESEARCH (www.JETNR.org), ISSN:2984-9276, Vol.4, Issue 6, page no.a761-a763, June-2026, Available :https://rjpn.org/JETNR/papers/JETNR2606101.pdf

Volume 4 Issue 6, June-2026

Pages : a761-a763

Paper Reg. ID: JETNR_235067

Published Paper Id: JETNR2606101

Downloads: 000105

Research Area: Science and Technology

Country: Trichy, Tamil Nadu, India

Published Paper PDF: https://rjpn.org/JETNR/papers/JETNR2606101

Published Paper URL: https://rjpn.org/JETNR/viewpaperforall?paper=JETNR2606101

DOI: https://doi.org/10.56975/jetnr.v4i6.235067

ISSN: 2984-9276 | IMPACT FACTOR: 9.87 Calculated By Google Scholar | ESTD YEAR: 2023

An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 9.87 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator

Publisher: RJPN (IJPublication) Janvi Wave

This work is licensed under a Creative Commons Attribution 4.0 International License and The Open Definition