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Q3 2024

IoT and AI for Real-time Water Monitoring and Leak Detection

Lahcene Guezouli · Lyamine Guezouli · Mohammed Baha Eddine Djeghaba · Abir Bentahrour
10.54966/jreen.v27i2.1210 391 Views 10 Citations
10
Citations
391
Views
Abstract

Water is essential for ecological sustainability and human survival, necessitating effective management to meet rising global demands and address climate change. Traditional water supply monitoring methods are labor-intensive and slow, limiting real-time data acquisition and issue resolution. This paper presents QoW-Pro, an IoT-based water monitoring system that leverages AI algorithms to significantly enhance water quality assessments and leak detection. QoW-Pro enables real-time data collection, predictive modeling, and anomaly detection, leading to improved decision-making in water resource management. The system demonstrates quantitative improvements in leak detection accuracy and water quality prediction, offering a scalable solution adaptable to both urban and agricultural settings. By combining IoT and AI, this research contributes to the sustainable management of water resources, ensuring their availability and quality for future generations.

Cite this Article (APA)
Lahcene, G., Lyamine, G., Mohammed, B. E. D., Abir, B. (2024). IoT and AI for Real-time Water Monitoring and Leak Detection. Journal of Renewable Energies. https://doi.org/10.54966/jreen.v27i2.1210
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Published in
ISSN 1112-2242
Quartile Q3
AMS Score 84
Field Engineering & Technology
Publisher Renewable Energy Development Center
Country 🇩🇿 Algeria
View Journal Profile →
Authors
Publication Details
Year 2024
Language English
Added 01 Aug 2026