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

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.

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Publication Details

Journal
Journal of Renewable Energies
Published
2024-12-25
DOI
https://doi.org/10.54966/jreen.v27i2.1210
Citations
6
Primary Topic
Water Quality Monitoring Technologies
Type
article
Field-Weighted Citation Impact
1.21
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article

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

Lyamine Guezouli, Lahcene Guezouli, Mohammed Baha Eddine Djeghaba, Abir Bentahrour
6 citations
Journal of Renewable Energies
Water Quality Monitoring Technologies
1.21
article

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

Lyamine Guezouli, Lahcene Guezouli, Mohammed Baha Eddine Djeghaba, Abir Bentahrour
article en
6 citations

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.

Journal of Renewable EnergiesVol. 27(2)
University of Batna 1 (DZ)
Zero hunger
Openalex Percentile: Top 22%
Water Quality Monitoring Technologies
1.21
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IoT and AI for Real-time Water Monitoring and Leak Detection — Lyamine Guezouli, Lahcene Guezouli, et al. · Journal of Renewable Energies (2024) | TGRS Research Map | TGRS