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.
Authors
- Lyamine Guezouli (ORCID: https://orcid.org/0000-0002-7406-7633)
- Lahcene Guezouli (ORCID: https://orcid.org/0000-0001-6489-7222)
- Mohammed Baha Eddine Djeghaba
- Abir Bentahrour
Institutions
- University of Batna 1 (DZ)
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