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 392 المشاهدات 10 الاقتباسات
10
الاقتباسات
392
المشاهدات
الملخص

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.

الاستشهاد بهذا المقال (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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الرقم الدولي ISSN 1112-2242
الربعية Q3
درجة المؤشر القياس العربي 84
التخصص Engineering & Technology
الناشر Renewable Energy Development Center
الدولة 🇩🇿 Algeria
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المؤلفون
تفاصيل النشر
السنة 2024
اللغة English
أُضيف في 01 Aug 2026