استخدام تطبيقات الذكاء الاصطناعي في ترشيد استهلاك المياه دراسة تطبيقية على نماذج مفتوحة المصدر

Abstract

Water resources management faces increasing global challenges, exacerbated by population growth, climate change, and urban expansion, which impose unprecedented pressure on freshwater supplies. In this context, artificial intelligence emerges as a pivotal tool capable of fundamentally transforming water management practices. This study aims to explore and analyze the role of machine learning applications, a branch of artificial intelligence, in enhancing the efficiency of water resources management and promoting sustainable consumption.

The research adopts a mixed-methods approach, combining a descriptive-analytical review of recent scientific literature with an experimental simulation-based methodology. Due to the difficulty of obtaining precise field data, a practical study was designed using synthetic data to simulate two main scenarios: detecting water leaks in distribution networks using the Isolation Forest model, and forecasting future water consumption using the Prophet time series model.

The scientific contribution of this study lies in providing a practical framework for utilizing open-source machine learning models as cost-effective and efficient solutions, particularly in developing countries facing data scarcity. The results demonstrate the effectiveness of the applied models in accurately identifying anomalies (leaks) and predicting consumption patterns reasonably, highlighting the significant potential of artificial intelligence to support informed decision-making and achieve sustainable water management. This aligns with the United Nations Sustainable Development Goals, particularly Goal 6, which focuses on clean water and sanitation.