From Data to Action: AI-Powered Smart Water Management in the Balkans

Abstract

Smart water management is turning into one of the key elements for a sustainable water infrastructure in the Balkans. Systems based on collected data can solve major problems, such as leakage, pollution and inefficient water distribution. This paper explores the path from data to action using artificial intelligence and machine learning in regional smart water management projects. In the paper, a comparative analysis of the implementation of smart systems in Bosnia and Herzegovina, Croatia, Serbia and Montenegro was carried out, with a focus on predictive analytics, the application of edge AI technology and real-time decision support systems.This study introduces hybrid technologies that combine IoT with machine learning algorithms such as Random Forest,XGBoost, and Deep Q-Learning with the goal of adaptive water distribution.Results indicate that localized AI models can reduce network losses by up to 30 % and improve anomaly detection accuracy by 25 %. Despite financial and infrastructural limitations, the adoption of AI-powered smart water systems demonstrates a measurable impact on sustainability and operational efficiency. The paper concludes with a roadmap for regional collaboration and the standardization of AI-driven water management practices in the Balkans.