Smart Water Systems: IoT Innovations in Sustainable Water and Wastewater Management

Abstract

Rapid population growth and industrial expansion are putting immense pressure on global water resources, making sustainable management a critical challenge. Traditional water quality assessment, which relies on manual sampling and laboratory testing, is often slow, labor-intensive, and fails to provide the real-time data needed to prevent contamination events. This paper presents a comprehensive review of the role of Internet of Things (IoT) innovations in developing smart water and sustainable wastewater management systems. We synthesize recent trends and technological advancements, examining the core components of modern smart water systems. This includes the integration of various sensors (e.g., pH, turbidity, Total Dissolved Solids (TDS), BOD, and COD), data transmission via wireless networks (such as LoRa, NB-IoT, and Wi-Fi), and the utilization of cloud and edge computing for data processing and visualization. Furthermore, this review explores the integration of Artificial Intelligence (AI) and Machine Learning (ML) for predictive analytics and anomaly detection. Key applications are surveyed, including real-time monitoring for municipal supplies, industrial effluent, agricultural irrigation, and smart-metering for consumption analysis. The analysis highlights significant advantages, such as real-time alerts, reduced manual labor, and improved public health. However, the paper also addresses critical challenges, including high initial costs, the need for frequent sensor calibration, and dependencies on stable power and internet connectivity. This review concludes that IoT-based systems are vital tools for achieving efficient water management and supporting global objectives like the UN Sustainable Development Goal 6 (SDG-6).