Integrating Edge Computing And Iot For Real-Time Air And Water Quality Monitoring Systems

Abstract

The continuous deterioration of air and water quality worldwide poses severe threats to human health, biodiversity, and environmental sustainability. Rapid urbanization, industrial activities, and increasing vehicular emissions have escalated pollution levels, especially in developing nations like India. Traditional centralized environmental monitoring systems are often inefficient due to high data transmission delays, network congestion, and limited scalability, making them inadequate for real-time monitoring and response. The integration of Edge Computing and Internet of Things (IoT) technologies provides an innovative framework to overcome these challenges. Edge devices enable local data processing near IoT sensors, minimizing latency, reducing bandwidth usage, and ensuring timely and efficient monitoring outcomes. This paper reviews the integration of Edge Computing and IoT for real-time air and water quality monitoring systems, highlighting their architecture, implementation strategies, benefits, challenges, and future directions.We present recent real-time data from major Indian cities showing Delhi’s Air Quality Index (AQI) at 245, significantly exceeding safe levels, and Kolkata’s Water Quality Index (WQI) at 50, indicating poor water conditions. The paper includes system architecture diagrams, comparative data tables, and graphical representations to provide a comprehensive understanding of these systems. Key challenges such as energy efficiency, device interoperability, data security, and scalability are analyzed, and solutions like federated learning and blockchain integration are explored. Future research opportunities in predictive environmental analytics and citizen-centric monitoring are identified. This review aims to assist researchers, environmental policymakers, and smart city developers in designing resilient, scalable, and real-time environmental monitoring systems leveraging edge–IoT synergies.