A Real-Time Environmental Pollution Monitoring Framework Using Iot And Remote Sensing Technologies

Abstract

Environmental pollution is a significant global issue that affects both human health and the environment. Traditional methods of monitoring environmental pollutants often suffer from limitations such as high costs, slow data collection, and lack of real-time analysis. The integration of Internet of Things (IoT) and remote sensing technologies presents an opportunity to address these challenges, enabling real-time monitoring of environmental pollution. This paper proposes a framework that combines IoT sensor networks and remote sensing techniques to develop an effective system for continuous environmental pollution monitoring. The IoT sensor network gathers data related to air quality, water quality, temperature, humidity, and other environmental factors, while remote sensing technologies, including satellite imagery and drone-based sensors, complement the ground-based data by providing spatially extensive information. The proposed framework utilizes advanced data processing algorithms to fuse and analyze the collected data in real-time, enabling accurate and timely insights into pollution levels. This system offers significant improvements over traditional monitoring approaches by providing real-time, high-resolution data, which can be utilized for better decision-making in environmental management and policy formulation. Results from the implementation of the proposed framework demonstrate its effectiveness in accurately monitoring pollution levels and provide valuable insights into future research and development directions in environmental monitoring technologies.