Publication

Abstract : Pollution in aquatic environment is an evolving risk in ecosystems since it leads to negative impacts in ecology and contaminates the entire environment. Water get polluted in many forms such as through industries, oil manufacturing companies, domestic sewages or by fertilizers used for agriculture. Such water pollution endangers underwater species and affects the health of human beings. Water play a major role in the transportation of non-degradable wastes to oceans which brings deadly diseases worldwide. Water bodies are facing an uncertain future around the globe. To reduce the risk of water pollution, rigorous monitoring is needed to identify the sources of pollutants. Many existing studies have concentrated on measures to avoid water pollution, but, lacked with effective surveillance systems for capturing the area being polluted. Hence, the proposed work focuses on monitoring from both the upper layer and lower layer of the pond through CCTV and underwater sensors for pollutant detection. CCTV detects for wastes that float on water and sensors predict the underwater wastes. Both forms of collected information are sent to the tower through Wireless Sensor Network (WSN) which reports the condition of pond through mobile devices. The CCTV based detection system uses the YOLO framework for detecting the hotspots for optimal evacuation processes. The proposed framework exhibits its efficiency in the form of accurate monitoring and broadcasting enhanced images or videos when predicted. Thus, the enhanced model designed for identification of plastics, polymers or any other types of wastes on pond reduces water pollution effectively.