Real-Time Water Quality Monitoring Using Computer Vision Technology

Abstract Water quality observation is essential for human health and environmental protection. Traditional methods, such as chemical testing, are slow, expensive, and labour-intensive. This research explores the use of computer vision technology for real-time, automated water quality assessment. By analyzing images of water bodies, computer vision algorithms can detect key water quality parameters such as clarity, turbidity, and contamination levels. The proposed system offers a faster, more efficient, and cost-effective alternative to conventional methods. It uses image processing techniques to evaluate water quality from still images captured in different environmental conditions. This study demonstrates that computer vision can provide accurate, real-time analysis of water quality, making it a scalable solution for continuous monitoring. The system can be deployed across various water bodies, ensuring better, more responsive management of water resources and improving overall environmental monitoring practices