Smart Environmental Monitoring and Management System for Water Quality Using Web-Based Data Analysis

In India, a large population depends on local water bodies such as ponds for daily use, yet the quality of these small, community-level sources is rarely monitored or made publicly accessible, even though contamination from waste disposal, human and animal faecal matter, plastic pollution, and poor sanitation makes timely monitoring essential for reducing public-health and environmental risks. This paper presents a smart environmental monitoring and management system that combines laboratory-based water quality testing with a web-based data-analysis platform. Twenty water samples were collected from ponds and public sources in Berhampur, Odisha, and analysed for pH, dissolved oxygen, chlorinity, salinity, temperature, hydrogen sulphide (H extsubscript{2}S), and microbial contamination. Each sample was compared against WHO and BIS (IS~10500) drinking-water limits and classified, through a rule-based decision procedure, into Safe, Moderate, or Not Safe categories. All records are stored in a structured database and presented through an interactive dashboard that supports historical comparison and public data contribution. Of the 20 samples, 9 (45%) were classified as Safe, 4 (20%) as Moderate, and 7 (35%) as Not Safe. Samples in the Not Safe category showed the highest average chlorinity, salinity, and H extsubscript{2}S values, confirming that chloride load and bacterial activity were the dominant contamination indicators in the study area. The results show that coupling low-cost laboratory testing with an accessible web platform provides a practical and scalable way to monitor local water bodies, raise community awareness, and build a shared dataset for researchers, students, and local communities, while remaining open to future integration of IoT sensors and machine learning.