Water monitoring

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• Published Subscription Original Research 7 Feb 2026

  Investigation of Pollution Status in River No. 2, Freetown, Sierra Leone, Using Physicochemical and Bacterial Indicators

  By Yahaya Kudush Kawa, Gibrilla Thullah, Sam Sonny Tommy, Victoria Olufemi Danke Kawa

  Abstract: This study assessed the physicochemical and bacteriological quality of surface water in the River No. 2 watershed, Sierra Leone, through monthly sampling from March–August 2024 at upstream, midstream, and downstream sites. Analyses included temperature, turbidity, pH, electrical conductivity, total dissolved solids, ammonia, fluoride, sulfite, nitrate, lead, arsenic, chromium, and microbial indicators (Escherichia coli, fecal and non-fecal coliforms). Most physicochemical parameters met WHO drinking-water guidelines. pH (7.0–7.3), TDS (7–17 mg/L), turbidity …

  Published in International Journal of Pollution: Prevention & Control · Vol. 4, Issue 1, 2026 · pp. 11–27 Read article →

• Published Subscription Review Article 16 May 2025

  Tank Water Quality Analysis Using Machine Learning

  By Sanika D. Gaikwad, Sakshi A. Chavan, Mayuri V. Jadhav, Rutuja K. Shinde, A.C. Jadhav

  Abstract: Tank Water quality is a critical factor for public health, agriculture, as well as industry. Continuous monitoring of tank water quality: temperature, humidity, water level, CO2 concentration, and pH, is vital for safe usage. Using machine learning, real-time data analysis can detect anomalies, predict issues, and optimize water management, ensuring timely responses and improved safety. This intelligent approach enhances decision-making and maintains water quality effectively in various environments.We develop an …

  Published in Journal of Control & Instrumentation · Vol. 16, Issue 2, 2025 · pp. 27–34 Read article →