MUMBAI, India, Feb. 6 -- Intellectual Property India has published a patent application (202541122515 A) filed by New Prince Shri Bhavani College Of Engineering And Technology; Mr. Vishal. M; Mr. Jeswanth. P; Mr. Reepath. M; Mr. Aravindh. M; and Mrs. Suganya. M, Chennai, Tamil Nadu, on Dec. 5, 2025, for 'integrated iot & ai system for ganga river monitoring.'
Inventor(s) include Mr. Vishal. M; Mr. Jeswanth. P; Mr. Reepath. M; Mr. Aravindh. M; and Mrs. Suganya. M.
The application for the patent was published on Feb. 6, under issue no. 06/2026.
According to the abstract released by the Intellectual Property India: "The Ganga River, one of the most sacred and ecologically vital rivers in India, is under severe environmental stress due to industrial discharge, untreated domestic sewage, agricultural runoff, and the growing menace of plastic waste. These pollutants degrade aquatic ecosystems, reduce water quality, and pose significant risks to human health and livelihood. Conventional monitoring approaches are often expensive, manual, and limited in scope, making them unsuitable for large-scale and real-time deployment. To address these challenges, this project introduces an Integrated loT and AI System for Ganga River Monitoring, a low-cost, scalable, and intelligent solution designed for continuous pollution detection, plastic waste identification, and automated alert generation. The proposed system combines IoT-ena~led sensors with artificial intelligence to provide a holistic monitoring framework. Key water. quality parameter pH, turbidity, and Total Dissolved Solids are measured using sensors interfaced with an Arduino Uno microcontroller. The collected data is displayed ori a 16x2 LCD module for local access and analyzed in real time to detect anomalies. When unsafe thresholds are reached, an alert mechanism is activated: a buzzer generates immediate local . warnings, Bluetooth~based voice notifications update nearby users, and a GSM module sends SMS alerts to. concerned authorities and stakeholders. This ensures rapid awareness and tiinely interventifn. To extend beyon~ sensor-based analysis, the system integrates,a camera module linked with MATLAB-based image processing. Using AI-drivcn machine vision techniques such as edge detection, contour recognition, and color segmentation, the system identifies floating plastic pollutants on the river's surface. This dual approach quantitative sensor analysis. and qualitative image recognition provides a more comprehensive assessmentofriverhealth. Data collected can further be uploaded to cloud storage, enabling long-term trend analysis, AI based prediction of pollution patterns, and policymaking support. The system design emphasizes affordability, portability, and robustness."
Disclaimer: Curated by HT Syndication.
