MUMBAI, India, May 1 -- Intellectual Property India has published a patent application (202641026497 A) filed by Sri Sai Ram Engineering College, Chennai, Tamil Nadu, on March 6, for 'machine learning-based predictive system for aquatic ecosystem, health monitoring and pollution detection.'
Inventor(s) include Rakshitha V; Srilakshmi P T; Varshini R; Dr. C. N. Savithri; R. Chttra; and M. Suganya.
The application for the patent was published on May 1, under issue no. 18/2026.
According to the abstract released by the Intellectual Property India: "A machine learning-based predictive system for aquatic ecosystem health monitoring and pollution detection comprises floating loT sensor nodes deployed in freshwater lakes, rivers, ponds and marine areas, and a shore-based analytics station. Each sensor node equipped with ESP32 microcontroller measures pH, temperature, dissolved oxygen, turbidity, phenol, conductivity, microplastics and dyes every five minutes, transmitting data via LoRa and GSM networks. The shore-based station computes Composite Aquatic Health Index (CAHI=E(WiXSi)), Fish Survival Index (FSI=(DO x 0.5)+(T emp x 0*.2)+(Toxicity x 0.3)) and Aquatic Ecosystem Health Index (AEHI) from sensor data. Random Forest classifier determines ecosystem state while LSTM model forecasts future conditions. Hybrid anomaly detection using isolation forest, autoencoder and LSTM identifies pollution events. Critical indices or anomalies trigger SMS and mobile app alerts. Web dashboard provides real-time visualisation, predictions and regulatory compliance reports, enabling proactive aquatic ecosystem management."
Disclaimer: Curated by HT Syndication.
