MUMBAI, India, Aug. 10 -- Intellectual Property India has published a patent application (202641089772 A) filed by Dr. Anand Konkala, Associate Professor Of Zoology Department Of Zoology, Government City College A.; Rithvik Konkala, Internship Department Of Electronics And Instrumentation, Bits Pilani, Hyderabad.; and Vishwa Teja Konkala, Internship Department Of Ai&ml, Neil Gogte Institute Of Technology. on July 23, 2026, for A System And Method For Continuous Water Quality Monitoring And Pollution Level Prediction.
Inventors include Dr. Anand Konkala, Associate Professor Of Zoology Department Of; Rithvik Konkala, Internship Department Of Electronics And; and Vishwa Teja Konkala, Internship Department Of Ai&ml, Neil Gogte.
The application for the patent was published on July 31, 2026, under issue no. 31/2026.
Abstract: Abstract A system and method for continuous water quality monitoring and pollution level prediction is disclosed, integrating a submersible multi parameter physicochemical sensor probe with an automated bio indicator monitoring chamber that houses sentinel aquatic organisms and computes a real-time Behavioral Activity Index using computer vision based motion tracking, in accordance with established zoological bio monitoring principles. Data from both sub-systems are transmitted via a low power wireless network to a cloud based machine learning prediction engine, which fuses the physicochemical and behavioral data into a composite Pollution Prediction Index and forecasts the Water Quality Index over a twenty four to forty eight hour horizon using a Long Short Term Memory (LSTM) recurrent neural network. When the forecast Water Quality Index is predicted to cross a configurable pollution threshold, the system automatically issues an early warning alert to regulatory, fisheries, and conservation stakeholders. In an illustrative field deployment, the system achieved a prediction root-mean-square error of approximately 3.2 WQI units and forecast threshold crossing pollution events approximately twenty four hours in advance of corresponding actual measured events, while the bio indicator module demonstrated a statistically significant behavioral response to pollutant exposure. The invention provides a scalable, low power, field deployable solution for protecting aquatic biodiversity and supporting fisheries management and environmental regulatory compliance through continuous, biologically validated water quality intelligence.
Disclaimer: Curated by HT Syndication.
