MUMBAI, India, Feb. 13 -- Intellectual Property India has published a patent application (202541123941 A) filed by Dr. Kanapathy Gopalakrishnan, Bangalore, Karnataka, on Dec. 9, 2025, for 'system design and method of development of smart pipeline surveillance and leakage detection prediction and prevention using iot and machine learning.'

Inventor(s) include Ajay D M; Charan S; Manjunath V; M. Y. Viswanath Reddy; Yashodhara C L; Dr. Rohith S; and Dr. Venkatesh Kumar H.

The application for the patent was published on Feb. 13, under issue no. 07/2026.

According to the abstract released by the Intellectual Property India: "The patent disclosure covers System, Design and Method of Development of Smart Pipeline Surveillance and Leakage Detection, Prediction and Prevention Using lot and Machine Learning. Water conservation is essential for sustainable development. This design presents a Smart Water Flow and Pipeline Leakage Detection System using loT- bedded technology and Python. The system uses an Arduino Uno as the main regulator, integrating a inflow detector to measure water inflow and a soil humidity detector to descry possible leakage. A DHT11 detector observes temperature and moisture to give environmental data. When leakage is linked, the system automatically turns off the water pump motor using a relay module, precluding farther water loss. Data is reused using Python, and a Random Forest algorithm is used to descry leakage conditions directly. This system offers an effective and cost-effective result for managing water operation and detecting channel faults in agrarian and domestic settings. In this design, we will design and apply the complete system setup by connecting all detectors and modules to the Arduino Uno. The collected data from detectors will be transmitted to a Python- grounded platform for real- time monitoring and analysis. We'll train and test the Random Forest algorithm using the detector data to directly classify normal and leakage conditions. A dashboard will be developed to fantasize live readings similar as inflow rate, temperature, and humidity situations. Finally, we will test the system in both controlled and real-world environments to evaluate its accuracy, reliability, and response time in detecting and managing water leakage."

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