Intellectual Property India Publishes Patent Application for 'Iot-Based Integrated Home Security System With Predictive Threat Detection And Method Thereof' Filed by Dr. Venkateswaran Radhakrishnan; Dr. A. T. Ravi; Nendragamti Pavan Kumar; Seena Thomas; Dr. Rahul Lahkar; Anitha R; Dr. A. Backia Abinaya; and Dr. R. Priya

MUMBAI, India, Jan. 2 -- Intellectual Property India has published a patent application (202511103009 A) filed by Dr. Venkateswaran Radhakrishnan; Dr. A. T. Ravi; Nendragamti Pavan Kumar; Seena Thomas; Dr. Rahul Lahkar; Anitha R; Dr. A. Backia Abinaya; and Dr. R. Priya, Salalah, Oman, on Oct. 25, 2025, for 'iot-based integrated home security system with predictive threat detection and method thereof.'

Inventor(s) include Dr. Venkateswaran Radhakrishnan; Dr. A. T. Ravi; Nendragamti Pavan Kumar; Seena Thomas; Dr. Rahul Lahkar; Anitha R; Dr. A. Backia Abinaya; and Dr. R. Priya.

The application for the patent was published on Dec. 12, under issue no. 50/2025.

According to the abstract released by the Intellectual Property India: "The present invention relates to an IoT-based integrated home security system with predictive threat detection and a method thereof, designed to provide proactive monitoring, intelligent analysis, and autonomous protection within residential environments. The system comprises a network of distributed sensing units configured to detect motion, vibration, acoustic disturbances, magnetic changes, and environmental conditions. The collected data is processed by a central processing unit that executes feature extraction, temporal synchronization, and data fusion to form a unified telemetry stream. A predictive analytics unit employing artificial intelligence techniques, such as recurrent neural networks and Bayesian inference models, analyzes these data streams to identify deviations from normal behavior patterns and compute probabilistic threat likelihoods. Based on these predictions, a control unit autonomously initiates countermeasures such as activating alarms, locking entry points, triggering surveillance recording, and dispatching encrypted alerts to user devices and emergency contacts. The invention further includes adaptive learning mechanisms that continuously refine model accuracy using post-event feedback and blockchain-secured logging for forensic data integrity."

Disclaimer: Curated by HT Syndication.