MUMBAI, India, Sept. 7 -- Intellectual Property India has published a patent application (202641104098 A) filed by Aditya Institute Of Technology And Managementautonomous on August 28, 2026, for An Intelligent Black Box For Vehicle Monitoring System With Ai Technology.
Inventors include Dr. K. Seetha Ram; Sri T. Sviswanadham; Dr. P. Eswara Satyanarayana; and Dr. P. Mallikharjuna Rao.
The application for the patent was published on September 04, 2026, under issue no. 36/2026.
Abstract: ABSTRACT OF THE INVENTION: AN INTELLIGENT BLACK BOX FOR VEHICLE MONITORING SYSTEM WITH AI TECHNOLOGY The present invention provides an intelligent black box system for vehicle monitoring incorporating Artificial Intelligence (AI) technology for real-time collision prediction, forensic data persistence, and emergency response. The system comprises a plurality of vehicle sensors generating continuous sensor data, a cyclic buffer for temporary data storage, and an AI processor executing a trained machine learning model to detect impending collisions and relevant events. Upon detection of an imminent event, the black box controller triggers data persistence by copying the cyclic buffer contents to non-volatile storage, ensuring preservation of critical pre-event data that conventional black boxes would otherwise overwrite. The system achieves collision detection accuracy exceeding 98%, false event suppression greater than 95%, and forensic data integrity of 99.97% under high-impact conditions. The intelligent black box integrates multi-sensor data including cameras, radar, lidar, GPS, inertial sensors, and vehicle operation parameters, providing comprehensive vehicle monitoring. The AI processor performs on-device neural network inference with latency of less than 12 milliseconds, enabling real-time event classification and collision prediction. Upon collision confirmation, the system automatically generates emergency alerts with precise geolocation and vehicle data, transmitting to emergency services within 214 milliseconds. Unlike conventional black boxes that operate with static configurations and limited recording windows, the present invention proactively preserves data when a collision is predicted, ensuring complete forensic evidence for post-incident analysis, insurance evaluation, and legal proceedings. The system is designed for OEM-independent retrofit installation, making advanced safety technology accessible to a wide range of vehicles. The machine learning model is trained using supervised learning on historical vehicle data and can be periodically optimized based on real-world performance feedback to minimize false positives and false negatives. Non-volatile storage utilizing cross point memory technology ensures data retention without power for extended periods, maintaining forensic integrity under severe impact conditions
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