MUMBAI, India, Jan. 9 -- Intellectual Property India has published a patent application (202511112834 A) filed by Sanjog Arora; Akanksha Chaturvedi; Dr. Vivek Bhojak; Dr. Gaurav Kumar Soni; Manish Kumar Jha; and Ravi Joshi, Jaipur, Rajasthan, on Nov. 17, 2025, for 'system and method for driver fatigue and drowsiness detection using in-vehicle iot and deep learning.'
Inventor(s) include Sanjog Arora; Akanksha Chaturvedi; Dr. Vivek Bhojak; Dr. Gaurav Kumar Soni; Manish Kumar Jha; and Ravi Joshi.
The application for the patent was published on Jan. 9, under issue no. 02/2026.
According to the abstract released by the Intellectual Property India: "A system and method for real-time detection of driver fatigue and drowsiness is disclosed, utilizing an in-vehicle Internet of Things (IoT) sensor suite combined with a deep learning model. The system integrates multimodal data streams, including behavioral features (Eye Aspect Ratio, Mouth Aspect Ratio) captured by a near-infrared (NIR) camera, and physiological/environmental features (steering wheel grip pressure, ambient tempera- ture, heart rate variability from contact-less sensor). This data is fed into a fused Con- volutional Neural Network-Recurrent Neural Network (CNN-RNN) architecture, optimized for low-latency edge deployment within an Electronic Control Unit (ECU). The system cal- culates a unified Drowsiness Risk Score (DRS) and triggers multi-tiered alerts (e.g., audi- tory, haptic seat vibration, climate control adjustment) when the score exceeds a dynamic threshold. Furthermore, the system utilizes the IoT connection to transmit high-risk event data and system diagnostics to a cloud-based fleet management platform. The invention provides enhanced accuracy and robustness by fusing diverse data types and leveraging temporal pattern recognition capabilities of the RNN component."
Disclaimer: Curated by HT Syndication.
