MUMBAI, India, June 30 -- Intellectual Property India has published a patent application (202641073845 A) filed by Vellore Institute Of Technology on June 15, 2026, for “a Context-Aware Automated Distress Detection System Using Iot And Deep Learning”.
Inventors include Parvathi R; and Ishwarya C.
The application for the patent was published on June 26, 2026, under issue no. 26/2026.
Abstract: The present invention relates to a context-aware automated distress detection system and method that enables reliable emergency recognition with reduced false alarms and improved privacy. The system comprises a physiological sensing module configured to continuously monitor biometric parameters such as heart rate and infrared signal strength to assess user stress conditions, and an acoustic sensing module configured to capture environmental audio signals. An edge processing unit, preferably an ESP32 microcontroller executing a lightweight deep learning model using TensorFlow Lite or TinyML, classifies distress-related vocal patterns including screams or panic sounds. The system operates in a passive monitoring mode where biometric data establishes a real-time baseline, and audio acquisition is activated only when physiological parameters exceed an adaptive stress threshold. A dual-factor distress verification algorithm correlates physiological deviation with acoustic classification confidence within a defined verification window to confirm an emergency event. The invention further includes fail-safe mechanisms based on sound intensity thresholds and automatically transmits emergency alerts with location data to predefined recipients through cloud services or telecommunication gateways, thereby minimizing power consumption, preserving privacy through on -device inference, and ensuring rapid distress response. Fig 1 to 6.
Disclaimer: Curated by HT Syndication.
