MUMBAI, India, May 1 -- Intellectual Property India has published a patent application (202641049800 A) filed by ViniBrawn Healthcare Solutions (OPC) Private Limited; and Bml Munjal University, Bangalore, Karnataka, on April 19, for 'a smart safety eyewear system with integrated ble-based proximity anti-theft detection, gesture-activated emergency sos with automatic audio and snapshot capture, imu-based automatic fall detection, and dual mobile application ecosystem for personal safety and elderly care.'
Inventor(s) include Dr. Nirupama M. P; Mr. Kanishk Gupta; Mr. Anurag Kumar; Mr. Raghav Khandelwal; and Mr. Shreshth Mittal.
The application for the patent was published on May 1, under issue no. 18/2026.
According to the abstract released by the Intellectual Property India: "Eyeconic - A Smart Safety Eyewear System with Integrated BLE-Based Proximity Anti-Theft Detection, Gesture-Activated Emergency SOS with Automatic Audio and Snapshot Capture, IMU-Based Automatic Fall Detection, and Dual Mobile Application Ecosystem for Personal Safety and Elderly Care Eyeconic (100) is a smart safety eyewear system developed at BML Munjal University, Gurgaon by Dr. Nirupama M.P. (mentor), Mr. Kanishk Gupta (lead inventor), Mr. Anurag Kumar, Mr. Raghav Khandelwal, and Mr. Shreshth Mittal. The system exploits the high wear-compliance of conventional spectacles as a personal safety platform. The smart glasses hardware (200) integrates an ESP32-WROOM MCU (210), MPU6050 six-axis IMU (220), INMP441 I2S microphone (230), ESP32-CAM module (240), capacitive touch sensor (250), ERM haptic motor (260), and a temple-hinge conductive power switch (340) that automatically powers the device on when worn and off when folded. An ESP32 firmware layer (300) implements four concurrent engines: a BLE RSSI proximity anti-theft engine (310) that triggers haptic alarm and overrides the smartphone silent mode when phone separation is detected; a gesture recognition engine (320) activating SOS on configured touch patterns; a three-stage IMU fall detection algorithm (330) with post-impact stillness confirmation; and a Wi-Fi exit auto-protection module (345). Upon any SOS activation, the system automatically records a 30-second ambient audio clip, captures environmental snapshots, acquires GPS coordinates, and uploads the complete evidence package to the cloud platform (510-560). An Eyeconic Core App (400) manages device configuration and anti-theft alarms; an Eyeconic Family App (500) delivers emergency notifications with live location, AI-transcribed audio, and snapshots to family members and caregivers. A fully functional prototype was built and validated at the IoT Lab, BML Munjal University between August and November 2025."
Disclaimer: Curated by HT Syndication.
