MUMBAI, India, Sept. 22 -- Intellectual Property India has published a patent application (202641108697 A) filed by Pragati Engineering College on September 10, 2026, for An Iot-Based Smart Glove For Real-Time Sign Language Translation With Haptic Feedback..
Inventors include Dr. Kola Satyanarayana; Mr. G. Srinivasa Siva Kumar; Dr. Prasanth Varasala; and Dr. Venkateswarlu Chitteti.
The application for the patent was published on September 18, 2026, under issue no. 38/2026.
Abstract: The present invention relates to a Digital Twin-enabled personal mobility assistance system designed to provide safe, intelligent, and real-time navigation support for visually impaired persons in indoor and outdoor environments. The system integrates a wearable sensing module comprising an RGB camera, depth sensor or LiDAR, ultrasonic or infrared sensors, an Inertial Measurement Unit, GPS/GNSS, microphones, environmental sensors, user-control interfaces, and wireless communication components. Sensor data are processed locally through an Edge AI and multi-sensor fusion module to detect and classify obstacles, estimate distances, recognize landmarks, monitor user movement, identify ground-level and overhead hazards, and understand the surrounding environment. A continuously synchronized Digital Twin creates a virtual representation of the user, current location, walking direction, destination, surrounding objects, available free space, environmental conditions, and route-related risks. The Digital Twin supports predictive hazard analysis by tracking moving vehicles, bicycles, pedestrians, animals, and other dynamic objects and estimating their future trajectories. Based on this virtual model, the system generates a safe walking path and dynamically replans the route when the original path becomes blocked, crowded, unsafe, inaccessible, or affected by temporary hazards. A neuro-symbolic decision engine combines artificial-intelligence outputs with predefined navigation rules, safety constraints, hazard-priority conditions, and user preferences. The engine evaluates obstacle type, distance, direction, movement, and urgency to prioritize critical hazards and suppress unnecessary alerts. Navigation instructions and safety warnings are communicated through multimodal feedback, including voice guidance, bone-conduction audio, directional vibration, and tactile signals. The system supports outdoor positioning through GPS/GNSS and indoor localization through UWB, Bluetooth beacons, Wi-Fi, visual landmarks, or inertial dead reckoning. It also detects emergency conditions such as falls, smoke, fire, harmful gases, waterlogging, prolonged immobility, and user-activated SOS events. During an emergency, the system may transmit the user’s location and hazard information to an authorized caregiver or emergency contact. Edge processing reduces communication delay, supports offline operation, and improves privacy by limiting continuous transmission of sensitive camera, audio, and location data. The invention therefore provides a reliable, adaptive, predictive, privacy-preserving, and user-friendly mobility assistance solution that improves independent navigation, environmental awareness, safety, and confidence for visually impaired persons.
Disclaimer: Curated by HT Syndication.
