Vehicle logistics, ride-hailing services, quick commerce and emergency responders heavily rely on smartphone-based navigation apps (like Google Maps or MapmyIndia) powered by GNSS (GPS/Galileo/NavIC etc). However, when a vehicle enters a long underground tunnel/ underpass, a multi-level parking lot, a dense forested highway, or a deep urban canyon surrounded by skyscrapers, GNSS connectivity drops entirely. GNSS signals are inherently weak and vulnerable to structural blockage (urban canyons, de
The goal is to develop a lightweight, edge-deployable software engine and mobile application that transforms a standalone smartphone into an Intelligent Dead Reckoning (IDR) system with GNSS Fusion.
Vehicle logistics, ride-hailing services, quick commerce and emergency responders heavily rely on smartphone-based navigation apps (like Google Maps or MapmyIndia) powered by GNSS... However, when a vehicle enters a long underground tunnel/ underpass, a multi-level parking lot, a dense forested highway, or a deep urban canyon surrounded by skyscrapers, GNSS connectivity drops... GNSS signals are inherently weak and vulnerable to structural blockage (urban canyons, de
The goal is to develop a lightweight, edge-deployable software engine and mobile application that transforms a standalone smartphone into an Intelligent Dead Reckoning (IDR) system with GNSS Fusion. When a GNSS outage occurs, the application must instantly transition to inertial tracking(INS), maintaining lane-level accuracy without requiring any physical connection to the vehicle’s internal computer and seamlessly switch back to GNSS aided INS solution. To bypass the need for an external speedometer, the solution must employ AI/ML models trained on vehicle kinematics to accurately predict vehicle speed and acceleration profiles solely from the smartphone’s noisy accelerometer/gyro inputs. It must dynamically detect and filter out non-navigation motions such as engine idling vibrations, po