Framework for Remote Device Localization and Application Level Visualization for Emergency Service Providers
Ayan Kumar Panja, Dhritesh Bhagat, Sarmistha Neogy, Chandreyee Chowdhury · 2022
During a crisis event, remote monitoring of the floor plan, devices, and crowd in an indoor public space is essential. To tackle such a situation it is imminent for the emergency service providers or the organization to gain real-time information of the floor map and the position(s) of the crowd affected by the crisis. In this paper, we intend to provide a framework for supporting smart emergency management for indoor space that constitutes of two parts- (i) remotely localizing the crowd on a near real-time basis and (ii) disseminating this information in a navigation-friendly manner to the emergency responders. A machine learning-based model trained on gathered WiFi Received Signal Strength(RSS) forms the basis of the positioning mechanism opted for our approach. A 3D visualization on a Virtual Reality(VR) platform is amalgamated at the application level to map the actual physical location(s) of the crowd to the virtual coordinate that will be displayed to the emergency responders.