An Efficient Path Recognition Multi-Layered framework for Healthcare Critical Application

In this work, multi layered structure is developed for effectively providing the path to the ambulance in the emergency situation. The Internet of Things(IoT) devices and edge devices are viewed as moving agents over the lane network. Due to the agents' and clients' mobility, processing input data gathered via IoT devices and sensors and delivering findings to client mobile devices becomes difficult. A simulation framework for clod/fog/edge is suggested in order to deliver higher Quality of Service(QoS) to reach the hospital. Road Side Unit(RSU) access points are placed over lane network. The coordinates of the objects on the trajectory are used to discover patterns in trajectory databases. According to color Red/Dark or Green/Grey representation given by the closer RSU, clustering facilitates quick access to reach the destination in a timely manner. Disassociation connection is a very difficult problem that arises during data retrieval and computation offloading in any mobile network and also linked vehicle's mobility is always changing, recognition of agents location is a significant task in a real-time healthcare environment. The proposed simulation framework is evaluated on MatLab by simulating a Vehicular ad hoc networks(VANET) communication. According to the lane network of RSU coverage, simulation results demonstrate that proposed method reduces the network congestion and latency than the existing mobility-aware task delegation system.