Indoor Positioning Design Based on HCC in the Background of Mobile Edge ComputingIndoor Positioning Design Based on HCC in the Background of Mobile Edge Computing

Abstract

In the subject of human-centered computing (HCC), achieving accurate location in an indoor setting is a crucial research problem and a hotspot for research. In comparison to WiFi, GPS, and Bluetooth location technologies, the radio frequency identification (RFID) technology obviously has benefits. However, the fixed path loss coefficient in the indoor positioning algorithm based on RFID cannot accurately reflect the complex and mutable properties of inside settings, leading to significant indoor positioning mistakes and sluggish speeds. This research suggests an indoor positioning system based on Edge Computing (EC) to improve the precision and responsiveness of indoor positioning. First, the indoor signal strength is calculated using RFID. Next, the output is sent to a neural network, which outputs the path loss coefficient. Finally, the EC is used to create a more effective indoor positioning system design. According to experiments, the suggested method can more correctly reflect inside environment signal changes and increase indoor location accuracy. This solution effectively satisfies the requirements for indoor real-time positioning even after being deployed to EC.