Smart Insoles for Multi-User Monitoring: A Case Study on Received Signal Strength Indicator-Based Distance Measurement

Abstract

In the current context of high adoption of wearables and Internet of Things (IoT) devices, this work develops a smart insole system to measure the distance between users using the RSSI signal (Received Signal Strength Indicator). ESP32 WROOM microcontrollers with Bluetooth Low Energy, Wi-Fi, and multiple functionalities were used. The prototype includes sensors to count steps, detect activity (walking/running) and a configurable alarm to alert when the distance is less than a threshold. Collected data are sent directly and in real-time to a database using the ThingSpeak web platform, which allows to visualize the data acquired from the insole sensors. Using the RSSI signal provided by the Bluetooth LE module, a significant response was interpreted and modeled using a multilayer perceptron (MLP) neural network, achieving an average distance estimation accuracy of 90.89% using data measured in real time.