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.

Victor Huilca Cabay, Alexandra Flores, Paul Hernan Machado Herrera and Byron Paul Huera Paltan, “Smart Insoles for Multi-User Monitoring: A Case Study on Received Signal Strength Indicator-Based Distance Measurement” International Journal of Advanced Computer Science and Applications(IJACSA), 16(3), 2025. http://dx.doi.org/10.14569/IJACSA.2025.0160306

@article{Cabay2025,
title = {Smart Insoles for Multi-User Monitoring: A Case Study on Received Signal Strength Indicator-Based Distance Measurement},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2025.0160306},
url = {http://dx.doi.org/10.14569/IJACSA.2025.0160306},
year = {2025},
publisher = {The Science and Information Organization},
volume = {16},
number = {3},
author = {Victor Huilca Cabay and Alexandra Flores and Paul Hernan Machado Herrera and Byron Paul Huera Paltan}
}