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

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.

Authors

Publication Details

Journal
International Journal of Advanced Computer Science and Applications
Published
2025-01-01
DOI
https://doi.org/10.14569/ijacsa.2025.0160306
Primary Topic
Industrial Vision Systems and Defect Detection
Type
article
Field-Weighted Citation Impact
0.00

Funders

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article

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

Alexandra Flores, Byron Paúl Huera Paltán, Paúl Hernán Machado Herrera, Victor Huilca Cabay
International Journal of Advanced Computer Science and Applications
Industrial Vision Systems and Defect Detection
article

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

Alexandra Flores, Byron Paúl Huera Paltán, Paúl Hernán Machado Herrera, Victor Huilca Cabay
article en

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.

International Journal of Advanced Computer Science and ApplicationsVol. 16(3)
Escuela Superior Politécnica de Chimborazo
Openalex Percentile: Top 92%
Industrial Vision Systems and Defect Detection
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Smart Insoles for Multi-User Monitoring: A Case Study on Received Signal Strength Indicator-Based Distance Measurement — Alexandra Flores, Byron Paúl Huera Paltán, et al. · International Journal of Advanced Computer Science and Applications (2025) | TGRS Research Map | TGRS