A Bluetooth Proximity-Based IoT Approach for Continuous Monitoring of Indoor Sedentariness

Sedentary behavior is a critical factor influencing overall health and well-being, particularly in aging populations. This work presents an indoor monitoring solution leveraging Bluetooth-Based proximity estimation to infer users’ location and movement patterns across different home environments. The objective is to generate a Sedentary Behavior Index (SBI) that quantifies the duration individuals spend in specific domestic spaces without requiring active user input. This index, derived through passive and pervasive sensing, provides healthcare professionals and researchers with insights into users’ lifestyle and activity levels within the context of their daily living environment. The proposed system, deployed in 45 houses, monitors 55 users and operates as a proximity-based IoT service that seamlessly integrates with broader health monitoring studies, enabling context-aware analysis when cross-referenced with clinical outcomes or other observational data. This approach aims to support continuous, unobtrusive, and personalized well-being assessments, laying the groundwork for adaptive interventions in remote healthcare and aging-in-place scenarios.

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Publication Details

Published
2025-10-27
DOI
https://doi.org/10.1109/wf-iot64238.2025.11270510
Primary Topic
Context-Aware Activity Recognition Systems
Type
article
Field-Weighted Citation Impact
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article

A Bluetooth Proximity-Based IoT Approach for Continuous Monitoring of Indoor Sedentariness

Context-Aware Activity Recognition Systems
article

A Bluetooth Proximity-Based IoT Approach for Continuous Monitoring of Indoor Sedentariness

article en

Abstract

Sedentary behavior is a critical factor influencing overall health and well-being, particularly in aging populations. This work presents an indoor monitoring solution leveraging Bluetooth-Based proximity estimation to infer users’ location and movement patterns across different home environments. The objective is to generate a Sedentary Behavior Index (SBI) that quantifies the duration individuals spend in specific domestic spaces without requiring active user input. This index, derived through passive and pervasive sensing, provides healthcare professionals and researchers with insights into users’ lifestyle and activity levels within the context of their daily living environment. The proposed system, deployed in 45 houses, monitors 55 users and operates as a proximity-based IoT service that seamlessly integrates with broader health monitoring studies, enabling context-aware analysis when cross-referenced with clinical outcomes or other observational data. This approach aims to support continuous, unobtrusive, and personalized well-being assessments, laying the groundwork for adaptive interventions in remote healthcare and aging-in-place scenarios.

Istituto di Scienza e Tecnologie dell'Informazione "Alessandro Faedo" (IT)
Openalex Percentile: Top 39%
Context-Aware Activity Recognition Systems
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