Development and Validation of a Proximity-based Wearable Computing Testbed for Community-oriented Wearable Systems

TL;DR

The paper presents a proximity-based wearable testbed for community-oriented systems that fuses UWB position sensors, 9-DOF motion sensing, edge computing, and a centralized server. It details the architecture, node topology (anchors/tags), and software stack (MQTT, Keepalived, HAProxy) and validates performance through static and dynamic tracking tests, reporting centimeter-level accuracy and reduced PLR when using redundant servers. Key contributions include a complete system design, implementation guidance, and empirical evaluation of tracking accuracy, latency, and reliability under varied load, highlighting practical considerations for real-world urban deployments. The work demonstrates the testbed's potential to strengthen community interactions and lays groundwork for interoperable, privacy-conscious smart wearables in shared spaces.

Abstract

In the rapidly evolving digital technology landscape, community-oriented wearable computing systems are emerging as a key tool for enhancing connectivity and interaction within communal spaces. This paper contributes to this burgeoning field by presenting the development and implementation of a proximity-based wearable computing testbed designed to forge stronger links within communities. The testbed exploits Ultra-Wideband (UWB) position sensors, 9-axis motion sensors, edge nodes, and a centralized server, forming a cohesive network that actively facilitates community interactions and engagements. By employing anchors and targets within the UWB sensors, the system achieves high precision in location and distance measurements, laying the groundwork for various proximity-based applications. Integrating 9-axis motion sensors and advanced edge nodes further underscores the system's versatility and robustness in wearable and edge computing. This paper delves into an in-depth exploration and evaluation of the proposed system's architecture, design, and implementation processes. It provides a comprehensive analysis of experimental results and discusses the system's potential impact on enhancing community networks, along with the future directions this technology could take.

Figures (9)

• Figure 1: Node Arrangement and Connectivity.
• Figure 2: Experiments Environment and Sensor deployment.
• Figure 3: Static Check Point.
• Figure 4: Dynamic Check Point.
• Figure 5: PLR with Master & Backup servers online.