An Embedded Risk Prediction System for Wheelchair Safety Driving

Ma, Congcong; Li, Wenfeng; Li, Qimeng; Gravina, Raffaele; Yang, Yi; Fortino, Giancarlo

doi:10.1007/978-3-030-02819-0_12

Cited by 2 publications

(1 citation statement)

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“…It is designed to transform community interactions and engagements by leveraging the synergy of advanced technologies. At its core, the system integrates Ultra-Wideband (UWB) position sensors [3] for precise location tracking and 9-axis motion sensors [2], [4] to capture intricate movement details. Supported by edge computing, this network excels in accuracy and responsiveness, which is essential for community-centric applications.…”

Section: Introductionmentioning

confidence: 99%

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

Li,

Mangione,

Porreca

et al. 2024

2024 IEEE International Conference on Pervasive Computing and Communications Workshops and Other Affiliated Events (PerCom Work

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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.

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Section: Introductionmentioning

confidence: 99%