Task Offloading for Smart Glasses in Healthcare: Enhancing Detection of Elevated Body Temperature
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Abstract (arXiv)
Wearable devices like smart glasses have gained popularity across various applications. However, their limited computational capabilities pose challenges for tasks that require extensive processing, such as image and video processing, leading to drained device batteries. To address this, offloading such tasks to nearby powerful remote devices, such as mobile devices or remote servers, has emerged as a promising solution. This paper focuses on analyzing task-offloading scenarios for a healthcare monitoring application performed on smart wearable glasses, aiming to identify the optimal conditions for offloading. The study evaluates performance metrics including task completion time, computing capabilities, and energy consumption under realistic conditions. A specific use case is explored within an indoor area like an airport, where security agents wearing smart glasses to detect elevated body temperature in individuals, potentially indicating COVID-19. The findings highlight the potential benefits of task offloading for wearable devices in healthcare settings, demonstrating its practicality and relevance.
Key facts. Cited by 3 papers in the map (data through 14 Oct 2026). Builds on 4 of its 20 references that are in the map. First posted on arXiv 14 Aug 2023.
Builds on
4 of 20 references.
References · 4
- 2016Challenges and Opportunities in Edge Computingcited by 26
- 2021A Survey of Hybrid Human-Artificial Intelligence for Social Computingcited by 5
- 2022Trust2Vec: Large-Scale IoT Trust Management System based on Signed Network Embeddingscited by 3
- 2022Blockchain Application on the Internet of Vehicles (IoV)cited by 3
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Citing papers per year: 2024: 2; 2025: 1.
3 papers.