5G Edge Vision: Wearable Assistive Technology for People with Blindness and Low Vision

Autor:	Azzino, Tommy, Mezzavilla, Marco, Rangan, Sundeep, Wang, Yao, Rizzo, John-Ross
Rok vydání:	2023
Předmět:	Electrical Engineering and Systems Science - Systems and Control
Druh dokumentu:	Working Paper
Popis:	In an increasingly visual world, people with blindness and low vision (pBLV) face substantial challenges in navigating their surroundings and interpreting visual information. From our previous work, VIS4ION is a smart wearable that helps pBLV in their day-to-day challenges. It enables multiple artificial intelligence (AI)-based microservices such as visual scene processing, navigation, and vision-language inference. These microservices require powerful computational resources and, in some cases, stringent inference times, hence the need to offload computation to edge servers. This paper introduces a novel video streaming platform that improves the capabilities of VIS4ION by providing real-time support of the microservices at the network edge. When video is offloaded wirelessly to the edge, the time-varying nature of the wireless network requires the use of adaptation strategies for a seamless video service. We demonstrate the performance of an adaptive real-time video streaming platform through experimentation with an open-source 5G deployment based on open air interface (OAI). The experiments demonstrate the ability to provide the microservices robustly in time-varying network loads. Comment: 6 pages, 4 figures, 2 tables, conference
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/2311.13939 Zobrazit plný text záznamu View this record from Arxiv