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

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, (VISION)-I-4 is a smart wearable that helps pBLV in their daily challenges. It enables multiple microservices based on artificial intelligence (AI), 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 (VISION)-I-4 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 adaptation strategies for a seamless video service. We demonstrate the performance of our 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 microservices robustly in time-varying network conditions.