A Software/Hardware Co-Design Framework for the 'Internet of Eyes'

Cathal Garry, Derek Molloy

Abstract: This paper examines the challenges involved in bringing real-time image analysis to the Internet of Things (IoT) and thereby develops a software/hardware co-design framework that takes account of the power and computational requirements of IoT edge devices. Current state-of-art solutions are typically suited to applications that require low power or low latency image analysis, but not both. This paper describes an architecture that can be used to perform low latency, low power processing on an edge device, thus making it suitable for wireless `Internet of Eyes' (IoE) applications. Such applications require the processing of vast amounts of high-resolution video data in order to extract small amounts of salient information, which can then be transmitted to cloud platforms using low-bandwidth network communications protocols. This novel approach is tested by applying it to a real-time vision-based distributed motorway vehicle counting application, and evaluated for suitability to an energy harvesting deployment.

External IDs:dblp:conf/wf-iot/GarryM19