DETAILS

Bringing real-time image analysis to the Internet of Things (IoT) poses many challenges. Current state-of-art solutions are typically suited to applications that require low power or low latency image analysis, but not both. We develpp 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. Our approach a software/hardware co-design framework that takes account of the power and computational requirements of IoT edge devices. This has been tested by applying it to a real-time vision-based distributed motorway vehicle counting application, and evaluated for suitability to an energy harvesting deployment.

Student(s): Cathal Garry (Intel)

Publications

• Garry, Cathal, and Derek Molloy. “A Software/Hardware Co-Design Framework for the ‘Internet of Eyes’.” In 2019 IEEE 5th World Forum on Internet of Things (WF-IoT), pp. 133-138. IEEE, 2019.