Past, Present, Future: A Comprehensive Exploration of AI Use Cases in the UMBRELLA IoT Testbed
Abstract
UMBRELLA is a large-scale, open-access Internet of Things (IoT) ecosystem incorporating over 200 multi-sensor multi-wireless nodes, 20 collaborative robots, and edge-intelligence-enabled devices. This paper provides a guide to the implemented and prospective artificial intelligence (AI) capabilities of UMBRELLA in real-world IoT systems. Four existing UMBRELLA applications are presented in detail: 1) An automated streetlight monitoring for detecting issues and triggering maintenance alerts; 2) A Digital twin of building environments providing enhanced air quality sensing with reduced cost; 3) A large-scale Federated Learning framework for reducing communication overhead; and 4) An intrusion detection for containerised applications identifying malicious activities. Additionally, the potential of UMBRELLA is outlined for future smart city and multi-robot crowdsensing applications enhanced by semantic communications and multi-agent planning. Finally, to realise the above use-cases we discuss the need for a tailored MLOps platform to automate UMBRELLA model pipelines and establish trust.
Keywords
Cite
@article{arxiv.2401.13346,
title = {Past, Present, Future: A Comprehensive Exploration of AI Use Cases in the UMBRELLA IoT Testbed},
author = {Peizheng Li and Ioannis Mavromatis and Aftab Khan},
journal= {arXiv preprint arXiv:2401.13346},
year = {2024}
}
Comments
6 pgaes, 4 figures. This work has been accepted by PerCom TrustSense workshop 2024