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Reference Number EP/Z533749/1
Title IDEAL: Reducing Carbon Footprints of IoT Devices through Extension of Active Lifespans
Status Funded
Energy Categories Energy Efficiency (Other) 20%;
Not Energy Related 80%;
Research Types Basic and strategic applied research 100%
Science and Technology Fields PHYSICAL SCIENCES AND MATHEMATICS (Computer Science and Informatics) 30%;
ENGINEERING AND TECHNOLOGY (Mechanical, Aeronautical and Manufacturing Engineering) 70%;
UKERC Cross Cutting Characterisation Not Cross-cutting 100%
Principal Investigator Dr KD McDonald-Maier
No email address given
Computing and Electronic Systems
University of Essex
Award Type Standard
Funding Source EPSRC
Start Date 01 January 2025
End Date 31 December 2027
Duration 36 months
Total Grant Value £1,568,896
Industrial Sectors Information Technologies
Region London
Programme Manufacturing and the Circular Economy, NC : ICT, NC : Physical Sciences
 
Investigators Principal Investigator Dr KD McDonald-Maier , Computing and Electronic Systems, University of Essex (99.994%)
  Other Investigator Dr J Cano Reyes , School of Computing Science, University of Glasgow (0.001%)
Dr C McElroy , Social Sciences Division, University of Oxford (0.001%)
Dr W Vanderbauwhede , School of Computing Science, University of Glasgow (0.001%)
Dr K Wheeler , Sociology, University of Essex (0.001%)
Professor N Yoshida , Computing, Imperial College London (0.001%)
Dr X Zhai , Computing and Electronic Systems, University of Essex (0.001%)
Web Site
Objectives
Abstract The CO2 emissions from manufacture (the so-called embodied carbon) of end-user ICT devices makes up the majority of their carbon footprint over the typical current useful life of such devices. To achieve sustainable ICT, in addition to reducing run time energy consumption, it is therefore essential to extend the active life, ideally to several decades. The largest growth in end-user devices is in the Internet of Things (IoT) market, projected to rise to 30 billion devices by 2030.Our vision with the IDEAL project is to demonstrate the possibility of extending the lifetime of IoT devices from several years to several decades through a combination of novel hardware design technologies, hardware/software co-design techniques, formal methods, machine learning and circular economy. As current business models assume short replacement cycles for end-user devices (typically a few years), in addition to the technologies to extend the useful life, we will also demonstrate the viability of alternative business models based on very long-lived devices, co-created with our partners.Our technology will allow not only to extensively prolong the useful life, but also to accurately assess the degradation of any given device, enabling the repurposing of devices with reduced capabilities for new tasks that match these capabilities. In this way, our proposal fits both with Sustainable ICT, as it will enable a drastic reduction in the embodied carbon of IoT devices, and the Circular Economy, as our technology will allow devices to be repurposed repeatedly throughout their useful life.Our proposed approach is to instrument the integrated circuits at the lowest level with a novel, ultra-low power, unobtrusive monitoring and data aggregation technology and additional self-healing capabilities. The generated data will be analysed using low power machine learning nodes executing close to the actual IoT devices rather than in the cloud for reliable and early detection of anomalies in the system operation, indicative of early system degradation, and produce the optimal strategy for addressing each anomaly before it can affect the lifetime of the system. Because this is a close-loop networked system with a considerable degree of control over the IoT devices, it is essential to have guarantees of correctness and security by design in the communication between the analysis and decision making nodes and the IoT devices, which will be enabled by the use of a formal mechanism know as session types.The system we propose to develop is a subsystem of any IoT system: an IoT system consists of end-user devices located at the so-called "edge", connected to a cloud data centre, with increasingly, part of the processing performed in the "fog" between the edge and the cloud. The aim is that the introduction and operation of our subsystem will substantially reduce the full-lifecycle carbon footprint of the overall system. In business terms, our system fits within an emerging environment of IoT-as-a-service and circular economy. Large-scale introduction of our technology and associated business models can result in the emergence of entirely new types of businesses taking care of the re-purposing of devices or offering monitoring and adaptation services
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