| EPSRC Reference: |
EP/R018677/1 |
| Title: |
IRC Next Steps Plus : OPERA - Opportunistic Passive Radar for Non-Cooperative Contextual Sensing |
| Principal Investigator: |
Piechocki, Professor RJ |
| Other Investigators: |
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| Researcher Co-Investigators: |
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| Project Partners: |
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| Department: |
Electrical and Electronic Engineering |
| Organisation: |
University of Bristol |
| Scheme: |
Standard Research |
| Starts: |
01 January 2019 |
Ends: |
31 December 2022 |
Value (£): |
1,363,228
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| EPSRC Research Topic Classifications: |
| Artificial Intelligence |
Information & Knowledge Mgmt |
| Networks & Distributed Systems |
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| EPSRC Industrial Sector Classifications: |
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| Related Grants: |
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| Panel History: |
| Panel Date | Panel Name | Outcome |
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15 Feb 2018
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HIPs 2017 and IRC Next Steps Plus Panel
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Announced
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Summary on Grant Application Form |
Physical activity and behaviour is a very large component in an array of long-term chronic health conditions such as diabetes, dementia, depression, COPD, arthritis and asthma, and the UK currently spends 70% of its entire health and social care budget on these types of conditions. All aspects of self-care, new therapies or management conditions, require novel non-intrusive technologies able to capture the salient data on causes and symptoms over long periods of time.
The OPERA Project - Opportunistic Passive Radar for Non-Cooperative Contextual Sensing - will investigate a new unobtrusive sensing technology for CONTEXUAL SENSING - defined as concurrent physical activity recognition and indoor localisation - to facilitate new applications in e-Healthcare and Ambient Assisted Living (AAL). The OPERA platform will be integrated into the "SPHERE long term behavioural sensing machine" to gather information alongside various other sensors around the home so as to monitor and track the signature movements of people.
The OPERA system will be built around passive sensing technology: a receiver-only radar network that detects the reflections of ambient radio-frequency signals from people - in this case, principally, the WiFi signals in residential environments. These opportunistic signals are transmitted from common household WiFi access points, but also other wireless enabled devices which are becoming part of the Internet of Things (IoT) home ecosystem.
The project will make use of cutting-edge hardware synchronisation techniques, and recent advances in direction finding techniques to enable accurate device-free (non-cooperative) localisation of people. It will also employ the latest ideas in micro-Doppler radar signal processing, bio-mechanical modelling and machine/deep learning for automatic recognition of both everyday activities e.g. tidying and washing-up, to events which require urgent attention such as falling. OPERA is expected to overcome some of the key barriers associated with the state-of-the-art contextual sensing technologies. Most notably non-compliance with wearable devices, especially amongst the elderly, and the invasion of privacy brought about by the intrusive nature of video based technologies.
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Key Findings |
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This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk
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Potential use in non-academic contexts |
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This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk
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Impacts |
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| Description |
This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk |
| Summary |
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| Date Materialised |
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Sectors submitted by the Researcher |
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This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk
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| Project URL: |
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| Further Information: |
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| Organisation Website: |
http://www.bris.ac.uk |