RES: Real-time Video Stream Analytics using Edge Enhanced Clouds
- Submitting institution
-
The University of Leicester
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 2174
- Type
- D - Journal article
- DOI
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10.1109/TCC.2020.2991748
- Title of journal
- IEEE Transactions on Cloud Computing
- Article number
- -
- First page
- .
- Volume
- (Online First)
- Issue
- -
- ISSN
- 2168-7161
- Open access status
- Compliant
- Month of publication
- May
- Year of publication
- 2020
- URL
-
-
- Supplementary information
-
https://doi.org/10.1109/TCC.2020.2991748
- Request cross-referral to
- -
- Output has been delayed by COVID-19
- No
- COVID-19 affected output statement
- -
- Forensic science
- No
- Criminology
- No
- Interdisciplinary
- No
- Number of additional authors
-
5
- Research group(s)
-
-
- Citation count
- -
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- Among the first papers to describe a cloud-based real-time video stream analytics system for object tracking and surveillance from large-scale distributed deployment of cameras, it been applied in the four following KTPs. XAD (Tariq, fahim@scflair.com) use this in a platform that supports law-enforcement agencies and infrastructure protection in cities. RDS (Flinn, andy.flinn@rds.global) and FPS (Coates, Mark.Coates@fp-solutions.co.uk) are using the work for real-time analysis of data streams from e.g. care homes, financial institutions and garages. Work with Bloc (Cox, keith@bloc.digital) has started laying the foundations of real-time processing of data from 5G networks, genome machines, and VR models.
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -