QoI-Aware Unified Framework for Node Classification and Self-Reconfiguration Within Heterogeneous Visual Sensor Networks
- Submitting institution
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Staffordshire University
- Unit of assessment
- 12 - Engineering
- Output identifier
- 5102
- Type
- D - Journal article
- DOI
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10.1109/ACCESS.2016.2635941
- Title of journal
- IEEE ACCESS
- Article number
- -
- First page
- 9027
- Volume
- 4
- Issue
- -
- ISSN
- 2169-3536
- Open access status
- Compliant
- Month of publication
- December
- Year of publication
- 2016
- URL
-
http://dx.doi.org/10.1109/ACCESS.2016.2635941
- Supplementary information
-
-
- 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
-
2
- Research group(s)
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B - Centre for Smart Systems, AI and Cybersecurity (CSSAIC)
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- The significance of this work is that it proposed, for the first time, a unified framework for node classification and dynamic self-reconfiguration in heterogeneous visual sensor networks that results in significant energy savings. Based on this work, Amjad attended an IEEE workshop on 5G Enabling Technologies that led to a new collaboration with Dr Mohsin Raza (Middlesex University) and Dr Sajjad Hussain (University of Glasgow). This resulted in the book chapter “Multiple Access and Resource Sharing for Low Latency Critical Industrial Networks” in Wireless Automation as an Enabler for the Next Industrial Revolution, John Wiley & Sons, 2019.
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -