QoI-Aware Unified Framework for Node Classification and Self-Reconfiguration Within Heterogeneous Visual Sensor Networks
- Submitting institution
-
Birmingham City University
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 11Z_OP_D0062
- 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
- -
- Year of publication
- 2016
- URL
-
https://ieeexplore.ieee.org/document/7779069
- 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
-
-
- Research group(s)
-
-
- Citation count
- 2
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- Due to energy and throughput constraints of visual sensing nodes, in-node energy conservation is one of the prime concerns in wireless visual sensor networks (VSNs). This work proposes a unified framework for node classification and dynamic self-reconfiguration in heterogeneous VSNs. The framework incorporates quality-of-information awareness to support a range of applications. The significant energy savings observed by analysing the simulation results demonstrate the framework’s feasibility to assist the system design engineers for speedy deployment of VSNs in scenarios with strict resource constraints. The 3D coverage modelling scheme provides a generalised direction to future research within the context of intelligent sensing.
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -