Distributed two-step quantized fusion rules via consensus algorithm for distributed detection in wireless sensor networks
- Submitting institution
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University of Lincoln
- Unit of assessment
- 12 - Engineering
- Output identifier
- 27396
- Type
- D - Journal article
- DOI
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10.1109/TSIPN.2016.2549743
- Title of journal
- IEEE Transactions on Signal and Information Processing over Networks
- Article number
- -
- First page
- 321
- Volume
- 2
- Issue
- 3
- ISSN
- 2373-7778
- Open access status
- Out of scope for open access requirements
- Month of publication
- April
- Year of publication
- 2016
- URL
-
https://doi.org/10.1109/TSIPN.2016.2549743
- Supplementary information
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- 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)
-
-
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- Distributed decision fusion in a bandwidth-constrained wireless sensor network (WSN) is considered. Existing distributed consensus-based fusion rules algorithms perform poorly, not converging across the sensor nodes. We propose a two-step distributed quantized fusion rule algorithm that requires 50% less power than the existing algorithm. The proposed algorithm has been applied to a WSN testbed as part of the BBSRC Seeding Catalyst award BB/SCA/Lincoln/17 that developed a low power LoRaWAN soil moisture sensor network on the farm, demonstrating how smart WSNs could provide an impetus to farmers by providing knowledge and information without the need for onsite instrument and data specialists.
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -