Design and implementation of cloud enabled random neural network-based decentralized smart controller with intelligent sensor nodes for HVAC
- Submitting institution
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Glasgow Caledonian University
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 33316194
- Type
- D - Journal article
- DOI
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10.1109/JIOT.2016.2627403
- Title of journal
- IEEE Internet of Things Journal
- Article number
- -
- First page
- 393
- Volume
- 4
- Issue
- 2
- ISSN
- 2327-4662
- Open access status
- Compliant
- Month of publication
- November
- Year of publication
- 2016
- URL
-
-
- 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
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5
- Research group(s)
-
-
- Citation count
- 32
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- A random neural network (RNN)-based smart controller for Internet of Things (IoT) platform was presented. It’s integrated with cloud processing for training the RNN which has been implemented and tested in an environment chamber at GCU. The IoT platform is modular and not limited to but has several sensors for measuring temperature, humidity, inlet air coming from the HVAC duct and PIR. Two research projects: TSB (Technology Strategy Board), “Feasibility of random neural networks as an intelligent self-learning platform for sensors” CENSIS “Low cost/ power consumption Random Neural Controller for enhanced sensor intelligence".
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -