A semantic IoT early warning system for natural environment crisis management
- Submitting institution
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University of Southampton
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 41296277
- Type
- D - Journal article
- DOI
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10.1109/TETC.2015.2432742
- Title of journal
- IEEE Transaction on Emerging Topics in Computing
- Article number
- -
- First page
- 246
- Volume
- 3
- Issue
- 2
- ISSN
- 2168-6750
- Open access status
- Out of scope for open access requirements
- Month of publication
- May
- Year of publication
- 2015
- URL
-
-
- 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
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5
- Research group(s)
-
-
- Citation count
- 34
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- Paper describes work on a new semantic early warning system concept for natural crisis management. Work included successful trials at NEAMWave12, the first Tsunami exercise in the North-eastern Atlantic, the Mediterranean and Connected Seas involving 19 member countries of the UNESCO-IOC Intergovernmental Coordination Group (ICG). This work on intelligent sensor data management led to follow-on grant (NERC NE/S015604/1, £319,096 UoS). Work led to Middleton being invited to be short paper/poster chair of IEEE Intelligent Environments 2016 and guest editor for Sensors Journal (ISSN 1424-8220; CODEN: SENSC9) special issue on “Sensors Application on Early Warning System” in 2019.
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -