City scale particulate matter monitoring using LoRaWAN based air quality IoT devices
- Submitting institution
-
University of Portsmouth
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 25020077
- Type
- D - Journal article
- DOI
-
10.3390/s19010209
- Title of journal
- Sensors
- Article number
- 209
- First page
- -
- Volume
- 19
- Issue
- 1
- ISSN
- 1424-8220
- Open access status
- Compliant
- Month of publication
- January
- Year of publication
- 2019
- 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
- Yes
- Number of additional authors
-
9
- Research group(s)
-
C - Cyber Security
- Citation count
- 20
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- This low cost Air Quality (AQ) device design has been deployed in the UK, Morocco, Vietnam, Taiwan, France (Oct19) and Switzerland (Sept19). It resulted in further funding (NEXUSS £33k calibration testing; NEXUSS £35k calibration equipment; SMMI AQ deployments £13k; IAA community engagement £14k; summer Internships funding £9k; NESTA/Solentcollective £15k) and formed a Zenodo AQ Community; 1000+ downloads (https://zenodo.org/communities/air-quality). Invited workshops: Vietnam-German University Ho-Chi-Minh City (Aug19); ETH Zurich AQ workshop (Sept19); NEXUSS Air Quality and sensor construction workshop (DEC19). Output public code repositories (github.com/FEEprojects) e.g. Plantower (5134 installs); sensirion-sps030 (500 installs). Data provider for SoCollective (mandi@socollective.org.uk) and Southampton City Council (Hazel.Agombar@southampton.gov.uk).
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -