{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,1]],"date-time":"2026-04-01T07:00:02Z","timestamp":1775026802475,"version":"3.50.1"},"reference-count":31,"publisher":"MDPI AG","issue":"9","license":[{"start":{"date-parts":[[2021,5,5]],"date-time":"2021-05-05T00:00:00Z","timestamp":1620172800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Horizon 2020","award":["825619"],"award-info":[{"award-number":["825619"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Air pollution is a widespread problem due to its impact on both humans and the environment. Providing decision makers with artificial intelligence based solutions requires to monitor the ambient air quality accurately and in a timely manner, as AI models highly depend on the underlying data used to justify the predictions. Unfortunately, in urban contexts, the hyper-locality of air quality, varying from street to street, makes it difficult to monitor using high-end sensors, as the cost of the amount of sensors needed for such local measurements is too high. In addition, development of pollution dispersion models is challenging. The deployment of a low-cost sensor network allows a more dense cover of a region but at the cost of noisier sensing. This paper describes the development and deployment of a low-cost sensor network, discussing its challenges and applications, and is highly motivated by talks with the local municipality and the exploration of new technologies to improve air quality related services. However, before using data from these sources, calibration procedures are needed to ensure that the quality of the data is at a good level. We describe our steps towards developing calibration models and how they benefit the applications identified as important in the talks with the municipality.<\/jats:p>","DOI":"10.3390\/s21093190","type":"journal-article","created":{"date-parts":[[2021,5,5]],"date-time":"2021-05-05T22:51:42Z","timestamp":1620255102000},"page":"3190","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":17,"title":["From a Low-Cost Air Quality Sensor Network to Decision Support Services: Steps towards Data Calibration and Service Development"],"prefix":"10.3390","volume":"21","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-5844-9383","authenticated-orcid":false,"given":"Tiago","family":"Veiga","sequence":"first","affiliation":[{"name":"Department of Computer Science, Norwegian University of Science and Technology, 7034 Trondheim, Norway"}]},{"given":"Arne","family":"Munch-Ellingsen","sequence":"additional","affiliation":[{"name":"Telenor Research, 1360 Fornebu, Norway"}]},{"given":"Christoforos","family":"Papastergiopoulos","sequence":"additional","affiliation":[{"name":"Centre for Research and Technology Hellas, Information Technology Institute, 57001 Thermi, Thessaloniki, Greece"}]},{"given":"Dimitrios","family":"Tzovaras","sequence":"additional","affiliation":[{"name":"Centre for Research and Technology Hellas, Information Technology Institute, 57001 Thermi, Thessaloniki, Greece"}]},{"given":"Ilias","family":"Kalamaras","sequence":"additional","affiliation":[{"name":"Centre for Research and Technology Hellas, Information Technology Institute, 57001 Thermi, Thessaloniki, Greece"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4256-7676","authenticated-orcid":false,"given":"Kerstin","family":"Bach","sequence":"additional","affiliation":[{"name":"Department of Computer Science, Norwegian University of Science and Technology, 7034 Trondheim, Norway"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6381-8326","authenticated-orcid":false,"given":"Konstantinos","family":"Votis","sequence":"additional","affiliation":[{"name":"Centre for Research and Technology Hellas, Information Technology Institute, 57001 Thermi, Thessaloniki, Greece"}]},{"given":"Sigmund","family":"Akselsen","sequence":"additional","affiliation":[{"name":"Telenor Research, 1360 Fornebu, Norway"}]}],"member":"1968","published-online":{"date-parts":[[2021,5,5]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Bai, L., Wang, J., Ma, X., and Lu, H. (2018). Air Pollution Forecasts: An Overview. Int. J. Environ. Res. Public Health, 15.","DOI":"10.3390\/ijerph15040780"},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"Penza, M., Suriano, D., Villani, M.G., Spinelle, L., and Gerboles, M. (2014). Towards Air Quality Indices in Smart Cities by Calibrated Low-Cost Sensors Applied to Networks, IEEE.","DOI":"10.1109\/ICSENS.2014.6985429"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"410","DOI":"10.1016\/j.envres.2017.10.019","article-title":"Localized real-time information on outdoor air quality at kindergartens in Oslo, Norway using low-cost sensor nodes","volume":"165","author":"Castell","year":"2018","journal-title":"Environ. Res."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"15403","DOI":"10.5194\/acp-18-15403-2018","article-title":"Airborne particulate matter monitoring in Kenya using calibrated low-cost sensors","volume":"18","author":"Pope","year":"2018","journal-title":"Atmos. Chem. Phys."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"293","DOI":"10.1016\/j.envint.2016.12.007","article-title":"Can commercial low-cost sensor platforms contribute to air quality monitoring and exposure estimates?","volume":"99","author":"Castell","year":"2017","journal-title":"Environ. Int."},{"key":"ref_6","doi-asserted-by":"crossref","unstructured":"Masselot, P., Chebana, F., Lavigne, E., Campagna, C., Gosselin, P., and Ouarda, T.B. (2019). Toward an Improved Air Pollution Warning System in Quebec. Int. J. Environ. Res. Public Health, 16.","DOI":"10.3390\/ijerph16122095"},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"4857","DOI":"10.1109\/JIOT.2018.2853660","article-title":"A Survey on Sensor Calibration in Air Pollution Monitoring Deployments","volume":"5","author":"Maag","year":"2018","journal-title":"IEEE Internet Things J."},{"key":"ref_8","doi-asserted-by":"crossref","unstructured":"Concas, F., Mineraud, J., Lagerspetz, E., Varjonen, S., Liu, X., Puolam\u00e4ki, K., Nurmi, P., and Tarkoma, S. (2021). Low-Cost Outdoor Air Quality Monitoring and Sensor Calibration: A Survey and Critical Analysis. arXiv.","DOI":"10.1145\/3446005"},{"key":"ref_9","unstructured":"Lauvsnes, T.B., and Nordstad, T. (2021, May 03). Air Quality in the City of Trondheim 2019 (In Norwegian). Available online: https:\/\/drive.google.com\/file\/d\/14VVUjyijgGL2zyCQeqS07mZ4oMVnHaRU\/view."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"7","DOI":"10.1111\/j.1440-1843.2011.02065.x","article-title":"Monitoring air pollution: Use of early warning systems for public health","volume":"17","author":"Kelly","year":"2012","journal-title":"Respirology"},{"key":"ref_11","unstructured":"Alphasense (2021, May 03). Data Sheet: NO-A4 Nitric Oxide Sensor. Available online: https:\/\/www.alphasense.com\/wp-content\/uploads\/2019\/09\/NO-A4.pdf."},{"key":"ref_12","unstructured":"Alphasense (2021, May 03). Data Sheet: NO2-A43F Nitrogen Dioxide Sensor. Available online: https:\/\/www.alphasense.com\/wp-content\/uploads\/2019\/09\/NO2-A43F.pdf."},{"key":"ref_13","unstructured":"Alphasense (2021, May 03). Data Sheet: OX-A431 Oxidising Gas Sensor. Available online: https:\/\/www.alphasense.com\/wp-content\/uploads\/2019\/09\/OX-A431.pdf."},{"key":"ref_14","unstructured":"Alphasense (2021, May 03). Data Sheet: Analogue Front End for Air Quality Sensors. Available online: https:\/\/www.alphasense.com\/wp-content\/uploads\/2019\/10\/AFE.pdf."},{"key":"ref_15","unstructured":"Alphasense (2021, May 03). Data Sheet: OPC-N3 Optical Particle Counter. Available online: https:\/\/www.alphasense.com\/wp-content\/uploads\/2019\/03\/OPC-N3.pdf."},{"key":"ref_16","unstructured":"Amphenol (2021, May 03). Data Sheet: Telaire ChipCap 2 Humidity and Temperature Sensor. Available online: https:\/\/www.amphenol-sensors.com\/en\/component\/edocman\/23-chipcap-2-datasheet\/download?Itemid=8487."},{"key":"ref_17","unstructured":"OriginGPS (2021, May 03). Data Sheet: ORG1510-MK04\/MK05 GPS Module. Available online: https:\/\/origingps.com\/wp-content\/uploads\/2021\/01\/Multi-Micro-Hornet-ORG1510-MK-DS-rev-4.2.pdf."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"464","DOI":"10.1021\/acssensors.6b00250","article-title":"Wearable Chemical Sensors: Present Challenges and Future Prospects","volume":"1","author":"Bandodkar","year":"2016","journal-title":"ACS Sens."},{"key":"ref_19","doi-asserted-by":"crossref","unstructured":"Han, P., Mei, H., Liu, D., Zeng, N., Tang, X., Wang, Y., and Pan, Y. (2021). Calibrations of Low-Cost Air Pollution Monitoring Sensors for CO, NO2, O3, and SO2. Sensors, 21.","DOI":"10.3390\/s21010256"},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"1352","DOI":"10.1080\/02786826.2016.1232859","article-title":"Evaluation of the Alphasense optical particle counter (OPC-N2) and the Grimm portable aerosol spectrometer (PAS-1.108)","volume":"50","author":"Sousan","year":"2016","journal-title":"Aerosol Sci. Technol."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"709","DOI":"10.5194\/amt-11-709-2018","article-title":"Evaluation of a low-cost optical particle counter (Alphasense OPC-N2) for ambient air monitoring","volume":"11","author":"Crilley","year":"2018","journal-title":"Atmos. Meas. Tech."},{"key":"ref_22","doi-asserted-by":"crossref","unstructured":"Bauerov\u00e1, P., \u0160indel\u00e1\u0159ov\u00e1, A., Rychl\u00edk, S., Nov\u00e1k, Z., and Keder, J. (2020). Low-Cost Air Quality Sensors: One-Year Field Comparative Measurement of Different Gas Sensors and Particle Counters with Reference Monitors at Tu\u0161imice Observatory. Atmosphere, 11.","DOI":"10.3390\/atmos11050492"},{"key":"ref_23","doi-asserted-by":"crossref","unstructured":"Hojaiji, H., Kalantarian, H., Bui, A.A.T., King, C.E., and Sarrafzadeh, M. (2017, January 13\u201315). Temperature and humidity calibration of a low-cost wireless dust sensor for real-time monitoring. Proceedings of the 2017 IEEE Sensors Applications Symposium (SAS), Glassboro, NJ, USA.","DOI":"10.1109\/SAS.2017.7894056"},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1038\/s41598-019-43716-3","article-title":"Long-term field comparison of multiple low-cost particulate matter sensors in an outdoor urban environment","volume":"9","author":"Bulot","year":"2019","journal-title":"Sci. Rep."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"115833","DOI":"10.1016\/j.envpol.2020.115833","article-title":"Improving accuracy of air pollution exposure measurements: Statistical correction of a municipal low-cost airborne particulate matter sensor network","volume":"268","author":"Considine","year":"2021","journal-title":"Environ. Pollut."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"105161","DOI":"10.1016\/j.envint.2019.105161","article-title":"Calibration of a low-cost PM2.5 monitor using a random forest model","volume":"133","author":"Wang","year":"2019","journal-title":"Environ. Int."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"1863","DOI":"10.1109\/TVCG.2016.2549018","article-title":"A systematic review of experimental studies on data glyphs","volume":"23","author":"Fuchs","year":"2016","journal-title":"IEEE Trans. Vis. Comput. Graph."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"400","DOI":"10.1080\/15230406.2017.1364169","article-title":"Star and polyline glyphs in a grid plot and on a map display: Which perform better?","volume":"45","author":"Opach","year":"2018","journal-title":"Cartogr. Geogr. Inf. Sci."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"133","DOI":"10.1111\/cgf.12791","article-title":"A taxonomy and survey of dynamic graph visualization","volume":"Volume 36","author":"Beck","year":"2017","journal-title":"Computer Graphics Forum"},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"775","DOI":"10.1016\/j.envpol.2018.06.019","article-title":"Review of modelling air pollution from traffic at street-level\u2014The state of the science","volume":"241","author":"Forehead","year":"2018","journal-title":"Environ. Pollut."},{"key":"ref_31","first-page":"235","article-title":"Near-Optimal Sensor Placements in Gaussian Processes: Theory, Efficient Algorithms and Empirical Studies","volume":"9","author":"Krause","year":"2008","journal-title":"J. Mach. Learn. Res."}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/21\/9\/3190\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T05:57:12Z","timestamp":1760162232000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/21\/9\/3190"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,5,5]]},"references-count":31,"journal-issue":{"issue":"9","published-online":{"date-parts":[[2021,5]]}},"alternative-id":["s21093190"],"URL":"https:\/\/doi.org\/10.3390\/s21093190","relation":{},"ISSN":["1424-8220"],"issn-type":[{"value":"1424-8220","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021,5,5]]}}}