SmartAQnet
April 18th, 2017 | Published in Research
Air quality and the associated subjective and health-related quality of life are among the important topics of our time. However, it is very difficult for many cities to take measures that to accommodate today’s needs concerning e.g. mobility, housing and work, because a consistent data base with fine-granular data and information on causal chains is missing. This has the potential to change, as today, both large-scale basic data as well as new promising measuring approaches are becoming available.
Project “SmartAQnet” is based on a pragmatic, data driven approach, which for the first time combines existing data sets with a networked mobile measurement strategy. By connecting open data, such as weather data or development plans, remote sensing of influencing factors, and new mobile measurement approaches, such as participatory with ultra-low sensor technology, “scientific scouts” and demand-oriented measurements by light weight UAVs, a novel measuring and analysis concept is created within the model region of Augsburg. In addition to novel analytics, a prototypical technology stack is planned which, through modern analytics methods and Big Data and IoT technologies, enables application in a scalable way.
SmartAQnet is funded by the German Federal Ministry of Transport and Digital Infrastructure (BMVI): www.mfund.de
Project Website
www.smartaq.net
Participate
SmartAQnet organizes a Citizen Science workshop to build fine dust sensor nodes on March 13th, 2019 in Augsburg
Open Data / API
…coming soon
Further Information
- Participate: Workshop to build fine dust sensor nodes on March 13th, 2019 in Augsburg
- LookKIT article about the project (German with English Summary)
- KIT press release on project start
- Related Article by the Stuttgarter Nachrichten (German)
- Related Article by the Badische Zeitung (German)
- Official project description on the mfund website
Start/End
- 04/2017 – 2020 (running)
Partners
- Institute of Meteorology and Climate Research, Atmospheric Environmental Research, Karlsruhe Institute of Technology (IMK-IFU)
- German Research Center for Environmental Health, Helmholtz Zentrum München (HMGU)
- Institut of Geography, University of Augsburg
- GRIMM Aerosol Technik GmbH & Co. KG
- Aerosol Akademie e.V.
- Umweltamt, Stadt Augsburg
Research topics
- Air Quality
- Environmental Sensing
- Big Data Analytics
- Mobile Computing
- Modeling
Contact
- Till Riedel (email: riedel(at)teco.edu)
- Matthias Budde (email: budde(at)teco.edu)
Selected Publications
(2019) Assessment of three-dimensional, fine-granular measurement of particulate matter by a smart air quality network in urban area, Proc. SPIE 11152, Remote Sensing of Clouds and the Atmosphere XXIV, 111520N, doi:10.1117/12.2533096
(2019) Potenzial und Grenzen des kostengünstigen SDS011 Partikelsensors bei der Überwachung urbaner Luftqualität, Umwelteinflüsse erfassen, simulieren, bewerten - 48. Jahrestagung der GUS 2019, p. 271-280, GUS, pdf
(2019) Stochastische Regressionsmodelle zur Verbesserung der Datenqualität, Kalibrierung und Interpolation von Umwelt-und Luftdaten in verteilten Messnetzen aus Low-Cost Sensoren, Umwelteinflüsse erfassen, simulieren, bewerten - 48. Jahrestagung der GUS 2019
(2019) FeinPhone: Low-cost Smartphone Camera-based 2D Particulate Matter Sensor, Sensors 19(3), p. 749, pdf, doi:10.3390/s19030749
(2018) SmartAQnet – raum/zeitlich hochaufgelöste Erfassung der Luftqualität mit neuen Datenprodukten, Umwelteinflüsse erfassen, simulieren, bewerten - 47. Jahrestagung der GUS 2018, GUS, pdf
(2018) Potential and Limitations of the Low-Cost SDS011 Particle Sensor for Monitoring Urban Air Quality, ProScience 5(3rd International Conference on Atmospheric Dust (DUST2018)), p. 6-12, url, doi:10.14644/dust.2018.002
(2018) Challenges in Capturing and Analyzing High Resolution Urban Air Quality Data, International Joint Conference on Pervasive and Ubiquitous Computing (Ubicomp'18), Adjunct Proceedings, doi:10.1145/3267305.3274762
(2018) Automated Quality Assessment of (Citizen) Weather Stations, GI_Forum, pdf, doi:10.1553/giscience2018_01_s65
(2018) SmartAQnet – Neuer smarter Weg zur räumlichen Erfassung von Feinstaub, AGIT – Journal für Angewandte Geoinformatik 4, pdf
(2018) Project SmartAQnet: Combining Existing Datasets and a Mobile Measurement Strategy into a Smart Urban Air Quality Network, Scientific Research Abstracts 8 (DUST 2018), p. 12, pdf
(2018) Suitability of the Low-Cost SDS011 Particle Sensor for Urban PM-Monitoring, Scientific Research Abstracts 8 (DUST 2018), p. 11, pdf
(2018) Privacy-Preserving Collaborative Blind Macro-Calibration of Environmental Sensors in Participatory Sensing, EAI Endorsed Transactions on Internet of Things 18(10), pdf, doi:10.4108/eai.15-1-2018.153564
(2017) SmartAQnet: Remote and In-Situ Sensing of Urban Air Quality, Proc. SPIE 10424, Remote Sensing of Clouds and the Atmosphere XXII, 104240C, pdf, doi:10.1117/12.2282698
(2017) Participatory Sensing or Participatory Nonsense? — Mitigating the Effect of Human Error on Data Quality in Citizen Science, Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies (IMWUT) 1(3), pdf, doi:10.1145/3131900