From a Low-Cost Air Quality Sensor Network to Decision Support Services: Steps towards Data Calibration and Service Development

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. View Full-Text

Keywords: air quality; low-cost sensors; sensor calibration; warning systems; data visualization

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Veiga, T.; Munch-Ellingsen, A.; Papastergiopoulos, C.; Tzovaras, D.; Kalamaras, I.; Bach, K.; Votis, K.; Akselsen, S. From a Low-Cost Air Quality Sensor Network to Decision Support Services: Steps towards Data Calibration and Service Development. Sensors 2021, 21, 3190. https://doi.org/10.3390/s21093190

AMA Style

Veiga T, Munch-Ellingsen A, Papastergiopoulos C, Tzovaras D, Kalamaras I, Bach K, Votis K, Akselsen S. From a Low-Cost Air Quality Sensor Network to Decision Support Services: Steps towards Data Calibration and Service Development. Sensors. 2021; 21(9):3190. https://doi.org/10.3390/s21093190

Chicago/Turabian Style

Veiga, Tiago, Arne Munch-Ellingsen, Christoforos Papastergiopoulos, Dimitrios Tzovaras, Ilias Kalamaras, Kerstin Bach, Konstantinos Votis, and Sigmund Akselsen. 2021. "From a Low-Cost Air Quality Sensor Network to Decision Support Services: Steps towards Data Calibration and Service Development" Sensors 21, no. 9: 3190. https://doi.org/10.3390/s21093190

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Tiago Veiga

Tiago Veiga is a postdoctoral researcher at the Department of Computer Science at NTNU. He received his M.Sc. (2010) and Ph.D. (2015) degress in Electrical and Computer Engineering from Instituto Superior Técnico, University of Lisbon, Portugal. His main research interests are decision-making under uncertanity for autonomous agents, active perception and data analysis for decision support.

Arne Munch-Ellingsen

Arne Munch-Ellingsen received his M.Sc. (1989) and Ph.D. (2009) degrees in computer science (distributed systems) from University of Tromsø, Norway. He is a senior research scientist in the Advanced Analytics and AI group at Telenor Research. His main research interests include IoT , AI, distributed systems, 5G and the analysis of time series data.

Christoforos Papastergiopoulos

Christoforos Papastergiopoulos received his M.Eng in Electrical and Computer Engineering (2019) from the Democritus University of Thrace, Greece. He is a research associate in CERTH/ITI. His main research interests are reduction of computational complexity in statistical learning algorithms and deep learning methods for stochastic simulations.

Dimitrios Tzovaras

Dimitrios Tzovaras is the Director of CERTH and a Senior Researcher (Grade A) at CERTH/ITI. He is also leading the Virtual & Augmented Reality Lab of CERTH/ITI. He received the Diploma in Electrical Engineering and the PhD in 2D and 3D Image Compression from the Aristotle University of Thessaloniki, Greece in 1992 and 1997, respectively. His main research interests include network and visual analytics for network security, computer security, data fusion, biometric security, virtual reality, machine learning and artificial intelligence.

Ilias Kalamaras

Ilias Kalamaras is a research associate at CERTH/ITI. He received his diploma in electrical and computer engineering from the Aristotle University of Thessaloniki (2010) and his PhD in multimodal dimensionality reduction from Imperial College London (2016). His main research interests include graph-based dimensionality reduction, data analysis and visualization of multimodal data, for applications related to health monitoring, network security and multimedia analysis.

Kerstin Bach

Kerstin Bach received her M.Sc. degree in Information Management and Information Technology (2007) and the Dr. rer. nat. in Computer Science (2012) from the University in Hildesheim, Germany. She is an associate professor in the Department of Computer Science at NTNU and a member of the Norwegian Open AI Lab. Her main research interests are case-based reasoning, intelligent decision support systems, explainable and human-centered AI.

Konstantinos Votis

Konstantinos Votis is a senior researcher (Grade B') and Director of the Visual Analytics Laboratory at CERTH/ITI. He received his MSc (2004) and PhD (2011) degrees in computer science and service-oriented architectures from Computer Engineering and Informatics department, University of Patras, Greece. His research interests include Human-Computer Interaction, information visualisation and management of big data, knowledge engineering and decision support systems, Internet of Things, cybersecurity and blockchain technologies as well as pervasive computing, with major application areas such as mHealth, eHealth, and personalized healthcare.

Sigmund Akselsen

Sigmund Akselsen received his M.Sc. (1987) and Ph.D. (1991) degrees in computer science (artificial intelligence) from University of Tromsø, Norway. He is a senior research scientist in the Advanced Analytics and AI group at Telenor Research. His main research interests include AI, IoT and the analysis of time series data.

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From a Low-Cost Air Quality Sensor Network to Decision Support Services: Steps towards Data Calibration and Service Development

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