Jelle Hofman, Air Quality researcher: “Kunak’s solutions build important evidence on the trustworthiness of air quality sensor data”

March 31, 2021
Interview with Jelle Hofman (IMEC) on sensor-based air quality systems

Last Thursday, March 18, 2021, we had the opportunity to talk with Jelle Hofman, about sensor-based air quality systems, their calibration and data validation.

Jelle Hofman is currently Air Quality Researcher at Imec, (Interuniversity Microelectronics Centrewith experience in environmental monitoring, UFP, PM, magnetochemical composition, personal exposure and citizen science. He works on scalable analytics for sensor data. The main topics covered by his research work include distant (cloud) calibration of PM/NO2 sensors and machine learning models for air quality inference of sensor data.

Currently, he is leading the research with sensor-based air quality systems for mobile applications.

Imec is a world-leading R&D and innovation hub in nanoelectronics and digital technologies. They create groundbreaking innovation in application domains such as healthcare, smart cities and mobility, logistics and manufacturing, energy and education. As a trusted partner for companies, start-ups and universities they bring together more than 4,000 brilliant minds from over 85 nationalities.

Imec is headquartered in Leuven, Belgium and has distributed R&D groups at a number of Flemish universities, in the Netherlands, Taiwan, USA, China, and offices in India and Japan.

Here are some of the questions we posed to Jelle and his thoughts on them:


QUESTION: Could you describe briefly the project you are carrying out with Kunak technology?

ANSWER: Regulatory air quality monitoring networks are scientifically sound and accurate. However, they achieve a limited spatial monitoring resolution, while pollutant concentrations can vary greatly in both space and time. This is why we are interested in the potential of supplementary sensor networks enabling more-fine grained sampling. This technology is also allowing us to develop data-driven models to interpolate the sensor readings in both space and time.


Q: Knowing the advantages and disadvantages of sensor-based technology, what made you choose Kunak AIR Mobile over other instruments?

A: Mobile sensors on a service fleet (in our case postal vans) enable the collection of representative fine-grained measurements (“postal service delivers at every doorstep”). Maintenance and calibration is also easy. Together with Labaqua, Kunak developed the Kunak AIR Mobile, a dedicated housing to protect the sensors against turbulent air flows and environmental effects. Moreover, we were able to test a demo device both in a mobile and static setting.


Mobile sensors […] enable the collection of representative fine-grained measurements.


Q: How would you rate your experience of using this type of technology? And do you think it is a suitable tool for projects in urban environments?

A: We have good experiences with the provided mobile sensors. The sensor devices have shown to be robust in terms of operability, connectivity and power. We like their communication and support, from deployment and device configuration to calibration and results. Although the accuracy and sensitivity of sensor data remain a challenging field of research, Kunak provides you with all the tools to easily test the performance, apply local particle/gas calibration via their cloud analytics in order to get the best out of their devices.


Q: Which are the key aspects that you consider when choosing a sensor-based technology in terms of calibration and data validation?

A: I would highlight in particular:

  • Sensor performance in 3rd party benchmarking studies/platforms (e.g. AQ-SPEC).
  • Insights on calibration approach and provided tools to improve the calibration locally.
  • Integrated protocols to test the resulting sensor performance (in this case against the newest air quality objectives (Uexp) that are being developed at the EU level).


Q: How do you think that our web-based Kunak Cloud software facilitates the maintenance and operability of a device network?

A: It provides all the necessary tools to maintain and configure the sensor tested. Moreover, its integrated functionalities derived from the well-known “Openair” R package provide you with the statistical tools to evaluate dependencies, plot time series and wind roses, and investigate correlations and accuracies,… Truly recommended!


(Kunak Cloud) provides all the necessary tools to maintain and configure the sensor tested.


Q: Finally, can you give us a sentence that summarizes your experience with Kunak?

A: “I greatly value the innovative Kunak solutions, together with their cloud analytics and calibration tools as they build important evidence on the trustworthiness of air quality sensor data! Well appreciated!”