HAPADS is an ambitious project that will custom design and build a novel air mobile monitoring system (devices, data acquisition, analysis, and user interface), which will enable end-users (drivers, transport companies, municipalities, and the at-large public) to make information-driven decisions to mitigate air pollution exposure for personnel and to the public. HAPADS will be a solution to overcome the significant problems of the use of moveable and portable air quality monitoring platforms (MPs) in mobile air quality monitoring. HAPADS will have special features:
- HAPADS be based on a mobile programmable platform for data collecting, processing, modeling, and transmitting wirelessly. The proposed platform will integrate the sensors and transmitting devices, it will also extensively collect and process data.
- To monitor gas such as NO2, HAPADS method is based on the dedicated nitrogen dioxide gas sensors developed with the utilization of metal oxides that serves as gas-sensitive materials. The measurement method will be based on the novel microwave circuits and conventionally resistive measurements to cover the full range of possible target gases concentration in comparison with commercially available NO2 detectors.
- To monitor PMs, HAPADS methods are using direct particle counting of certain sizes to allow precise and unambiguous measurements. The proposed sensor uses this principle to accurately measure PM. Currently, there are no portable sensors available on the market that use this measurement principle. The innovativeness of the proposed solution lies in the development of the first prototype using the principle of direct PM counting, which is small, cheap, and can be used as a portable device.
- HAPADS will devise and implement specialized embedded software for energy-efficient cognitive mobile MPs that are automatically self-calibrated for a new deployment location, enabling mobile deployment.
HAPADS is an EEA POLNOR research project (2020 – 2023). In the project the Arctic Green Computing group is the leader of the work package on multi-objective optimization of MPs.