Collecting and integrating multi-source, multi-scale air pollution related data in the APDSS
Developing a web interface for visualization, query and data mining of APDSS
Developing a mobile application for volunteer air pollution monitoring
Developing an adaptive modularized mobile sensors node for air pollution monitoring
Developing algorithms for path planning of a squadron of UAVs
We have developed an Air Pollution Decision Support System (APDSS) that put together all relevant multi-scale and multi-source data for the investigation of and decision-making on urban air pollution. We have then developed a plug-and-play mobile sensor system with 8 different types of air quality modules measuring CO, SO2, O3, NO2, CO2, temperature-humidity-pressure, α/β/γ radiation, and β/γ radiation. In addition, we have tested the CO, O3, NO2, and temperature-humidity-pressure modules performance by comparing them with collocated certified reference equipment provided by EPD and HKO. We have applied a US provisional patent for the original design. We have also collaborated with oversea researchers from Korea Institute of Science and Technology Information (KISTI) and developed a system integrating the PM2.5 data provided by governmental stations and vehicular sensors to enhance the spatio-temporal resolution of the PM2.5 pollution map.
Following the success of the APDSS, we have been developing a wearable Particulate Matter (PM) monitor to assess the 24-hour personal exposure to PM particles, including PM2.0, PM2.5, and PM10, with high temporal resolution (1-minitue). This PM monitor is a pilot development for a health-related project evaluating the relationship between personal PM2.5 exposure and arterial endothelial dysfunction.