AQPDBJUT Dataset: Picture-Based PM Monitoring in the Campus of BJUT
This work addresses PM monitoring for student health on a specific campus, but it is incremental as it primarily tests existing methods on new data.
The researchers tackled the problem of monitoring particulate matter (PM) concentrations on a university campus to protect student health by creating a new dataset of 1,500 photos from the Beijing University of Technology, and found that state-of-the-art methods perform poorly in this setting.
Ensuring the students in good physical levels is imperative for their future health. In recent years, the continually growing concentration of Particulate Matter (PM) has done increasingly serious harm to student health. Hence, it is highly required to prevent and control PM concentrations in the campus. As the source of PM prevention and control, developing a good model for PM monitoring is extremely urgent and has posed a big challenge. It has been found in prior works that photobased methods are available for PM monitoring. To verify the effectiveness of existing PM monitoring methods in the campus, we establish a new dataset which includes 1,500 photos collected in the Beijing University of Technology. Experiments show that stated-of-the-art methods are far from ideal for PM monitoring in the campus.