Using High-Frequency Information and RH to Estimate AQI Based on SVR
The Environmental Protection Administration of Taiwan’s Executive Yuan has set up many air quality monitoring stations to monitor air pollution in the environment. The current weather forecast also includes information used to predict air pollution. Since air quality indicators have a considerable i...
| Main Authors: | , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2021-05-01
|
| Series: | Sensors |
| Subjects: | |
| Online Access: | https://www.mdpi.com/1424-8220/21/11/3630 |
| _version_ | 1797533017721274368 |
|---|---|
| author | Jiun-Jian Liaw Kuan-Yu Chen |
| author_facet | Jiun-Jian Liaw Kuan-Yu Chen |
| author_sort | Jiun-Jian Liaw |
| collection | DOAJ |
| description | The Environmental Protection Administration of Taiwan’s Executive Yuan has set up many air quality monitoring stations to monitor air pollution in the environment. The current weather forecast also includes information used to predict air pollution. Since air quality indicators have a considerable impact on people, the development of a simple, fast, and low-cost method to measure the AQI value is a worthy topic of research. In this study, a method was proposed to estimate AQI. Visibility had a clear positive relationship with AQI. When images and AQI were compared, it was easy to see that visibility decreased with the AQI value increase. Distance is the main factor affecting visibility, so measuring visibility with images has also become a research topic. Images with high and low PM<sub>2.5</sub> concentrations were used to obtain regions of interest (RoI). The pixels in the RoI were calculated to obtain high-frequency information. The high-frequency information of RoI, RH, and true AQI was used for training via SVR, which was used to generate the model for AQI estimation. One year of experimental samples was collected for the experiment. Two indices were used to evaluate the performance of the proposed method. The results showed that the proposed method could be used to estimate AQI with acceptable performance in a simple, fast, and low-cost way. |
| first_indexed | 2024-03-10T11:07:40Z |
| format | Article |
| id | doaj.art-bc254404227a4ee6940395bee3c907f9 |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-03-10T11:07:40Z |
| publishDate | 2021-05-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-bc254404227a4ee6940395bee3c907f92023-11-21T21:00:59ZengMDPI AGSensors1424-82202021-05-012111363010.3390/s21113630Using High-Frequency Information and RH to Estimate AQI Based on SVRJiun-Jian Liaw0Kuan-Yu Chen1Department of Information and Communication Engineering, Chaoyang University of Technology, 168, Jifeng E. Rd., Wufeng District, Taichung 413310, TaiwanDepartment of Information and Communication Engineering, Chaoyang University of Technology, 168, Jifeng E. Rd., Wufeng District, Taichung 413310, TaiwanThe Environmental Protection Administration of Taiwan’s Executive Yuan has set up many air quality monitoring stations to monitor air pollution in the environment. The current weather forecast also includes information used to predict air pollution. Since air quality indicators have a considerable impact on people, the development of a simple, fast, and low-cost method to measure the AQI value is a worthy topic of research. In this study, a method was proposed to estimate AQI. Visibility had a clear positive relationship with AQI. When images and AQI were compared, it was easy to see that visibility decreased with the AQI value increase. Distance is the main factor affecting visibility, so measuring visibility with images has also become a research topic. Images with high and low PM<sub>2.5</sub> concentrations were used to obtain regions of interest (RoI). The pixels in the RoI were calculated to obtain high-frequency information. The high-frequency information of RoI, RH, and true AQI was used for training via SVR, which was used to generate the model for AQI estimation. One year of experimental samples was collected for the experiment. Two indices were used to evaluate the performance of the proposed method. The results showed that the proposed method could be used to estimate AQI with acceptable performance in a simple, fast, and low-cost way.https://www.mdpi.com/1424-8220/21/11/3630AQIvisibilitydigital image processingSVRhigh frequency informationRH |
| spellingShingle | Jiun-Jian Liaw Kuan-Yu Chen Using High-Frequency Information and RH to Estimate AQI Based on SVR Sensors AQI visibility digital image processing SVR high frequency information RH |
| title | Using High-Frequency Information and RH to Estimate AQI Based on SVR |
| title_full | Using High-Frequency Information and RH to Estimate AQI Based on SVR |
| title_fullStr | Using High-Frequency Information and RH to Estimate AQI Based on SVR |
| title_full_unstemmed | Using High-Frequency Information and RH to Estimate AQI Based on SVR |
| title_short | Using High-Frequency Information and RH to Estimate AQI Based on SVR |
| title_sort | using high frequency information and rh to estimate aqi based on svr |
| topic | AQI visibility digital image processing SVR high frequency information RH |
| url | https://www.mdpi.com/1424-8220/21/11/3630 |
| work_keys_str_mv | AT jiunjianliaw usinghighfrequencyinformationandrhtoestimateaqibasedonsvr AT kuanyuchen usinghighfrequencyinformationandrhtoestimateaqibasedonsvr |