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The open-data platform of the Central Meteorological Administration and the Ministry of Environment is integrated into ThingSpeak to analyze the outdoor environment weather comfort index.
The open-data platform of the Central Meteorological Administration and the Ministry of Environment is integrated into ThingSpeak to analyze the outdoor environment weather comfort index.
Some time ago, I saw that Central Weather Administration and Ministry of Environment have open-data platforms that can be used. At the same time, I was also testing the function of ThingSeak. I thought that if the data from the Central Weather Administration and the Ministry of Environment were automatically uploaded to ThingSpeak, I would do some more the analysis I want to do should be quite interesting. After testing, I can really write the program code on MATLAB Analysis of ThingSpeak Apps, capture the open data of the Central Weather Administration and Ministry of Environment, and then import it to the cloud for calculation and analysis. Although it is only a simple chart and instrument display, you can also observe its changes and some data meanings.
During the integration test, special thanks to my friends for their assistance and help in recording data so that the test could proceed smoothly.
After logging in to ThingSpeak at the beginning, go to the Apps field and click the MATLAB Analysis option. Then, write the program code in the MATLAB Code field. For its syntax, refer to the tutorial on the ThingSpeak website (Click this link), as shown in Figure 1.
Figure 1：ThingSpeak MATLAB Analysis Command Line Code Window
Then observe whether the data you want to capture is automatically imported into ThingSpeak's built-in charts and instruments. In this test, Miaoli's automatic observation station data is used to make test records. Figure 2 shows temperature and humidity. Figure 3 shows air pressure and climate comfort level (THI). Figure 4 shows the ultraviolet index UVI and fine suspended particles PM2.5. Figure 5 shows air quality (AQI) and rainfall probability. Figure 6 shows body temperature and outdoor environment weather index (OEWI).
Figure 2：Temperature and humidity
Figure 3：Air pressure and THI
Figure 4：UVI and PM2.5
Figure 5：AQI and rainfall probability
Figure 6：Body temperature and outdoor environment weather index (OEWI)
Among them, the data on temperature, humidity, air pressure, and rainfall probability are collected from the Central Weather Administration -Meteorological Open Data Platform; The data on UVI, PM2.5, and AQI are collected from the open data platform of the Ministry of Environment, and the website of the data open platform has detailed data introduction and collection methods.
OEWI (Outdoor Environmental Weather Index) is a term I hypothesized. I use the concept of fuzzy theory to analyze THI, UVI, AQI, and rainfall probability to determine the OEWI model, as shown in Figure 6. It is assumed here that OEWI has four levels, 1 is good, 2 is ordinary, 3 is careful, and 4 is alert. According to the level, I can judge whether it is suitable to go out or what things I should pay attention to; this is purely for my reference because I think it is fun and interesting.
The ThingSpeak chart I used for testing is at the link below：
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