To the central content area

Deployment and maintenance project of internet of things for air quality sensing in Chiayi City year 2019

Absrtact
The main jobs of this project is to deploy 50 stations and 8 wind- meters, 200 existing stations inspection and maintenance, public version of environmental information inquiry platform, and hot zone data analysis. In response to the risk that the sensing element may also disable mainland products this year, the Swiss Sensirion element will be selected. This year, the PM2.5 sensing element will be replaced with a Swiss brand, and the communication module will also be replaced with an Italian brand. Available only after passing type approval. The type verification procedure for the sensor to be sent to the Measurement and Development Center of the Industrial Technology Research Institute was approved before the end of August. In this study implements the inspection plan. A comparison frame used by the comparison source has been set up at the Chiayi University station. After completing the inspection before the inspection, the site inspection comparison will be started. Each sensor will be inspected at least once a quarter. The number of 202 is inspections in this plan, and the number of two device is inspection standards. The replacement was new ones on October 9. The number of one is missing data . The main reason for the lack of data is that the wireless signals may be due to weather. The signal will be disturbed by humidity, causing a bad condition of signal transmission. The improvement method is next month's inspection and comparison and supplementary testing. At the same time, the wireless signal will be monitored 24 hours. quality. The public version of the environmental information query platform mainly uses the actual point of the sensor as the unit, presents the air quality color level with real-time data, and can broadcast the trend change over time in the last 6 hours. Protective measures at air quality level. In terms of auxiliary auditing applications, based on the characteristics of real-time monitoring and extensive deployment of sensors, through statistical analysis, it provides long-term pollution potential hotspots based on sensing attributes. In community sensing, the causes of two long-term pollution potential hotspots are estimated from sensor concentration trends and time characteristics. One is market activity; the other is the restaurant ’s soot emissions that cause the sensor VOCs concentration to be at business hours. High values occur, and an audit is performed through the time characteristics of the monitoring to detect the situation of excessive emissions and a penalty will be issued. The PM2.5 pollution potential hot zone in Houhu Industrial Zone is the northeast corner and Zhongxiao 1st Street and 2nd Street. The VOCs pollution potential hot zone is located in the northeast and southeast corner of Houhu Industrial Zone. A total of 13 suspected pollution sources are provided. At present, no clear cause of pollution has been found for the hot zone. It is speculated that the source of pollution may not be near the sensing point due to the high height of the chimney emitted by the factory. Therefore, more information and related simulations are needed to confirm the source of the pollution. In terms of assisting the visit of the sensor, the sensor currently uses the sensor alarm analysis system to assist the auditor in detecting one case of open-air pollution. However, there is still much room for improvement in actually assisting other sub-plans to verify the performance. Application analysis has been adopted to continuously track and observe the changes. The sensor data comparison analysis is performed through the integration of other sub-project feedback information, and the correlation between the city's events and alarm events is compared to a total of 16 events. Among them, 4 were monitored with sensor PM2.5; 12 were monitored with VOCs, and only 1 sensor responded with PM2.5; with the VOCs concentration of the sensor By comparison, it was found that there was a difference of 3-4 hours between the time of aging and the concentration, but there were peak changes in the monitoring of catering fume. In addition, the potential areas of pollution were found based on statistical analysis, and related suspicious sources of pollution were provided to assist the inspection.
Keyword
PM2.5, VOCS, IoT
Open
top