| Summary: | With the increase of tourist environment, the real-time monitoring of ecological environment has become a concern. This study mainly discusses the application of cloud computing and Internet of things in the evaluation of ecological environment quality of rural tourism areas in a smart city. In this study, the real-time monitoring of the atmosphere, water, and meteorological data is collected through the GPRS data transmission module and then sent back to the local server by the GPRS network, and the obtained non-real-time and real-time data are used to establish the ecological monitoring database, the database analysis of its information, and get real-time data, monthly data, and longer cycle data. In the cloud GIS platform, there are multiple subnodes. The split tasks can be processed by each subnode through a map, and the results after processing can be summarized through reduce, which completes the implementation process of the whole idea of map reduce. Monitoring station management is mainly to establish monitoring stations in rural tourism areas and collect first-hand environmental monitoring data by using temperature, humidity, infrared, ultrasonic, and other sensors and cameras. The monitoring objects are the air quality, water quality, meteorology, etc. of the scenic area, mainly showing the location of monitoring stations and the placement of sensors. At the same time, an LED screen is set at the monitoring station to display the air quality data of the scenic spot. The data content is introduced into the DPSIR model, combined with social and economic data; according to the ecological health grading evaluation standard, the evaluation score and health grade are obtained and the ecological health status of rural tourism area is judged and evaluated. When the amount of data is less than 500 MB, there is little difference between the storage speed of the cloud GIS platform and single machine, but with the continuous increase of the amount of data, the storage speed of the cloud GIS platform is significantly higher than that of a single machine. This study is helpful in improving the ecological environment quality of rural tourism areas.
|
|---|
