Abstract
The Internet of Things (IoT) has many potential applications in the field of environmental monitoring. In this article, some hardware, including noise meters, ZigBee, and GPRS, were assembled and adjusted to get traffic noise data, which would be analyzed and compiled into a database based on the categories and characteristics of the data. Based on traffic noise data from 35 roads of nine green spaces in Xiamen, we used a back propagation neural network to practice net-simulation of noise data from 30 roads, while data from the remaining 5 roads were used as test data. Finally, the trained neural network was used to simulate traffic noise from 100 roads in Xiamen Island. Software systems using VB language and Flex network technology were also developed, and the simulation results were published on the Internet. The success of the method indicates that the Environmental IoT not only enables fast and effective acquisition of environmental data, but also enables accurate simulation and real-time network distribution.
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