Research On Urban Noise Pollution Monitoring System Based On NB-IoT

With the rapid development of economy,environmental pollution has become increasingly serious,especially noise pollution from various aspects in cities has seriously affected people’s life and work,and even caused damage to physical and mental health.In order to obtain the more comprehensive and a wider range of truth of noise pollution,this dissertation has build a set of NB-IoT-based urban noise pollution monitoring system using the Internet,performing long-term monitoring of noise pollution in cities.The monitoring data can not only be used for laboratory analysis,but also provide factual basis for relevant environmental protection departments,which is helpful for noise pollution control.This dissertation takes urban noise pollution as the research object,arranges the monitoring terminal in a real environment,and implements noise signal collection and excessive noise classification at the monitoring point.The monitoring terminal and the IoT cloud platform are connected through the NB-IoT wireless communication technology.Users can view real-time noise data,alarm records and historical records through the webpage or mobile phone We Chat applet,which realizes an all-weather noise pollution monitoring system.The main contents of this dissertation are as follows:1.Aiming at the increasingly serious situation of urban noise pollution,the current status of research on urban noise pollution monitoring systems at home and abroad is analyzed.In view of the shortage of existing technologies,a set of NB-IoT-based urban noise pollution monitoring systems is designed with the help of narrowband IoT technology to achieve all-weather monitoring of the monitoring area.2.The software and hardware design of the monitoring terminal is completed.Based on the pulse-coupled neural network,a noise classification algorithm is proposed.It can output time series and information entropy sequences as the characteristics of noise classification through network iterations.It is verified through experiments that the accuracy of the noise classification results is above 90%.The design and implementation of the noise classification module,data transmission,and hardware channel are completed on the PL side of the PYNQ-Z2 hardware platform through collaborative design of software and hardware.The PS side has completed the design of the overall process control of the system,implemented the software and hardware collaboration through API functions,and designed two monitoring modes for selection of different monitoring areas.3.The software and hardware design and implementation of the wireless data transmission layer is completed.The surrounding circuit design of the NB-IoT module makes the module work normally.The initialization settings and networking settings are completed based on the two basic functions required by the wireless data transmission layer as the starting point.Communication protocols and framing mechanisms are designed for the actual needs of the system.According to the characteristics of the noise monitoring system,a low-power operation mode is designed to further reduce the system power consumption.4.The test of the overall system function and communication quality performance is completed by running in an actual environment.Partition and select points according to the selected measurement area,set noise standards,connect monitoring equipment to the IoT cloud platform,and test system functions.The test results show that both the webpage and the mobile phone can view the functions of noise pollution monitoring data,historical record query,alarm push,and alarm record query in real time,and the communication quality performance meets the system requirements,which verifies the feasibility of the system.