Design And Implementation Of Environmental Noise Map System Based On Mobile Computing

With the increase of people's awareness of environmental protection,noise problem which is caused by urban construction and vehicles caused many contradictions.Noise map is a tool demonstrates the distribution of noise,which can be used in noise pollution control and other fields.However,the traditional way of drawing noise map has many problems,such as high cost of acquisition equipment,low coverage,and untimely updating of map,which seriously affects the popularization and application of noise map.Following the continuous development of mobile network technology,the popularity of mobile intelligent terminal is increasingly higher.Under this background,it is a feasible solution to develop an app that monitors environmental noise in real time and dynamic by displaying a noise map based on intelligent terminal instead of traditional measuring equipments and combining with big data technology.This thesis takes the construction of environmental noise map system as the research object,analyzes both domestic and foreign status quo of noise mapping on mobile devices,and summarizes several problems in noise mapping at this stage,also focuses on the realization of noise map system based on mobile computing method.The main modules of the preliminary design system include: Mobile noise data collection,background service,front-end map display,including noise measurement and correction,noise source identification,noise data information upload,background data processing,map details display,noise knowledge popularization and other functions.In this thesis,an environment noise map system based on Android mobile terminal is implemented by using Android and Hadoop framework,distributed architecture,noise processing algorithm and real-time streaming processing and analysis technology.The mobile terminal uses MP + MFCC time and frequency domain feature extraction method,based on SVM classifier voting algorithm to identify the type of noise source,and upload the processed noise data to the server platform.The back-end big data streaming processing platform has a very high expansibility and scalability.The server cluster is deployed through Docker Compose to process data in real time.The mobile app obtains the noise data at the designated location through the web server interface,and draws the noise map with the help of the AMAP SDK,and visualizes the real-time noise decibel value and noise dynamic change.The system has passed the function tests of user login,noise measurement,noise source identification and noise map display,which can normally collect and measure the surrounding noise information,process the data in time through big data related technology,and update the environmental noise map in real time,which can meet the requirements of the scheme.The completion of this system basically solves the problems faced at this stage.By promoting this system,not only can more noise data be collected,but also can integrate the data shared by users,draw a complete noise map,and then meet the needs of the public and government departments.