Research On Streetlight Intelligent System Based On Web

With the expansion of the city,the streetlights as a part of the city are also expanding the scale.They are distributed in various important traffic roads and around the city.People can’t walk and drive at night without them.The streetlights are an important tool for people who work at night.Huge street network continues devouring power with the increasingly shortage of energy.The implementation of energy-saving control of the streetlights is in tune with the current situation of energy conservation.Reducing energy consumption of the streetlights is also benefit for the country and its people.In this paper,the streetlight intelligent system based on Web is studied.Through an in-depth analysis of domestic streetlight monitoring system status and control strategy,combined with the needs of today’s society monitoring and management on the streetlights,a streetlight intelligent system in which the fault streetlights are displayed by the Baidu map is put forward.The streetlights brightness control strategy combined the comprehensive control method with BP neural network algorithm is presented.The main endeavor and contributions of the dissertation are as follows:Firstly,a streetlight remote monitoring system platform is built.Eclipse is the site development software.My SQL is the database.The data exchange between single streetlight and the monitoring center is completed by the communication mode combining Zig Bee and GPRS.Establishing platform has laid the foundation for the whole streetlight intelligent system.Secondly,the control strategy of streetlight intelligent system is determined.Based on the comprehensive control method in which timing scheme,induction scheme,sunrise and sunset switching scheme,emergency scheme are integrated,the BP neural network prediction model of the road light intensity is established.The power proportion is fine-tuning to the best through the model.Thus the energy saving needs and lighting effects can be taken into account.Then,the map display function of the streetlight real-time state parameters is realized.The visualization display of the real time status of the streetlights on the map is finished by the background program wrote by Python.According to the latitude and longitude information of a specific streetlight queried in the database,the corresponding location is found by the Baidu map API.The warning window of fault streetlight is pop-up automatically on the Baidu map as the same.The maintenance workers can know the status of the streetlight in real time,and quickly acquire the geographical position of the streetlight through this function.Finally,sytem functions and the intensity simulation based on BP neural network are tested.The man-machine interface is designed based on the Web technology.The main interface of the streetlight intelligent system,the automatic control interface,the manual operation interface,the fault and alarm interface of the streetlights and the real-time querying interface of the streetlight state are included.The system basic function testing icludes tests of user login,streetlight real-time monitoring,and streetlight alarm The communication function between the streetlights and the user is realized.The participation degree and the control power of the user to the streetlight intelligent system are enhanced.This paper is to provide an automated,fine management program to improve our streetlight intelligent system to make it meeting the public demand,easier on the operation and maintenance.It’s valuable and significant for the promotion of energy-saving technology and smart city development.