The Study On Intelligent Lighting Control System Of Urban Street Lamp Based On Internet Of Things

With the development of high technology such as cloud computing,big data,and artificial Intelligence,the traditional city street light has been unable to meet the needs of people's lives gradually.The construction of city has been changing from a traditional city to a new smart city,in which the intelligent lighting control system of urban street lamp plays an important role.Traditional urban streetlight controls,such as manual,inductive and timing control methods,have problems such as low intelligence,waste of energy,difficulty in maintenance,and lack of humanity.But the smart lighting provides comfortable and green lighting for people's road trip from the aspects of intelligent dimming,energy saving,quick maintenance and humanistic care.In this dissertation,the technologies of the intelligent lighting control system of urban street lamp include: system circuit design,ZigBee,GPRS,backstage software,mobile APP and intelligent dimming,and so on.The system consists of six parts:street lamp node controller,centralized controller,cloud server,backstage management system,mobile terminal APP and database.The main research content of this dissertation: Firstly,the control circuit of street lamp node with the functions of light intensity,vehicle flow,voltage and current data collection and ZigBee networking is designed;Secondly,the centralized controller circuit is designed for data relay and remote wireless communication;Thirdly,the backstage management system and mobile terminal APP with data analysis and processing,display,map positioning and fault alarm functions are developed;Finally,a six-category intelligent dimming algorithm with directed acyclic graphs is studied to automatically change the dimming level,according to the environment factors such as different vehicle flow and light intensity.The innovations of this dissertation: Aiming at the problem that urban street lights are not timely inaccurate dimming and low intelligence,a six-category intelligent dimming algorithm with directed acyclic graph support vector machine(DAG-SVM)is proposed.Firstly,the minimum sequence optimization method is used to improve the speed of the optimal solution of the support vector machine;then the support vector machine,adopting the different linear,polynomial and Gauss kernel functions,is used to construct a six-category dimming model;Finally,the dimmingmodel is used to classify the traffic flow,light intensity and other data.According to the classification results,the backstage management system delivers the corresponding dimming level command to realize the intelligent adjustment of the street lamp brightness.The results of the system experiment show that the intelligent lighting control system of urban street lamp,adopted a six-category dimming algorithm with directed acyclic support vector,can not only be more intelligent and accurate,but also save up to 63.0 percent energy.Compared with the manual,inductive and timing control methods,our method respectively improve the 57.5 percent,14.5 percent and 5.0percent system energy efficiency.