Design And Algorithm Research Of Intelligent Street Lamp Control System

With the rapid development of Internet of Things technology,the management of urban lighting in China is gradually moving in the direction of refinement and intelligence.Against this background,intelligent street lighting has emerged as an integral part of smart cities,providing new ideas for the management of urban lighting with its intelligent and energysaving features.However,the majority of the city’s lighting systems still use more conventional controls,relying on manual inspection,computer monitoring,etc.These monitoring and management modes lack flexibility.Therefore,to address the problems of backward management technology,low lighting efficiency,and excessive energy consumption in traditional lighting systems,this thesis researches intelligent street light control systems to achieve intelligent management of urban lighting.Firstly,this thesis designs the overall scheme of the intelligent street light control system,specifying the functional requirements and overall architecture of the system.The system consists of a sensing layer,a transmission layer,a platform layer,and an application layer,which are specifically divided into the intelligent street light terminal,Narrow Band Internet of Things(NB-IoT)communication module,IoT platform,and client application software.Under the system architecture,each part was designed and developed separately,completing the construction of the physical street light hardware,writing a program to realize sensor data collection and upload,improving the functions of the platform layer,writing a mobile phone application using Java language,and finally completing the end-toend integrated development of the smart streetlight.Then,this thesis proposes an intelligent street light energy-saving control algorithm,introducing Tuna Swarms Optimize Long and Short-Term Memory(TSO-LSTM)model to predict short-time traffic flow,combining light intensity and traffic flow fuzzy controller to control the overall luminous efficiency of the street light and completes the training of the traffic flow prediction algorithm and the design of the dual fuzzy controller in MATLAB software.Finally,the testing results for each component of the NB-IoT-based intelligent street light control system showed that all parts of the system could work normally,the intelligent street light terminal sensors could successfully collect data,and the terminal and the cloud platform could communicate normally.The designed energy-saving control algorithm was then simulated in MATLAB software and compared with the power consumed by traditional street lighting control methods.It was finally calculated that the streetlight based on double fuzzy control saves 44.03% electricity compared with all-night lights and 20.74% electricity compared with alternate-light lights,which verifies the feasibility of the scheme in lighting systems.