| Smart street lighting systems are essential to city energy conservation,emission reduction and traffic lighting safety,and are highly valued in the construction of many smart cities.However,most cities still use more traditional street lamp system control schemes.There are many problems in this scheme,such as rough street lamp control methods,high power consumption,street lamp failure analysis and poor maintenance methods.Aiming at the energy-saving problem of street lighting,A street lamp energy-saving control method based on multi-sensor information fusion and edge computing is proposed.This control method collects multiple sensor information to detect pedestrians on the road,distance to objects,environmental noise,etc.,according to relevant environmental factors,Accurately analyze lighting needs.In order to optimize the brightness control cycle of street lights,a CNN algorithm for traffic statistics based on image enhancement is adopted.The histogram equalization(HE)and convolutional neural network(CNN)hybrid algorithm is used to build a deep learning model to achieve pedestrian and vehicle traffic statistics.Adjust the brightness control cycle of street lights according to pedestrian and vehicle flow.Complete the system energy saving control plan.For street lamp data storage,calculation,and analysis requirements,a monitoring platform based on cloud computing and visual analysis is used to monitor street lamp operation in real time.The platform realizes data reception and provides users with an interactive interface,which can display street lamp nodes and their locations,operating conditions,surrounding environment and other information in real time.In addition,it can also realize node management,historical data query,real-time alarm,remote control,and fault diagnosis.And other functions.On the basis of the above research,This article is based on a smart monitoring and management system for urban street lamps composed of street lamp nodes,concentrator nodes and cloud monitoring platform.The street lamp node is composed of the main control chip STM32,power supply module,various types of sensors and wireless transmission module LORA.Its main function is to collect street lamp environmental data and calculate and detect the conditions of people and vehicles,and provide street lamp switch control commands.The concentrator node is mainly composed of the main control chip,LORA and NB-IOT wireless communication modules.It receives the data of the street light node through the LORA network,and then transmits it to the cloud monitoring platform remotely through the NB-IOT wireless.In the end,the cloud monitoring platform will view and use the data collected by street lights through a visual web interface for users.After experimental testing and analysis,the problems of lamp lighting energy saving and operation safety can be better solved in this system,and have good market value and application prospects.Based on the street lamp node and configuring the corresponding sensors,the author designed an environmental monitoring station for the later research of the subject.Figure[35]table[5]reference[52]... |
