Research On Intelligent Monitoring System For Tobacco Storage Environment Based On Internet Of Things Technology

At present,with the continuous development of new generation information technologies such as cloud computing and Internet of Things,all walks of life are using information technology to improve the efficiency and comprehensive competitiveness of the entire enterprise.The tobacco industry is also increasing in CIMS and ERP.Investment in large information technology.In the tobacco industry,tobacco leaves undergo a natural alcoholization process before they are made into finished tobacco.In the process of alcoholization,the problem of moldy tobacco storage leaves has been plaguing major tobacco companies for many years,and the annual losses are enormous.At present,the detection means for tobacco mold in the production process and storage of the tobacco industry is still determined by artificial sensory identification or by using a pin-type temperature sensor in combination with the experience of the tester to determine whether mildew has occurred.Artificial sensory evaluation has strong subjectivity and limitations,is easily interfered by the tester’s own state and the external environment,and the detection range is limited,it is difficult to find and eradicate all moldy tobacco leaves.Therefore,this topic explores the development of an objective,reliable and fast new detection method.In order to realize the real-time collection of large-area storage tobacco environmental parameters,real-time monitoring and mildew warning of stored tobacco leaf environment,overcoming the problem of traditional wired data transmission distance and limited data processing capacity,combined with Internet of Things technology and artificial neural network The technology has built a monitoring platform for the storage parameters of tobacco leaves.Firstly,according to the temperature and humidity and various special gas changes occurring in the process of tobacco leaf alcoholization,an environmental data collection terminal was designed with STM32 microprocessor as the core and combined with temperature,humidity,carbon dioxide and alcohol sensors for collecting tobacco storage environment.parameter.At the same time,using STM32 microprocessor combined with wireless RF module and GPRS data transmission module,a set of handheld wireless repeaters is designed.The handheld wireless repeater is used to wake up the data collection terminal and collect the environmental data information collected by each terminal by wireless.Send data to the server via GPRS.After that,the tobacco leaf state recognition model was established based on BP neural network algorithm.The storage state of the tobacco leaf was obtained by processing the collected environmental parameters,and the validity of the model was verified by simulation experiments.Finally,based on Python language and django framework,the intelligent monitoring background information management system of tobacco storage environment is completed,which can realize the functions of receiving,storing,analyzing and processing,and querying the environmental parameters of storage tobacco,and can realize tobacco on the information management system.Visual display and alarm of parameter anomalies and mildew status of tobacco leaves.The test results show that the system uses the Internet of Things technology combined with BP neural network algorithm to effectively complete the real-time monitoring of tobacco storage environment parameters and tobacco mildew status,and achieved good results.