{"title":"Environment Monitoring System for Tobacco Storage Based on IOT and Neural Network","authors":"Dagui Chen, Donghai Liu","doi":"10.1109/CISCE50729.2020.00064","DOIUrl":null,"url":null,"abstract":"In order to realize the real-time collection, real-time monitoring and mildew warning of the environmental parameters of stored tobacco leaves, a set of monitoring system of tobacco storage environment was built in combination with Internet of things and artificial neural network technology. The system uses temperature sensor, humidity sensor and carbon dioxide sensor as sensor data terminal, transmits data to master controller STM32F103 for off-line detection through Zigbee wireless module, and uses BP neural network to fuse sensor data on MATLAB. Then the fusion algorithm is transplanted to STM32F103 for off-line detection. Finally, the sensor data and fusion calculation results are uploaded to the cloud server through the WiFi module, real-time monitoring on the client side. The results show that the system has high precision and can realize the whole function design.","PeriodicalId":101777,"journal":{"name":"2020 International Conference on Communications, Information System and Computer Engineering (CISCE)","volume":"21 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 International Conference on Communications, Information System and Computer Engineering (CISCE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CISCE50729.2020.00064","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
In order to realize the real-time collection, real-time monitoring and mildew warning of the environmental parameters of stored tobacco leaves, a set of monitoring system of tobacco storage environment was built in combination with Internet of things and artificial neural network technology. The system uses temperature sensor, humidity sensor and carbon dioxide sensor as sensor data terminal, transmits data to master controller STM32F103 for off-line detection through Zigbee wireless module, and uses BP neural network to fuse sensor data on MATLAB. Then the fusion algorithm is transplanted to STM32F103 for off-line detection. Finally, the sensor data and fusion calculation results are uploaded to the cloud server through the WiFi module, real-time monitoring on the client side. The results show that the system has high precision and can realize the whole function design.