Qidi Zhao, Yanju Liu, Yang Yu, Jianhui Song, G. Zhou
{"title":"基于ARM9的粮食状况智能监控系统","authors":"Qidi Zhao, Yanju Liu, Yang Yu, Jianhui Song, G. Zhou","doi":"10.1109/CCDC.2014.6852902","DOIUrl":null,"url":null,"abstract":"An intelligent system for monitoring and controlling of the grain condition is designed. The system is based on embedded ARM9 core processor, using SCM for the lower machine control unit. The grain environment Information such as temperature, humidity, and CO2 concentration is collected and stored by Multi-sensor. Then the data is processed via multi-regional information fusion. The levels of the grain condition are predicted based on the BP neural network. The article focused on the hardware circuit design of the grain condition intelligent monitoring system and the principle of the multi-regional weighted fusion. The Experimental results show that grain condition intelligent monitoring system designed in this paper has many good features such as good site stability, easy acquisition and real-time on-line detection. And the system has important significance for future grain situation monitoring.","PeriodicalId":380818,"journal":{"name":"The 26th Chinese Control and Decision Conference (2014 CCDC)","volume":"51 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-07-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"10","resultStr":"{\"title\":\"Intelligent system for monitoring and controlling of the grain condition based on ARM9\",\"authors\":\"Qidi Zhao, Yanju Liu, Yang Yu, Jianhui Song, G. Zhou\",\"doi\":\"10.1109/CCDC.2014.6852902\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"An intelligent system for monitoring and controlling of the grain condition is designed. The system is based on embedded ARM9 core processor, using SCM for the lower machine control unit. The grain environment Information such as temperature, humidity, and CO2 concentration is collected and stored by Multi-sensor. Then the data is processed via multi-regional information fusion. The levels of the grain condition are predicted based on the BP neural network. The article focused on the hardware circuit design of the grain condition intelligent monitoring system and the principle of the multi-regional weighted fusion. The Experimental results show that grain condition intelligent monitoring system designed in this paper has many good features such as good site stability, easy acquisition and real-time on-line detection. And the system has important significance for future grain situation monitoring.\",\"PeriodicalId\":380818,\"journal\":{\"name\":\"The 26th Chinese Control and Decision Conference (2014 CCDC)\",\"volume\":\"51 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2014-07-14\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"10\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"The 26th Chinese Control and Decision Conference (2014 CCDC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CCDC.2014.6852902\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"The 26th Chinese Control and Decision Conference (2014 CCDC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CCDC.2014.6852902","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Intelligent system for monitoring and controlling of the grain condition based on ARM9
An intelligent system for monitoring and controlling of the grain condition is designed. The system is based on embedded ARM9 core processor, using SCM for the lower machine control unit. The grain environment Information such as temperature, humidity, and CO2 concentration is collected and stored by Multi-sensor. Then the data is processed via multi-regional information fusion. The levels of the grain condition are predicted based on the BP neural network. The article focused on the hardware circuit design of the grain condition intelligent monitoring system and the principle of the multi-regional weighted fusion. The Experimental results show that grain condition intelligent monitoring system designed in this paper has many good features such as good site stability, easy acquisition and real-time on-line detection. And the system has important significance for future grain situation monitoring.