{"title":"An agricultural extension support system on mobile communication networks","authors":"Chi-Ngon Nguyen, Nguyen Thai-Nghe","doi":"10.1109/ATC.2015.7388386","DOIUrl":null,"url":null,"abstract":"This study proposes an approach for building a Semi-Automatic Agricultural Extension Support System based on mobile communication networks and machine learning. This system can be used to link farmers and agricultural experts, thus, it can be considered as an online “farmer-expert bridge”. To build the system, at first, we need to build modules for sending and receiving SMS/MMS messages. These modules are important for farmers to send questions or images, e.g., about their rice status, that need to be consulted by the agricultural experts. Next, a message classification module is built using a combination of machine learning method (e.g., SVM) with image and text processing technologies. Finally, a whole web-based system is conducted to integrate these modules. Initial results show that construction of this system is feasible. This is also the foundation for building an online automatic agricultural extension support system through mobile communication networks.","PeriodicalId":142783,"journal":{"name":"2015 International Conference on Advanced Technologies for Communications (ATC)","volume":"28 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 International Conference on Advanced Technologies for Communications (ATC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ATC.2015.7388386","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
This study proposes an approach for building a Semi-Automatic Agricultural Extension Support System based on mobile communication networks and machine learning. This system can be used to link farmers and agricultural experts, thus, it can be considered as an online “farmer-expert bridge”. To build the system, at first, we need to build modules for sending and receiving SMS/MMS messages. These modules are important for farmers to send questions or images, e.g., about their rice status, that need to be consulted by the agricultural experts. Next, a message classification module is built using a combination of machine learning method (e.g., SVM) with image and text processing technologies. Finally, a whole web-based system is conducted to integrate these modules. Initial results show that construction of this system is feasible. This is also the foundation for building an online automatic agricultural extension support system through mobile communication networks.