{"title":"Developing a Small-Scale Agriculture Knowledge and Information Dissemination System: Tankyu Practice Approach","authors":"Boikobo Tlhobogang, Boago Setoto","doi":"10.1109/IIAI-AAI.2018.00054","DOIUrl":null,"url":null,"abstract":"The use of ICT has become essential to help farmers collect important and updated information and knowledge which are valuable resources that farming depends on. The study embarked on investigating the problem sources of unavailability or lack of timely, relevant and accurate farming information and knowledge for small-scale farmers. The main target is to deal with plant diseases and how to manage them by carefully diagnosing the plants leaves. This work proposes to use image analysis and convolutional neural networks and the ever increasing capability of machine learning such as supervised learning to offer a mobile solution the other functionality is development of agro advisory system to argument the work of extension farmers. A Design Science Research Methodology was followed in shaping skeleton of the proposed prototype by establishing the status quo of ICT use and readiness of the intended users. The developed prototype will be subjected to three usability measures to test if indeed it is timely, relevant and accurate as the farmers need it to be.","PeriodicalId":309975,"journal":{"name":"2018 7th International Congress on Advanced Applied Informatics (IIAI-AAI)","volume":"3 2","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 7th International Congress on Advanced Applied Informatics (IIAI-AAI)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IIAI-AAI.2018.00054","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
The use of ICT has become essential to help farmers collect important and updated information and knowledge which are valuable resources that farming depends on. The study embarked on investigating the problem sources of unavailability or lack of timely, relevant and accurate farming information and knowledge for small-scale farmers. The main target is to deal with plant diseases and how to manage them by carefully diagnosing the plants leaves. This work proposes to use image analysis and convolutional neural networks and the ever increasing capability of machine learning such as supervised learning to offer a mobile solution the other functionality is development of agro advisory system to argument the work of extension farmers. A Design Science Research Methodology was followed in shaping skeleton of the proposed prototype by establishing the status quo of ICT use and readiness of the intended users. The developed prototype will be subjected to three usability measures to test if indeed it is timely, relevant and accurate as the farmers need it to be.