A SOLUTION FOR SUPPLYING NUTRITIONAL INFORMATION BASED ON THE NAÏVE BAYES MODEL TO ENHANCE AGRICULTURAL PRODUCTS TO VIETGAP STANDARD IN LAM DONG PROVINCE

Abstract

In the period of Industry 4.0, applying modern information technology in supporting the production process, it is necessary to have an inspection and monitoring
system to effectively support the implementation of the production process to prevent risks or improve quality agricultural products meeting VietGap standards in
order to facilitate the development of safe and sustainable crop production. This paper presents a practical solution, applying Naïve Bayes model, one of the most
popular probabilistic supervised learning techniques in Machine Learning to build a mobile application that predicts information of Nutritional science for crops
supports experts in the process of smart agricultural production with high quality and better VietGap standards than the traditional method, the results are recorded in
Excel for the purpose only to check and compare. The results of this study have shown the convenience and speed of sending to users actual results of nutritional
information monitoring for crops by using Flutter's open source mobile technology running on multiple platforms such as Android, iOS, Linux, Windows and MacOS,
and along with the SQL Sever management system on the Client - Sever model.