Anugerah F. Amalia, H. S. Rahayu, Y. P. Rahardjo, Lintje Hutahaean, E. Rohaeni, C. Indrawanto, R. A. Saptati, V. Siagian, Abdul Waris
{"title":"Artificial intelligence for small hydroponics farms employing fuzzy logic systems and economic analysis","authors":"Anugerah F. Amalia, H. S. Rahayu, Y. P. Rahardjo, Lintje Hutahaean, E. Rohaeni, C. Indrawanto, R. A. Saptati, V. Siagian, Abdul Waris","doi":"10.1590/1807-1929/agriambi.v27n9p690-697","DOIUrl":null,"url":null,"abstract":"ABSTRACT The application of artificial intelligence (AI) in modern agriculture has attracted increasing attention since its automation has the potential to accelerate food production with efficiency in resource use. Fuzzy logic, as one AI method, can be applied in hydroponics as an automation function of a nutrient mixing machine. There have been some inventions of nutrient mixing machines in commercial-scale agribusiness but not yet at the level of the small and medium farms that are mostly found in developing countries. This study constructed a hydroponics nutrient mixing machine employing a fuzzy logic method, calculated the machine’s efficiency, and evaluated its economic application. The automated nutrient mixing machine using fuzzy logic was efficient, and both theoretical field capacity and actual field capacity indicators were higher with the use of the nutrient mixing machine compared to manual nutrient mixing. This machine saves 78% of the labor normally used for mixing nutrients, with a saving of up to 42.86% in the nutrients used compared with mixing manually.","PeriodicalId":21302,"journal":{"name":"Revista Brasileira de Engenharia Agrícola e Ambiental","volume":"16 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2023-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Revista Brasileira de Engenharia Agrícola e Ambiental","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1590/1807-1929/agriambi.v27n9p690-697","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
ABSTRACT The application of artificial intelligence (AI) in modern agriculture has attracted increasing attention since its automation has the potential to accelerate food production with efficiency in resource use. Fuzzy logic, as one AI method, can be applied in hydroponics as an automation function of a nutrient mixing machine. There have been some inventions of nutrient mixing machines in commercial-scale agribusiness but not yet at the level of the small and medium farms that are mostly found in developing countries. This study constructed a hydroponics nutrient mixing machine employing a fuzzy logic method, calculated the machine’s efficiency, and evaluated its economic application. The automated nutrient mixing machine using fuzzy logic was efficient, and both theoretical field capacity and actual field capacity indicators were higher with the use of the nutrient mixing machine compared to manual nutrient mixing. This machine saves 78% of the labor normally used for mixing nutrients, with a saving of up to 42.86% in the nutrients used compared with mixing manually.