Android based rice pest detection system using learning vector quantization method

2nd International Conference on Natural Resources and Life Sciences

生态环境科学

Budiman, A.^1 ; Utomo, P.^1 ; Rahayu, S.^2

Informatics Management Department, Merdeka University of Madiun, Jl. Serayu 79, Madiun

63133, Indonesia^1

Agrotechnology Department, Merdeka University of Madiun, Jl. Serayu 79, Madiun

63133, Indonesia^2

关键词: Alternative solutions;    Crop failures;    Detection system;    Farmer;    Learning Vector Quantization;    Primary sources;    Rice plants;    Staple food;   

Others  :  https://iopscience.iop.org/article/10.1088/1755-1315/293/1/012001/pdf
DOI  :  10.1088/1755-1315/293/1/012001

学科分类：环境科学（综合）

来源: IOP

【 摘 要 】

In Indonesia, rice was still an essential commodity. Aside from being a staple food producer of rice, as well as a primary source of livelihood for farmers. The problem often experienced by farmers was the threat of pest attack and cause massive losses; it could even lead to crop failures and harm the farmers. During this time to suppress the attacks of pest, farmers give pesticides which if it handles inappropriate would interfere with health. The best solution was to make detection system of pest attacks so could minimise the pest aggression. The limited knowledge and skills of farmers in the detection of rice crops made farmers prefer to spray pesticides. To facilitate farmers in detecting pest attacks, developed Android-based applications that were simple and easy to use device directly in the field using smartphone devices and Learning Vector Quantization (LVQ) Method. Farmers could use the application by taking pictures of rice plants that allegedly exposed to attacks with smartphones. The app would recommend alternative solutions to pest-infected plants without the use of pesticides.