Smart Pest Identification and Management System using Drone for Mango Farming
What is SPIMS
By conducting researches, surveys and interviews, the researchers found out that one of the main factors of the major decline in the Philippines mango production is due to rampant pest infestation and widespread diseases. Farmer’s uncertainty of pest and disease proper prevention also caused pests to be immune of pesticides. To solve this problem, the researchers assisted mango growers by automatically identify the pest through leaf and fruit markings using a MATLAB algorithm with at least 85% accuracy that provides suggestions of integrated pest management and effective date of application available through the researchers’ published android application. The Smart Pest Identification and Management System using Drone for Mango Farming project’s main goal is to identify three classifications of pests/diseases particularly Anthracnose, Fruit Borer and Sooty Mold that is inhabiting a Mango Tree by using web and mobile applications. Identifying the pest and its proper pest management increases the production of mango by a number of percentages. The researchers utilized the current drone technology to capture images of leaves at a high altitude. Using gray-level co-occurrence matrix and support vector machine functions, the algorithm is able to identify pests and diseases accurately. A real-time database is also developed for collecting information and a list of trained data set of leaf markings used for pest classification. This research project is a usable template for other fruit-bearing trees and a basis for future statistical records using the data gathered from the application.