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The Smart Pest Identification and Management System using Drone for Mango Farming project's main goal is to help the farmers identify the pest for them to be guided and certain of which type of pesticide is to be used, and to avoid low effectivity pesticide solution mix that farmers create in their own preferences and has no scientific basis. The researchers used the current drone technology to capture images of leaves at a high altitude, created an algorithm to identify pest using different MATLAB functions, a database for collecting information, data set and for future statistical record, and a mobile and web app to access the whole project's system and by utilizing the current drone technology to capture images. Through a lot of researches,
surveys and interviews, the researchers found out that one of the main factors of the major decline in our country's mango production is due to pests and the farmer's uncertainty in using which pesticide for each occurrence of pest. To solve this problem, the researchers assists the farmers by automatically identifying the pest through leaf and fruit markings using a MATLAB algorithm with at least 85% accuracy and give them suggestions in which pesticide is suitable to use through researchers' mobile application. This research project can also be used as a template for other fruit-bearing trees and be a basis for future statistical records using the data gathered.