Prototype of Strawberry Maturity-level Classification to Determine Harvesting Time of Strawberry

Abstract

The smart farm has recently attracted great attention as a solution to rural problems facing the sustainability crisis, such as the aging population of farming and livestock industries, the shortage of manpower and the production area of young people, and the stagnation of income, exports. A smart farm is a system that combines information and communication technology (ICT), internet of things (IoT), and agricultural technology that enable a farm to operate with minimal labor and to automatically control of a greenhouse environment. Machine learning based on recently data-driven techniques has emerged with big data technologies and high-performance computing to create opportunities to quantify data intensive processes in agricultural operational environments. In this paper, presents research on the application of machine learning technology to diagnose the growth status of crops and predicting the harvest time of strawberries according to image processing techniques. [1] We designed and implemented a prototype system that detects and classifies object image of strawberry using the YOLO v2 algorithm and Darknet in order to decide harvesting time of strawberries.