Enhanced Efficiency of Coffee Fruit Ripe Sorting System through Ultrasound-based Optimization and Fuzzy Logic

Abstract

This research focuses on the development of a coffee fruit sorting system, which is a part of an embedded automation system for coffee processing and storage. The implementation of this system aims to improve and maintain the quality of coffee throughout the production and storage processes. The embedded automation system for coffee processing begins with the coffee fruit sorting system, which is responsible for selecting perfectly ripe and high-quality coffee fruits. Subsequently, the system proceeds with coffee bean production and storage processes. The developed system comprises small-scale subsystems capable of performing various coffee processing tasks. These subsystems can be integrated to form a larger system capable of handling coffee production and storage processes. The research utilizes software technology embedded in the hardware system. The employed software technology is a component of an intelligent control system, which utilizes artificial intelligence as its underlying control mechanism. The maturity classification of coffee fruits is divided into three classes: KM (immature), MM (mature), and MS (fully mature). This classification scheme simplifies the understanding of the sorting process.