CODET: An artificial intelligence-based multisensory system for precision harvesting and purchase decisions

Abstract

Fruit ripeness detection plays a key role in precision agriculture, which enables optimal harvesting and transportation of produce to retailers. Various methods have been explored as means to detect this feature; however, in modern age, no standardised method exists to classify fruits based on their ripening state. Thus, this project aims to design and develop a smart system based on Artificial Intelligence to evaluate the ripeness state. The result is a portable handheld device capable of detecting maturity based on the physical properties of the fruit in real-time. Codet is a portable fruit ripeness prediction system with hardware and software components that make these predictions possible. It consists of an RGBC sensor, an 18-channel spectrometer (from 410nm to 940nm), an 11-channel spectrometer (from 430nm to 670nm), an ultrasonic sensor, time of flight sensors and a camera. With the help of a display, the user can determine the ripeness state of a fruit with just a button press. The device can identify the ripeness state of fruits with an accuracy of 99.9%.

Description

Applied project submitted to the Department of Computer Science and Information Systems, Ashesi University, in partial fulfilment of Bachelor of Science degree in Computer Science, August 2024

Keywords

agricultural device

Citation

DOI