Development of Object Detection and Size Determination of Pineapple Fruit

Abstract

Accurate measurement of pineapple size is crucial for farmers to determine fruit value. Existing challenges in size assessment, due to the irregular shape and the presence of crowns and stems, highlight the need for a precise measurement system. This research focuses on developing an object detection system tailored for accurately measuring and analysing pineapple sizes. The methodology integrates HC_SR04 and VL53L0X sensors with an Arduino MEGA 2560 for efficient data processing. The HC_SR04 assesses both height and diameter, while the VL53L0X specifically measures diameter, allowing for a comparative analysis of sensor accuracy. The collected data is transmitted to the Arduino MEGA 2560, which interprets and displays the readings on the Serial Monitor in centimetres. Experimental results affirm the success of this methodology in obtaining accurate diameter measurements. The HC_SR04 sensor emerges as the superior choice, offering precision and efficiency. The system's practicality lies in delivering readings in centimetres, enhancing ease of interpretation for users engaged in size measurement processes. In conclusion, the study establishes a reliable system for accurately measuring both height and diameter of pineapples. Future enhancements, such as incorporating LiDAR sensors known for superior accuracy, could further refine and expand the measurement system, paving the way for even higher precision in pineapple size assessment.