HomePULSARvol. 2 no. 1 (2013)

Automated Banana Classifier

Ian Roy N. Jarantilla | Jon Mark Von D. Javier | Franc Winston O. Narada | Reynaldo D. Deypalubos

Discipline: Computer Engineering, Applied Sciences



This study aimed to develop devices that enable banana exporting companies and banana growers to classify their bananas accurately. The device comprising of a Liquid Crystal Displays (LCD), a segregator, motor driven conveyor, camera, and an image processing module, will serve as an automated banana classifier. For the device to be deemed effective, efficiency of its individual feature’s performance and as a whole was evaluated. The design project employed quantitative research method in assessing the device’s performance. The device was tested for 9 days and was evaluated by 21 respondents, who included 10 banana growers/ harvester/ selector, five teachers from the Faculty of Engineering, 1 engineer, and five engineering students. Every observation in testing the device and statistical evaluation were recorded. The recorded data were then analyzed to come up with a result as to how well did the device function. After conducting a thorough research, from device testing to evaluation, the researchers concluded that the device was effective in performing its task. Nevertheless, certain factors still need to be considered in improving the device for it to reach its maximum potential. With this, the researchers recommend to both banana exporting companies and growers to conduct further studies for the improvement of this Automated Banana Classifier.