Open AccessPotato Classification by using Ultrasonic Sensor with LabVIEW
Author(s) -
Abdullah Beyaz,
Dilara Gerdan
Publication year - 2020
Publication title -
agricutural science digest/agricultural science digest
Language(s) - English
Resource type - Journals
eISSN - 0976-0547
pISSN - 0253-150X
DOI - 10.18805/ag.d-173
Subject(s) - calipers , ultrasonic sensor , software , agriculture , computer science , regression analysis , precision agriculture , work (physics) , linear regression , agricultural engineering , data mining , engineering , machine learning , mechanical engineering , acoustics , geography , physics , archaeology , programming language
Background: Agricultural product classification is an essential and widely working issue in the agriculture industry. There is a lot of work to be done in this area and the agriculture industry is looking for new applications. The reason is that the software and hardware Technologies are always developing, and the latest technologies giving better results parallel to these developments. Also, the costs of the new technologies are decreasing with the help of low-cost sensor and device technologies. New technique and technology usage also directly related to classification efficiency. The primary data on agriculture are agricultural products, so these technologies and techniques use for agricultural production. Methods: The primary data on agriculture are agricultural products, because of this reason, this research aimed to make ultrasonic sensor measurements with the help of a software which is developed in LabVIEW platform for potato classifications and showing the efficiency of the method for the potato classification, which has different sizes. Result: According to the regression coefficient results, the regression between caliper length measurement (CL) and static ultrasonic sensor length measurement (SUL) found as 95.5%, the regression between caliper length measurement (CL) and dynamic ultrasonic sensor length measurement (DUL) found as 86.9%, the regression between static ultrasonic sensor length measurement (SUL) and dynamic ultrasonic sensor length measurement (DUL) found as 87.9% for potato classification.