Smartphone for palm oil fruit counting to reduce embezzlement in harvesting season

Abstract

Harvest estimation is an essential parameter in the agriculture industries to estimate transportation facilities and storage areas in the harvesting season. Meanwhile, companies are required to calculate crop yields quickly and accurately. This paper reports on an experimental study in the form of a smart application to count oil palm fruit in the field quickly and accurately. The system used a single shot detector algorithm to count the number of fresh fruit bunches (FFB) on-site using a smartphone camera. The cutting area (CA) at the top of the collection was collected in various positions in the database. Our research documented that the algorithm matched the CA with the picture taken by the operator. Hence, the application automatically calculated the number of harvests per-site in the FFB unit. The data were then sent to the cloud database via a wireless router in a warehouse or through a cellular network. The main advantage of this application is reducing the theft that usually occurs on the spot. The model used performs very well for agricultural applications, with 94% to 99% accuracy.