Open AccessAI-Based Ripeness Grading for Oil Palm Fresh Fruit Bunch in Smart Crane Grabber
Author(s) -
Harsawardana,
Reza Rahutomo,
Bharuno Mahesworo,
Tjeng Wawan Cenggoro,
Arif Budiarto,
Teddy Suparyanto,
Don Bosco Surya Atmaja,
Bayu Samoedro,
Bens Pardamean
Publication year - 2020
Publication title -
iop conference series. earth and environmental science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.179
H-Index - 26
eISSN - 1755-1307
pISSN - 1755-1315
DOI - 10.1088/1755-1315/426/1/012147
Subject(s) - ripeness , palm oil , process (computing) , sorting , grading (engineering) , automation , computer science , engineering , agricultural engineering , artificial intelligence , environmental science , mechanical engineering , civil engineering , agroforestry , horticulture , operating system , ripening , programming language , biology
Indonesia is one of the biggest palm oil exporters in the world. For Indonesia to stay competitive in thepalm oil industry, the harvesting and evacuating process in its oil palm plantation need to be optimized. This research introduces machinerycalled as Smart Crane Grabber. This machinery can be used for automatic harvesting and evacuation process of oil palm fresh fruit bunch. To enable automation, Smart Crane Grabber is equipped with an Artificial Intelligencesystem for automatic ripeness sorting. TheArtificial Intelligence system developed for Smart Crane Grabber achieves 71.34% accuracy by using only 400 images as preliminary training data.