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All Journal Journal of Applied Geospatial Information
Indra Jaya
Marine Science and Technology Departement, IPB University, Indonesia
Civil Engineering, Building, Construction & Architecture Earth & Planetary Sciences Engineering Environmental Science Physics

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Computer Vision-Based Fish Feed Detection and Quantification System Riyandani Riyandani; Indra Jaya; Ayi Rahmat
Journal of Applied Geospatial Information Vol 7 No 1 (2023): Journal of Applied Geospatial Information (JAGI)
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jagi.v7i1.5644

Abstract

The development of the Automatic Feeder instrument and OAK-D camera has yielded positive results. The Automatic Feeder functions well, dispensing 30 grams of fish feed every 5 rotations of the stepper motor. The OAK-D camera records with sharp details, accurate colors, and good contrast, producing high-quality videos. The YOLOv5x detection model achieves an accuracy of 82%, precision of 80%, recall of 84%, mAP of 81.90%, and a training loss of 0.079144. This model can detect fish feed with high accuracy. The calculation of fish feed reveals different consumption patterns in the morning, afternoon, and evening. On average, the fish feed is depleted at the 25th minute across all time periods. The information from the graphs and tables can assist in optimizing the feeding process to avoid overfeeding.
Co-Authors Ayi Rahmat Riyandani Riyandani