eprintid: 20417
rev_number: 3
eprint_status: archive
userid: 1
dir: disk0/00/02/04/17
datestamp: 2026-01-12 12:17:56
lastmod: 2026-01-12 12:17:56
status_changed: 2026-01-12 12:17:56
type: conference_item
metadata_visibility: show
creators_name: How, Goh Ken
creators_name: Ee, Ho Joe
creators_name: Kiu, Qi Song Colin
creators_name: Ooi, Boonyaik Yaik
creators_name: Tan, Teik Boon
creators_name: Hong, Zengwei
title: Low-Cost and Non-Invasive Fish Feeding Status Monitoring using ArUco Markers
ispublished: pub
keywords: Aquaculture; Cost effectiveness; Fish; Internet of things; Aruco; Human errors; Invasive fishes; IoT; Labour-intensive; Low-costs; Pose-estimation; Precision aquaculture; Status monitoring; Water surface; Feeding
note: Cited by: 0
abstract: This paper explores the use of floats with ArUco markers to monitor fish feeding status, addressing the limitations of traditional manual observation, which is labor-intensive and prone to human error. The ArUco markers, affixed to floats on the water's surface, provide pose estimations, which can be used to reflect fish movements during feeding at the water surface. These measurements can be analyzed in real time to determine feeding behavior, optimize feeding schedules, and reduce waste. With its high scalability, the system enables a single camera to monitor multiple tanks simultaneously, enhancing efficiency and cost-effectiveness. Preliminary results indicate high measurement accuracy across various parameters, and successful deployment in a fish farm demonstrates the system's effectiveness in real-world applications. © 2025 IEEE.
date: 2025
publisher: Institute of Electrical and Electronics Engineers Inc.
official_url: https://www.scopus.com/inward/record.uri?eid=2-s2.0-105022415122&doi=10.1109%2FICCE-Taiwan66881.2025.11207871&partnerID=40&md5=6256aa016afb58aa4a824683854bccfe
id_number: 10.1109/ICCE-Taiwan66881.2025.11207871
full_text_status: none
pagerange: 47 - 48
refereed: TRUE
isbn: 9798331587413
citation:   How, Goh Ken and Ee, Ho Joe and Kiu, Qi Song Colin and Ooi, Boonyaik Yaik and Tan, Teik Boon and Hong, Zengwei  (2025) Low-Cost and Non-Invasive Fish Feeding Status Monitoring using ArUco Markers.  In: UNSPECIFIED.