@inproceedings{scholars20417,
            note = {Cited by: 0},
       publisher = {Institute of Electrical and Electronics Engineers Inc.},
           pages = {47 -- 48},
             doi = {10.1109/ICCE-Taiwan66881.2025.11207871},
            year = {2025},
           title = {Low-Cost and Non-Invasive Fish Feeding Status Monitoring using ArUco Markers},
            isbn = {9798331587413},
             url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-105022415122&doi=10.1109\%2FICCE-Taiwan66881.2025.11207871&partnerID=40&md5=6256aa016afb58aa4a824683854bccfe},
        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. {\^A}{\copyright} 2025 IEEE.},
          author = {How, Goh Ken and Ee, Ho Joe and Kiu, Qi Song Colin and Ooi, Boonyaik Yaik and Tan, Teik Boon and Hong, Zengwei},
        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}
}