Abstract
Aquaculture automation is one of the effective solutions to meet the growing global demand for seafood by improving efficiency and sustainability in the aquaculture industry. In this study, it can explore the abilities of advanced technologies such as robotics, artificial intelligence (AI) and the Internet of Things (IoT) to optimize operations in the field of aquaculture to be more advanced. Key innovations include robotic fish feeders, which can improve feeding accuracy based on fish behavior and environmental conditions, and automatic cleaning systems that maintain optimal water quality, reducing labor consumption and fish health will be more assured. These technologies collectively reduce operating costs, minimize indirect waste and can reduce environmental pollution. Despite challenges such as high start-up costs and technical complexity, aquaculture automation provides great opportunities in the production of a product. This research highlights how automation can revolutionize aquaculture practices, ensuring economic stability, increasing product quality and environmental balance that can guarantee global sustainability.
Metadata
Item Type: | Article |
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Creators: | Creators Email / ID Num. Adzher, Siti Nurul Azreen 2024412028@student.uitm.edu.my Asmizi, Nur Anis Hurin 2024209448@student.uitm.edu.my Azlan, Nor Arifah E’liyana 2024804602@student.uitm.edu.my Othman, Jamal jamalothman@uitm.edu.my |
Contributors: | Contribution Name Email / ID Num. Chief Editor Othman, Jamal UNSPECIFIED |
Subjects: | L Education > LG Individual institutions > Asia > Malaysia > Universiti Teknologi MARA > Pulau Pinang L Education > LG Individual institutions > Asia > Malaysia > Universiti Teknologi MARA |
Divisions: | Universiti Teknologi MARA, Pulau Pinang > Permatang Pauh Campus |
Journal or Publication Title: | Beyond Boundaries: The Multidimensional Horizons of E-Learning |
ISSN: | 9786299875550 |
Volume: | 9 |
Page Range: | pp. 8-18 |
Keywords: | Aquaculture Automation, Robotic Fish Feeders, Automated Cleaning Systems |
Date: | March 2025 |
URI: | https://ir.uitm.edu.my/id/eprint/114780 |