Implementation of Artificial Intelligence in Aquaculture and Fisheries: Deep Learning, Machine Vision, Big Data, Internet of Things, Robots and Beyond

Abstract

The aquaculture and fishery industry are multi-billion-dollar business across the globe and the demand for aquatic species produce increases exponentially throughout these years. However, the depletion of aquaculture lands and aquatic pollution are some of the major worrying predicaments challenging the future of this industry. Sustainable growth strategies are the only way out and they must come hand in hand with the implementation of artificial intelligence to achieve the desired outcomes high-throughput in short time periods. The intelligent fish farm and smart cage aquaculture management system are some of the fruits of this drive and the system keeps improving to date. In this review, we provide recent updates over the past half decade of artificial intelligence implementation in fishery and aquaculture in hope to provide highlights and future directions to push the industry to greater heights.

Implementation of Big Data Analytics and its Challenges in Digital Transformation Era: A Literature Review

“…For example, in the education sector, Big Data Analytics is commonly utilized to build remote interactive digital learning transmission classrooms, network-based professional teaching resource libraries and 3D virtual reality technology application center as a form of school-company cooperation in the integration of industry and education, which is expected to obtain qualified human resources [17]. In Taiwan, the implementation of Big Data technology in the aquaculture and fisheries sector is an interesting example, including the use of Unmanned Condition Monitoring (UAV), Smart Feeding, Support Vector Machine (SVM), Intelligent Cage Aquaculture (ICA), etc [20].…”

MGFGNet: an automatic underwater acoustic target recognition method based on the multi-gradient flow global feature enhancement network

“…As this industry continues to expand, traditional processes involving essential technologies such as aquaculture environment monitoring, feeding, and fish behavior surveillance (Wu et al, 2022) incur significant costs. Hence, the urgent need arises to employ artificial intelligence technologies to enhance the economic, social, and environmental sustainability of the fish supply chain (Lim, 2022). AI-based aquaculture technologies primarily encompass environmental monitoring, intelligent feeding, biological behavior monitoring, and fishing vessel motion tracking (Setiyowati et al, 2022).…”