Sustainable aquaculture development: a review on the roles of cloud computing, internet of things and artificial intelligence (CIA)

• Published in: Reviews in aquaculture 2021-09, Vol.13 (4), p.2076-2091
• Main Authors: Mustapha, Umar Farouk, Alhassan, Abdul‐Wadud, Jiang, Dong‐Neng, Li, Guang‐Li
• Format: Article
• Language: English
• Subjects: Aquaculture; Aquaculture development; Aquaculture products; Artificial intelligence; Bionics; Cameras; Capture fisheries; CIA (cloud computing internet of things and artificial intelligence); Cloud computing; Demand; Disease detection; Disease recognition; Energy conservation; Environmental monitoring; Fish; fish health; Fisheries; Food; Food production; Food sources; Foods; Information technology; Internet of Things; Labour; Limiting factors; Manufacturing industry; Productivity; Proteins; Remote sensors; Resource utilization; Sorting algorithms; Sustainability; Sustainable aquaculture; Sustainable development; technology
• ISSN: 1753-5123; 1753-5131
• DOI: 10.1111/raq.12559

Each year, there is a significant rise in demand for global food production due to population increase and a rise in demand for protein food sources. This puts pressure on capture fishery as fish is a preferred protein source worldwide. However, the more resources we put into the capture fisheries to obtain maximum catch, the faster the fisheries stock becomes depleted. The best option left to produce enough fish to meet demand is relying on advanced aquaculture. Unfortunately, the impact of technological advancement in the aquaculture sector is not profound compared to the agricultural and manufacturing sectors. The advent of Cloud computing, Internet of Things, and Artificial Intelligence (CIA) has expanded numerous possibilities for applying and integrating information technology in all works of life. This article reviews the emergence of research development on CIA and the potential to revolutionize the aquaculture industry. The use of CIA techniques and tools such as drones, nano and micro‐sensors, bionic robots, remote cameras, intelligent sorting, energy‐saving processing equipment, statistical modules, and algorithms will reduce human intervention and increase aquaculture productivity. Also, the application of CIA in the aquaculture value chain to ensure effectiveness in traceability, feeding, disease detection, growth prediction, environmental monitoring, market information, and others is key to increasing aquaculture productivity and sustainability. Therefore, the future of aquaculture operations with less human labour, effective maintenance, and resource utilization largely depend on innovative technologies. Here, we outlined the need for adopting innovative technologies and the limiting factors that hinge on CIA adoption in the aquaculture industry.