ARTIFICIAL INTELLIGENCE IN FISHERIES AND AQUACULTURE: A NEXT-GEN FISH FARMING SYSTEM

Intensified aquaculture and expansion of area under aquaculture farms can make it difficult for farm managers to supervise each and every culture system and take customized decisions. In this scenario, machine learning (ML) and artificial intelligence (AI) may assist with real-time decision-making and farm monitoring. Artificial intelligence (AI) is a simulation of human intelligence in robots by providing them with sufficient contextual data. AI can also be applied to capture fisheries and preservation of natural resources. The emergence of blockchain technology has made it possible for ML to efficiently trace the source of fish on a customer's stable and track it along the supply chain. As a result, fisheries and aquaculture may become more environmentally as well as economically sustainable. Due to growing populations and increased demand for protein food sources, there is an apparent rise in the world's food production demand each year. Fish is a desired source of protein across the globe; hence this exerts pressure on the capture fisheries. Relying on advanced aquaculture has become the best option for producing enough fish to fulfill demand. Unfortunately, in contrast to the agricultural and manufacturing sectors, the aquaculture industry has not had a significant impact from technological advancements. The emergence of AI has opened up enormous opportunities for the implementation and integration of information technology in all spheres of life. Drones, bionic robots, nano- and micro-sensors, remote cameras, intelligent sorting, statistical modules, and algorithms are some of the AI techniques and tools that will help enhance aquaculture output and minimize human intervention. Through the concept of "replacing human with machine," the intelligent farm attempts in handling precision work such as increasing oxygen input, optimizing feeding, lowering infection, and accurately harvesting in order to completely liberate the manpower and move forward towards green and sustainable aquaculture. In an effort to boost aquaculture productivity and sustainability, AI must be employed throughout the aquaculture value chain to ensure efficiency in tracking, feeding, detection of diseases, growth estimation, monitoring the environment, market information, and other areas. Therefore, innovative technologies will play a significant role in the development of aquaculture operations that call for less human labour, effective maintenance, and efficient utilization of resources. Here, we've addressed the necessity of adopting advanced technology as well as the hurdles to AI adoption in the aquaculture sector. Further, this chapter discusses how AI is deployed in the aquaculture and fishery industries presently and in the future, as well as its potential to revolutionize the aquaculture industry.