Artificial Intelligence in Fisheries and Aquaculture: Enhancing Sustainability and Productivity

Mohale, Hari Prasad and Narsale, Swapnil Ananda and Kadam, Rishikesh Venkatrao and Prakash, Patekar and Sheikh, Samad and Mansukhbhai, Chovatia Ravikumar and Kirtikumar, Parmar Bindiya and Baraiya, Ravi (2024) Artificial Intelligence in Fisheries and Aquaculture: Enhancing Sustainability and Productivity. Archives of Current Research International, 24 (3). pp. 106-123. ISSN 2454-7077

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Abstract

According to its definition, artificial intelligence (AI) is "the future built from fragments of the past." These are applications that acquire novel solutions with practice. Artificial intelligence has been used in various disciplines, from agriculture to full industry automation. Thanks to AI, aquaculture has become a less labor-intensive industry, enabling the fisheries sector to grow quickly and triple production quickly. It can appear as any laborer at work, such as feeders, water quality monitors, harvesters, processors, etc. AI can even be employed to protect aquatic life types from extinction. AI monitors fishing activity worldwide and promotes open sea fisheries' sustainability. AI plays a significant role in combating IUU fishing. Artificial intelligence (AI) can be used in aquaculture to limit input waste and cut costs by up to 30%. As a result, AI offers total control over fish production systems at a lower maintenance and input cost. AI's integration into aquaculture has transformed the industry, enabled sustainable growth, increased productivity and cost savings while minimizing environmental impact and labor requirements. Through the application of AI technologies, aquaculture can meet the growing demand for seafood while addressing challenges such as overfishing, environmental degradation, and resource scarcity.

Item Type: Article
Subjects: Institute Archives > Multidisciplinary
Depositing User: Managing Editor
Date Deposited: 05 Apr 2024 06:58
Last Modified: 05 Apr 2024 06:58
URI: http://eprint.subtopublish.com/id/eprint/4215

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