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Design and Use of an Apparatus for Quantifying Bivalve Suspension Feeding at Sea
Published on: September 5, 2018
Exploring opportunities of Artificial Intelligence in aquaculture to meet increasing food demand
Mohd Ashraf Rather1, Ishtiyaq Ahmad1, Azra Shah1
1Division of Fish Genetics and Biotechnology, Faculty of Fisheries Ganderbal, Sher-e- Kashmir University of Agricultural Science and Technology, Kashmir 190006, India.
Abstract:
The increasing global population drives a rising demand for food, particularly fish as a preferred protein source, straining capture fisheries. Overfishing has depleted wild stocks, emphasizing the need for advanced aquaculture technologies. Unlike agriculture, aquaculture has not seen substantial technological advancements. Artificial Intelligence (AI) tools like Internet of Things (IoT), machine learning, cameras, and algorithms offer solutions to reduce human intervention, enhance productivity, and monitor fish health, feed optimization, and water resource management. However, challenges such as data collection, standardization, model accuracy, interpretability, and integration with existing aquaculture systems persist. This review explores the adoption of AI techniques and tools to advance the aquaculture industry and bridge the gap between food supply and demand.

