Applying AR Assistive Devices to AI Identification of the Number and Body Length of Ornamental Fish

Abstract: This research attempts to focus on the focus of aquaculture: the number and length of breeding, and develop an artificial intelligence identification module using AR assistive devices to identify the length and quantity of aquatic organisms to reduce the workload of aquaculture operators. When AR assistive devices are used to assist in the breeding of ornamental fish, AI’s quantity and length identification will be affected by light refraction. Dynamic ornamental fish will affect quantity identification, and the depth of the breeding pond will also affect length identification. Then grasp the characteristics of the scene, find the appropriate recognition algorithm and parameter tuning, and adjust the recognition strategy. These problems can be effectively overcome and the needs of farmers can be met. Let farmers recognize the application of AR assistive devices in assisting the breeding of ornamental fish. It can be used to count shipment quantities, reduce shipping costs, and improve shipping service quality. It is used in daily growth records to streamline record operations and reduce record management costs. The accumulated information helps to grasp the panorama and life cycle of ornamental fish breeding.

Key words: Yolo, AI length identification, quantity identification, ornamental fish, industrial applications

JEL codes: Q1, Q16