IOT-Oriented Visual Target Tracking and Supply Chain Art Product Design

Abstract

Visual target tracking technology has always been one of the hotspots in the field of computer vision. After analyzing the above two problems and introducing real-time tracking, this article makes corresponding improvements to the visual target tracking structure of the Internet of Things. Based on this point, this article finally brings together related theories such as the Internet of Things and supply chain, starting from practical problems, inspecting the current situation of the supply chain of Chinese art product design companies, and proposing the necessity of establishing a systemic risk indicator system to use in the product supply chain; this article uses the HHM method to identify the risk factors of the artwork in the Internet of Things environment and promotes a multiangle risk analysis tailored to its own characteristics in the product supply chain. According to controllable risks and uncontrollable risks, combined with the structural level of the Internet of Things system, risks are divided into detection risk layer, network layer (information layer), application layer risk, and other risks. This article combines the above-mentioned visual target tracking technology with the relationship between the Internet of Things supply chains, uses the G1 method and the entropy weight method to determine the risk indicators for the subject and purpose of the risk weight, and classifies the risk indicators to propose risk control measures.