| Summary: | 碩士 === 國立宜蘭大學 === 多媒體網路通訊數位學習碩士在職專班 === 107 === In recent years, Taiwan’s industrial safety accidents have been frequent, and various types of occupational disasters have occurred continuously. Each occupational disaster is a family tragedy. According to past research, the most important reason for the occurrence of occupational accidents is due to the unsafe behavior of workers in unsafe locations. Therefore, it is very important for industrial plants to accurately locate the location of personnel to prevent accidents. This paper first discusses the shortcomings of the existing security management system. Then the paper designs a set of reliable personnel positioning combined with face detection of the security management system to improve the existing security management system. Because in the environment of most industrial plants, there are a large number of steel structures and iron and steel equipment inside and outside the plant, in most wireless positioning systems such as RFID, Wi-Fi, ZigBee, etc. will be because of steel structure, Causes diffraction, reflection, refraction, diffusion, etc. This paper compares the advantages and disadvantages of a positioning system, and uses the UWB positioning system to judge the position of the person, Combine the function of face detection to avoid personnel trailing.
In the literature discussion part of this paper, various wireless positioning technologies are listed and compare the advantages and disadvantages of various technologies for wireless indoor positioning. And enumerate a variety of wireless positioning measurement methods, and compare advantages and disadvantages. Various face detection techniques are listed. Research method Design a system flow and complete system architecture for the industrial plant management system using UWB positioning technology and face detection. The experiment of the positioning system compares the performance difference between the RFID positioning system and the UWB system in the general office environment and the simulated industrial plant environment positioning. The face detection part experiment uses the commonly used OpenCV technology to compare the advantages and disadvantages of the Microsoft Azure Face API face detection technology used in this paper. It is found that the system can effectively perform positioning and face detection, which can greatly improve the plant security system.
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