Personnel monitoring in hazardous areas requires a high camera density, real-time transmission, and high image quality. Power Domain Non-Orthogonal Multiple Access (PD-NOMA) technology can support the parallel transmission of multiple channels, which is beneficial for improving real-time transmission in dense transmission scenarios. Furthermore, the collaboration of multiple camera nodes can improve image quality. A transmission algorithm based on multi-image fusion is thus proposed to achieve high-quality monitoring in PD-NOMA camera networks for supervising personnel in hazardous areas. The term ″single-person information″ is defined as a key concept that reflects the probability of accurately identifying a single person in an image. The fusion image information of a single-person captured by multi-camera nodes is then defined based on the spatial relationship between the camera nodes. To maximize the fusion of image information, a real-time transmission scheduling scheme is calculated with the camera node's image resolution and wireless transmission power as control variables, while satisfying the real-time transmission requirements and the recognition of all personnel in the image. Experimental evaluations show that when the real-time transmission upper limit is 0.4 s, the transmission information of the PD-NOMA-based transmission scheduling scheme is 46.4% higher than that of the traditional transmission scheme, increasing the probability of personnel identification in the image from 0.8549 to 0.8919
