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Substations are an important part of the power grid. The quality of substations’ maintenance is related to the safety and stability of the power grid. The number of devices in substations increases rapidly, but the number of personnel for maintenance is relatively shortage, which leads to the transformation of substation maintenance from manual inspection to intelligent inspection. There are a large number of video cameras in substation, and the video data is generally transmitted to the back-end server for analysis and processing through optical fibers. In order to solve the problem of high bandwidth pressure of transmission channel, high computational performance requirements of application server, and to improve the image recognition efficiency, the edge intelligent recognition equipment for multiple video streams in substations was developed based on artificial intelligence and edge computing technology. The design and development were carried out from the aspects of overall architecture, main control software, algorithm model, and so on. The accuracy of the defect intelligent identification algorithm was tested by using the substation image database, and the pilot application verification was carried out for the intelligent operation and maintenance scene of the substation. The results of algorithm model accuracy test and the practical application showed that the intelligent identification accuracy of the equipment can meet the requirements of the intelligent patrol business of the substation. The equipment can realized the real-time collection, online intelligent recognition, and optimized streaming of multiple video streams in substations at the edge side. The intelligent level of substation’s maintenance can be significantly improved.