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Nowadays, with the rapid development of science and technology, more and more factories and enterprises are also growing. In order to obtain more profits, these factories and enterprises need to reduce their production costs, which make the improvement and development of automatic control technology on the agenda. The automatic control system can reduce the production cost and system operation cost to a great extent. This kind of automatic control system not only promotes the progress of social economy, but also reduces the possibility of accidents, which greatly guarantees people’s life safety. Therefore, this paper analyzes and discusses the current situation and future development trend of electrical automation engineering control system. Firstly, the composition of electrical automation engineering control system is introduced and explained. Then, this paper analyzes which fields this control system has been applied in our country and the specific benefits it brings. Finally, it forecasts its future development and gives relevant suggestions. The results show that the workers have a positive attitude towards the electrical automation engineering control system, and the electrical automation engineering control system can reduce the cost of the factory and improve the income.

The spiritual breath is industrial knowledge, the number of people, the number of people, the data knowledge, the method, and the polymorphism. The amount of data possessed by human beings is getting larger and larger. There may be a lot of information that we are interested in hiding behind the amount of data. How to effectively use digital technology to mine this information has become a problem to be solved. There are two core technologies in digital technology, data mining technology and data fusion technology. The purpose of this article is to conduct research and analysis based on (BO) the teaching reform of big data ideological and political (IAP) courses. This paper recommends using the traditional algorithm FP-growth algorithm to solve the digital technology problems commonly used in big data. The FP growth algorithm has the widest range of applications. Compress the transaction database into the FP tree for processing. It also uses the Aprili algorithm. Instead of generating frequent candidate itemsets, you only need to scan the database twice. The improvement of the experimental results shows that in the IAP courses BO big data studied in this article, students recognize and like educational reforms. The degree of students’ love of the course has increased by about 90%, which has played an important role in improving students’ concentration on the course.

The human behavior datasets have the characteristics of complex background, diverse poses, partial occlusion, and diverse sizes. Firstly, this paper adopts YOLO v3 and YOLO v4 algorithms to detect human objects in videos, and qualitatively analyzes and compares detection performance of two algorithms on UTI, UCF101, HMDB51 and CASIA datasets. Then, this paper proposed an improved YOLO v4 algorithm since the vanilla YOLO v4 has incomplete human detection in specific video frames. Specifically, the improved YOLO v4 introduces the Ghost module in the CBM module to further reduce the number of parameters. Lateral connection is added in the CSP module to improve the feature representation capability of the network. Furthermore, we also substitute MaxPool with SoftPool in the primary SPP module, which not only avoids the feature loss, but also provides a regularization effect for the network, thus improving the generalization ability of the network. Finally, this paper qualitatively compares the detection effects of the improved YOLO v4 and primary YOLO v4 algorithm on specific datasets. The experimental results show that the improved YOLO v4 can solve the problem of complex targets in human detection tasks effectively, and further improve the detection speed.

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