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Traffic flow data is the basic data for the macro decision of traffic management, and the traffic flow data collection system is an important part of the traffic management information intelligence. With the vigorous development of China's traffic field, traffic flow surge, high-speed traffic congestion, traffic accidents and other emergencies occur frequently. Therefore, it is very necessary to design a traffic flow data collection system with good real-time and high accuracy. This paper develops a set of highway traffic flow data acquisition system based on the all-in-one machine, using the Internet of T architecture of terminal-edge-cloud hierarchical transmission. Moreover, the system combines the independently developed radar video all-one machine and uses CNN neural network technology to extract image information. Then, the edge computer optimizes the information extracted from the radar and the monitoring camera through the data workflow of one-dimensional data optimal estimation, multi-sensor data matching, multi-sensor bidirectional optimal estimation, and multi-sensor target feature fusion, to accurately extract the road target traffic information. Finally, the system uploads the processed feature information to the cloud server to realize the accurate and real-time collection of traffic flow data. The system test operation results show that the traffic flow data acquisition system based on radar video all-one machine can effectively improve the detection accuracy and strengthen the real-time performance of the detection results.