Object detection is an essential subject in the field of computer vision. It is widely used in various scenes and greatly shares the work of human beings. In view of the lack of real-time performance of pedestrian detection in the field of object detection and the excessive load of data returned by the central server in the cloud computing environment, this paper proposes an improved SSD model under the edge computing architecture. The intelligent mobile terminal completes the real-time data collection, and the edge server undertakes the preliminary calculation, The cloud server is responsible for complex computing and model training. The SSD algorithm is lightweight improved to better adapt to the performance of the edge server. The idea of feature pyramid is introduced to fuse the semantic information carried by the deep feature map with the shallow feature map to improve the detection accuracy of small objects. Through experiments, the model has achieved about 0.72 map and about 0.034s single frame processing speed, which can be applied to real life.
With the development of aviation industry, the aviation industry system needs more and more high bandwidth, high reliability, real-time performance and high fault tolerance. Under this background, TTE came into being. This paper studies the time-triggered Ethernet SAE AS6802 protocol, and the synchronization design method of SM, SC and CM is designed. The simulation results show that the synchronization design meets the clock synchronization accuracy requirements of time-triggered Ethernet.
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