# A Multidimensional Data Collection and Edge Computing Analysis Method
## 3 Overall System Architecture and Improved Target Detection Model
### Public Space Parameter Acquisition and Data Visualization  
After the accurate detection of the targets obtained in machine vision in the previous section, we can recognize all the people in the public space. Due to the limitations of the edge computing platform's own computing power, we can extract screenshots from the video file at time intervals to form a file stream for identification and positioning. The size of the same target in the image is varied due to the difference of the distance between the target and the camera in the image. We use GPS sensors to calibrate the position of the camera during the actual installation of the camera to provide a reference for the successive parameter extraction. The data acquired by the GPS sensor is mapped to the position coordinates of the corresponding target in the image, and the distance between the target and the camera and the height of the target are essentially computed by the coordinate position. Figure 10a,b illustrates the 3D and 2D plan view of the whole parameter calculation process, and the specific calculation is derived from Figure 10c,d. In the completion of the recognition function, a part is used to frame the recognized target, and the pixel height of the recognized target in the image can be retrieved, and the pixel coordinates of the upper left corner of the frame can also be obtained. The principle of selecting the reference object to determine the distance is: for example, the height of the selected reference object at the same angle in the actual scene is H (cm), the distance from the camera in the actual scene is D, and the pixel height in the image is h, we assume pedestrian height Hr: 170 cm, it can be retrieved from the program that the pedestrian height is Ht. According to a similar ratio, the distance between the pedestrian and the camera can be obtained as (14):  
\[d=(L\times H)/(H_{r}\times h)\times D \tag{14}\]  
In the actual scene, the actual height D of the camera can be retrieved, which is the distance between the target and the lower part of the camera, as shown in Figure 10a. The principle of determining the target position: We can retrieve the coordinates of the upper left corner of the recognition frame in the recognition program, compare the pixel coordinates in the image with the pixel width of the entire image, and then obtain the target distance from the center below the camera according to the width in the actual scene. For the distance of the line, and then for the distance between the actual distance and the center line, use the Pythagorean theorem to calculate the actual position. In this project, the parameters of a scene are actually selected for data calibration and verification. The actual height of the reference object is 200 cm, the pixel height is 337, the actual distance is 12 m, the scene width is 15 m, and the length is 30 m. The calculation principles of parameters in different scenes in the community are compatible. \begin{table}
\begin{tabular}{c c c c c c c c} \hline \hline
**Map** & **a** & **None** & **0.9** & **0.6** & **0.5** & **0.4** & **0.3** & **0.2** \\ \hline None & 90.94\% & 90.19\% & 91.10\% & 91.32\% & 91.56\% & 91.71\% & 91.11\% \\
1.1 & 91.25\% & 90.95\% & 91.58\% & 91.67\% & 91.87\% & 91.92\% & 91.51\% \\
1.2 & 90.27\% & 90.15\% & 90.77\% & 91.06\% & 91.22\% & 91.36\% & 90.82\% \\
1.3 & 91.19\% & 91.08\% & 91.37\% & 91.72\% & 92.02\% & 92.21\% & 91.31\% \\
1.4 & 91.54\% & 91.42\% & 91.88\% & 92.13\% & 92.25\% & 92.33\% & 91.51\% \\
1.5 & 92.27\% & 92.21\% & 92.52\% & 92.79\% & 92.85\% & **92.92**\% & 92.83\% \\
1.6 & 90.56\% & 90.05\% & 91.02\% & 91.29\% & 91.33\% & 91.89\% & 91.01\% \\
1.7 & 91.71\% & 91.56\% & 91.87\% & 91.95\% & 92.17\% & 92.36\% & 91.85\% \\
1.8 & 91.63\% & 91.45\% & 91.75\% & 91.81\% & 92.11\% & 92.23\% & 91.77\% \\
1.9 & 89.46\% & 89.37\% & 90.19\% & 90.55\% & 90.82\% & 91.07\% & 90.84\% \\ \hline \hline \end{tabular}
\end{table} 
Table 2: The effect of k and a on accuracy. Maximum values are in bold.