Monitoring data transmission method based on 5G

Abstract

The present invention relates to the technical field of data transmission, and in particular to a monitoring data transmission method based on 5G. The method determines the urgency by the change of information on the frame image, and uses the urgency to characterize the transmission importance of each frame image. When allocating resource blocks, not only the signal-to-noise ratio of the resource block is considered, but also the changing trend of the signal-to-noise ratio is considered. Considering that the frequency problem between resource blocks that are too close will cause frequency band interference, thereby affecting the stability of data transmission, the uplink priority is updated according to the distance between the unallocated and allocated resource blocks, and the allocation and transmission are performed according to the urgency and uplink priority during the allocation process. The present invention avoids the defects of channel congestion and intermodulation interference caused by resource preemption through reasonable resource allocation, and improves the transmission delay and transmission quality of monitoring data.

Description

Technical Field

[0001] The present invention relates to the technical field of data transmission, and in particular to a 5G-based monitoring data transmission method. Background Art

[0002] In scenes that need to be monitored, in order to achieve unmanned scene monitoring, images within the scene will be collected through image acquisition equipment. 5G transmission technology can take advantage of low latency to ensure the stability and real-time nature of monitoring data, thereby improving the management efficiency of monitoring scenes and reducing operation and maintenance costs.

[0003] During 5G transmission, due to the unequal power strength of the base station and the monitoring transmitter, the uplink and downlink links are unbalanced. Therefore, it is necessary to regulate the uplink transmission channel to improve the quality of the link between the monitoring transmitter and the base station. During 5G uplink transmission, since the power of the monitoring transmitter is relatively small, it is easily affected by small-scale fading in the wireless channel, and it is necessary to allocate uplink frequency selection resources. In the prior art, an uplink frequency selection method based on signal-to-noise ratio is adopted, but the selected frequencies are easily interfered with, or multiple terminals simultaneously occupy the better frequencies, causing channel congestion and intermodulation interference, resulting in poor uplink data transmission quality and high latency, and unable to guarantee the transmission stability and real-time performance of the monitoring data. Summary of the invention

[0004] In order to solve the technical problem that uplink frequency selection is performed based solely on the signal-to-noise ratio when 5G uplink transmits monitoring data, resulting in poor transmission stability and real-time performance of the monitoring data, the purpose of the present invention is to provide a monitoring data transmission method based on 5G, and the technical solution adopted is as follows:

[0005] The present invention proposes a monitoring data transmission method based on 5G, the method comprising:

[0006] The acquired surveillance video is transmitted to a video analysis transmission controller, wherein the surveillance video is composed of frame images at consecutive moments; for each moment, the urgency of the frame image at each moment is determined according to the information change on the frame image;

[0007] At each moment, for each resource block in the uplink channel of the 5G base station, the uplink priority of each resource block is determined according to the signal-to-noise ratio of the resource block and the signal-to-noise ratio change trend;

[0008] At each moment, all video analysis transmission controllers are sequentially allocated to resource blocks for uplink transmission according to the urgency level in accordance with an iterative allocation method; the iterative allocation method comprises: in each allocation process, the unallocated video analysis transmission controller with the highest urgency level is allocated to the resource block with the highest uplink priority; after the allocation is completed, the uplink priority of each unallocated resource block is updated according to the frequency difference between each unallocated resource block and the allocated resource block in the channel; after the update is completed, the next allocation is performed until all the video analysis transmission controllers are allocated.

[0009] Furthermore, the method for obtaining the urgency degree includes:

[0010] For each moment, a grayscale difference image is obtained based on the difference between the frame image and the frame image at the previous moment; the picture deviation degree is determined based on the size of the pixel value in the grayscale difference image; the local change degree is obtained based on the degree of distribution and aggregation of the pixel values ​​in the grayscale difference image; the urgency degree is obtained based on the picture deviation degree and the local change degree.

[0011] Furthermore, the method for obtaining the picture deviation degree includes:

[0012] The average pixel value in the grayscale difference image is used as the picture deviation degree.

[0013] Furthermore, the method for obtaining the local variation degree includes:

[0014] The absolute value of the skewness in the grayscale difference image is multiplied by the range in the grayscale difference image to obtain the local variation degree.

[0015] Furthermore, after obtaining the urgency, the method further includes:

[0016] The frame image in the video analysis transmission controller is divided into a plurality of data packets. For each data packet, the urgency of the corresponding frame image is embedded into the corresponding data packet as a label; and the data packet is transmitted during uplink transmission.

[0017] Furthermore, the method for obtaining the uplink priority includes:

[0018] For each moment, taking the moment as a starting point, searching forward for a preset number of historical moments to form a time period to be analyzed, and obtaining a signal-to-noise ratio sequence of each resource block in the time period to be analyzed; obtaining a trend weight according to the change trend information in the signal-to-noise ratio sequence; multiplying the trend weight by the signal-to-noise ratio at the current moment, and obtaining the uplink priority of the corresponding resource block at the current moment.

[0019] Furthermore, the method for obtaining the trend weight includes:

[0020] Performing STL decomposition on the signal-to-noise ratio sequence, obtaining the trend strength according to the trend item obtained by the decomposition; obtaining the slope of the fitting straight line of the signal-to-noise ratio sequence;

[0021] The trend strength and the slope are multiplied to obtain a change trend feature; the variance of the signal-to-noise ratio sequence is negatively correlated to obtain a change stability feature; and the trend weight is obtained according to the change trend feature and the change stability feature.

[0022] Furthermore, the method for updating the uplink priority includes:

[0023] For each unallocated resource block, the frequency distance between the unallocated resource block and the allocated resource block with the shortest frequency distance is used as an update weight, and the update weight is multiplied by the uplink priority before updating to obtain the updated uplink priority.

[0024] Furthermore, the video analysis transmission controller uses a traditional signal-to-noise ratio frequency selection method to determine a resource block for transmission within a preset initial time period of the transmission period.

[0025] Furthermore, the monitoring video is a monitoring video in an unmanned water pump room.

[0026] The present invention has the following beneficial effects:

[0027] The present invention first takes into account the particularity of monitoring data, because monitoring data is video data composed of continuous frame images, so it is transmitted in the frame image during the transmission process. For monitoring data, data at abnormal moments in the monitoring scene should be transmitted first, which is convenient for the management of the monitoring scene. Therefore, the present invention determines the urgency by the information change on the frame image, and uses the urgency to characterize the transmission importance of each frame image. Considering that the channel attenuation of the frequency point resource block in the uplink channel of the 5G base station is dynamically changing, not only the signal-to-noise ratio of the resource block is considered when allocating the resource block, but also the change trend of the signal-to-noise ratio is considered. Further considering that the frequency problem between resource blocks that are too close will cause frequency band interference, thereby affecting the stability of data transmission, the uplink priority is updated by the distance between the unallocated and allocated resource blocks, and the stability of monitoring data transmission can be guaranteed by allocating according to the urgency and uplink priority during the allocation process, and the defects of channel congestion and intermodulation interference caused by resource preemption are avoided through reasonable resource allocation, so as to improve the transmission delay and transmission quality of monitoring data. BRIEF DESCRIPTION OF THE DRAWINGS

[0028] In order to more clearly illustrate the technical solutions and advantages in the embodiments of the present invention or the prior art, the drawings required for use in the embodiments or the prior art descriptions are briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0029] Figure 1 A flow chart of a 5G-based monitoring data transmission method provided by an embodiment of the present invention;

[0030] Figure 2 A schematic diagram of a monitoring data 5G transmission process provided by an embodiment of the present invention;

[0031] Figure 3 A schematic diagram of data packet division provided by an embodiment of the present invention;

[0032] Figure 4 A schematic diagram of resource block allocation provided by an embodiment of the present invention;

[0033] Figure 5 The present invention is provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0034] In order to further explain the technical means and effects adopted by the present invention to achieve the predetermined invention purpose, the following is a detailed description of the specific implementation method, structure, characteristics and effects of a 5G-based monitoring data transmission method proposed by the present invention in combination with the accompanying drawings and preferred embodiments. In the following description, different "one embodiment" or "another embodiment" does not necessarily refer to the same embodiment. In addition, specific features, structures or characteristics in one or more embodiments may be combined in any suitable form.

[0035] Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs.

[0036] First, the prior art content involved in the embodiments of the present invention is introduced:

[0037] The embodiment of the present invention is mainly aimed at optimizing the 5G transmission process of monitoring data, please refer to Figure 2 , which shows a schematic diagram of a monitoring data 5G transmission process provided by an embodiment of the present invention, Figure 2 The system includes a monitoring camera 1, a video analysis transmission controller 2, a 5G wireless transmission channel 3, a 5G signal base station 4, a wired transmission line 5 between the base station and the cloud, a cloud storage for monitoring data 6, and a monitoring display controller 7. Figure 2As shown, first, the monitoring video of the monitoring scene is collected by the monitoring camera 1, and then the video analysis transmission controller 2 analyzes the monitoring video data and transmits it to the 5G signal base station 4 through the 5G wireless transmission channel 3, and then transmits the data to the cloud storage 6 of the monitoring data through the wired transmission line 5 between the base station and the cloud, and finally displays it visually in the monitoring display controller 7. The scenario targeted by the embodiment of the present invention is the process in which the video analysis transmission controller 2 analyzes the monitoring video data and transmits it to the 5G signal base station 4 through the 5G wireless transmission channel 3. In the uplink channel of the 5G base station, with a channel distance of 100M bandwidth, there are 273 RBs (Resource Blocks), each of which has a number in the bandwidth, which can be regarded as corresponding to a smaller bandwidth frequency, that is, a frequency point. The video analysis transmission controller (User Equipment, UE) can compress and encode the video data so that the wireless transmission channel can be transmitted stably.

[0038] See also Figure 1 , which shows a flow chart of a 5G-based monitoring data transmission method provided by an embodiment of the present invention, the method comprising:

[0039] Step S101: The acquired surveillance video is transmitted to the video analysis transmission controller, where the surveillance video is composed of frame images at consecutive moments; for each moment, the urgency of the frame image at each moment is determined according to the information change on the frame image.

[0040] In normal data uplink transmission, the 5G base station can assign different scheduling priorities according to the transmission task type of the terminal, for example, voice services have a higher priority, while services such as message mail have a lower priority. For the scenario of the embodiment of the present invention, all of them are monitoring video data, so it can be considered that the priorities of all video analysis transmission controllers are the same during the uplink transmission process.

[0041] However, for monitoring data, ensuring the monitoring quality of the scene is an important task. If an abnormality occurs in the monitoring scene, and the priority of all video analysis transmission controllers is the same at this time, the area where the abnormality occurs cannot be guaranteed to be stably and effectively transmitted to the monitoring terminal, and a large delay is generated during the transmission process, resulting in a lag in the monitoring data. Considering that the monitoring video is composed of frame images at continuous moments, each frame image corresponds to a collection moment, so for each frame image at each moment, if the monitoring scene is normal, the image information on the frame image is relatively stable; if the monitoring scene is abnormal, there will be significantly different image information in the frame image. Therefore, the urgency of the frame image at each moment can be determined according to the information changes on the frame image. The greater the urgency, the more the current frame image needs to be preferentially transmitted, and the corresponding video analysis transmission controller needs to allocate it to the resource block with good transmission quality when allocating frequency points in the subsequent period.

[0042] In a specific implementation of the embodiment of the present invention, the frame rate of the monitoring video is 30, that is, 30 frames of images are collected per second.

[0043] Preferably, in one embodiment of the present invention, in order to ensure the integrity of the data, the traditional frequency selection method is still used to determine the resource block and transmit it in the initial stage of the monitoring video transmission, that is, the embodiment of the present invention presets the initial time period, and the video analysis transmission controller uses the traditional signal-to-noise ratio frequency selection method to determine the resource block for transmission during the initial time period of the transmission period. It should be noted that the traditional signal-to-noise ratio frequency selection method is a technical means well known to those skilled in the art and will not be described in detail here. In a specific implementation of the embodiment of the present invention, the initial time period is set to 2 seconds.

[0044] Preferably, in one embodiment of the present invention, considering that the moment when the abnormality occurs or the moment when the abnormality further changes should be the moment of focus, the method for obtaining the urgency includes:

[0045] For each moment, a grayscale differential image is obtained based on the difference between the frame image and the frame image at the previous moment. If both frame images represent normal monitoring scenes, the image information is not much different, and the pixel values ​​in the grayscale differential image are close to 0; on the contrary, if the current moment is the moment when the abnormality occurs or the moment when the abnormality further changes, the obtained grayscale differential image has obvious high pixel value information, which indicates that there is an obvious abnormality at the current moment. Therefore, the urgency can be further determined based on the pixel information in the grayscale differential image.

[0046] The image deviation is determined according to the pixel value in the grayscale difference image, that is, the larger the pixel value, the more obvious the abnormality and the greater the urgency.

[0047] Further consideration is given that the light changes in the monitoring scene will cause a more obvious brightness change in the frame image at a certain moment, which in turn leads to a larger pixel value in the grayscale difference image. However, the changes in this case are relatively uniform, that is, each position in the image has a larger pixel value. Therefore, in order to eliminate the influence of light on the image, the local variation degree is obtained according to the degree of aggregation of the pixel value distribution in the grayscale difference image. That is, the larger the local variation degree, the more concentrated the anomaly in the frame image at the current moment is in a certain local area, and the more the picture difference at this time is due to the difference in the monitoring scene caused by the anomaly.

[0048] Therefore, the urgency is obtained according to the picture deviation and the local change. That is, the greater the picture deviation and the local change, the greater the urgency of the frame image at the current moment.

[0049] Furthermore, in some implementations of the embodiments of the present invention, the picture deviation may be an average pixel value in the grayscale difference image, that is, a larger average pixel value indicates a greater information change between two frames of images.

[0050] In some other implementations of the embodiments of the present invention, the image deviation degree may also be the mode of pixel values ​​in the grayscale difference image, and the mode is used to represent the overall information difference.

[0051] Furthermore, in some implementations of the embodiments of the present invention, the method for obtaining the local variation degree includes:

[0052] The absolute value of the skewness in the grayscale difference image is multiplied by the range in the grayscale difference image to obtain the local variation. The range is the difference between the maximum pixel value and the minimum pixel value in the grayscale difference image, that is, the larger the range, the more uneven the information change in the current frame image, and the stronger the change, the greater the local variation; the larger the absolute value of the skewness, the more the pixel value distribution in the grayscale difference image is biased towards a certain local information, and the greater the local variation. Therefore, the local variation is obtained by merging the two feature data by multiplication.

[0053] In some implementations of the embodiments of the present invention, the urgency of the corresponding frame image can be obtained by multiplying the picture deviation degree and the local change degree and then performing normalization processing.

[0054] It should be noted that the grayscale difference image acquisition method is to perform a subtraction of the grayscale images of two frame images, which is a technical means well known to those skilled in the art and will not be described in detail here. Also, skewness, range, and averaging are all technical means well known to those skilled in the art and will not be described in detail here.

[0055] Preferably, in one embodiment of the present invention, considering that the amount of image data of a single frame is large, in order to facilitate transmission, after obtaining the urgency, the method further includes:

[0056] The frame image in the video analysis transmission controller is divided into multiple data packets. For each data packet, the urgency of the frame image is embedded in the corresponding data packet as a label; when performing uplink transmission, the data packet is transmitted. Figure 3 , which shows a schematic diagram of data packet division provided by an embodiment of the present invention, it should be noted that Figure 3 Taking the division of three data packets as an example, in actual scenarios, a frame image can be divided into multiple data packets. Figure 3 A represents the data sequence after the video analysis transmission controller encodes and compresses the frame image, #1 represents the first data packet, #2 represents the second data packet, and #3 represents the third data packet. Taking the first data packet as an example, it is divided into a main part B and a label part C, wherein the label part C contains an urgency label.

[0057] It should be noted that, in one embodiment of the present invention, the normalized urgency is further divided into 8 levels, and 8 converted into binary is 2 to the cube, so that each urgency label only occupies 3 bits of information.

[0058] Step S102: At each moment, for each resource block in the uplink channel of the 5G base station, the uplink priority of each resource block is determined according to the signal-to-noise ratio of the resource block and the signal-to-noise ratio change trend.

[0059] In the traditional uplink frequency selection allocation based on signal-to-noise ratio, only the attenuation of the uplink channel at the current moment is used to select resource blocks with smaller attenuation, that is, larger signal-to-noise ratio for frequency selection allocation. However, since the attenuation of the channel changes dynamically, it is easily affected by the small-scale fading of the channel conditions, which makes most of the data that the video analysis transmission controller needs to upload occupy the better resource blocks, thereby causing unreasonable resource allocation and low spectrum efficiency. The embodiment of the present invention first optimizes the frequency selection method of the resource block, considering that the resource blocks that can serve as emergency data transmission under ideal circumstances should be able to maintain a stable uplink attenuation channel or the signal-to-noise ratio of the resource block gradually increases for a continuous period of time, indicating that the transmission interference of the resource block on the 5G uplink channel is relatively small at this time. Therefore, for each resource block at each moment, not only its signal-to-noise ratio is considered, but also the uplink priority of each resource block is determined in combination with its signal-to-noise ratio change trend.

[0060] Preferably, in one embodiment of the present invention, the method for acquiring the uplink priority includes:

[0061] For each moment, starting from the moment, search forward for a preset number of historical moments to form the time period to be analyzed, and obtain the signal-to-noise ratio sequence of each resource block in the time period to be analyzed. By quantizing the signal-to-noise ratio sequence, it is easier to analyze the signal-to-noise ratio change trend information of each resource block at the current moment, and then obtain the trend weight according to the change trend information in the signal-to-noise ratio sequence; multiply the trend weight by the signal-to-noise ratio at the current moment to obtain the uplink priority of the corresponding resource block at the current moment.

[0062] Furthermore, the method for obtaining the trend weight includes:

[0063] Perform STL decomposition on the signal-to-noise ratio sequence, and obtain the trend strength according to the trend item obtained by the decomposition; obtain the slope of the fitting line of the signal-to-noise ratio sequence. The greater the trend strength, the greater the magnitude of the change in the resource block at this time, and the more obvious the change trend; and the slope of the fitting line has obvious positive and negative signs, a positive value represents an increase in the signal-to-noise ratio, and a negative value represents a decrease in the signal-to-noise ratio. At the same time, the value of the slope can also characterize the magnitude of the change trend. Therefore, multiply the trend strength and the slope to obtain the change trend characteristics. The greater the change trend characteristics, the more likely the signal-to-noise ratio of the resource block is to change towards a significantly increasing trend; conversely, it is more likely to change towards a significantly decreasing trend.

[0064] Further analyze the stability of the change trend, map the variance of the signal-to-noise ratio sequence in a negative correlation, and obtain the change stability feature. Obtain the trend weight based on the change trend feature and the change stability feature. That is, the more obviously and stably the resource block can rise at the current moment, the higher the uplink priority of the resource block should be, and the greater the trend weight; conversely, the more unstable the channel quality of the current resource block is, the lower the uplink priority should be, and the smaller the trend weight.

[0065] As an example, in one embodiment of the present invention, the formula of the uplink priority is expressed as:

[0066] ; Where D is the uplink priority of the resource block at the current moment, is the signal-to-noise ratio of the resource block at the current moment, is the trend strength of the signal-to-noise ratio series, is the slope of the fitting line of the signal-to-noise ratio series, is the variance of the signal-to-noise ratio sequence, exp() is an exponential function with a natural constant as the base, and norm() is a normalization function. That is, in this formula, the trend characteristics are numerically mapped through an exponential function with a natural constant as the base, and the variance is negatively correlated in the form of a reciprocal, and then the two are multiplied and normalized to obtain the trend weight.

[0067] It should be noted that, in one embodiment of the present invention, the fitting method of the fitting line adopts the least square method for fitting. The least square method fitting and the trend strength method obtained by STL decomposition are both well-known technical means to those skilled in the art, and will not be described in detail here.

[0068] Step S103: at each moment, all video analysis transmission controllers are sequentially allocated to resource blocks according to the urgency level and in accordance with an iterative allocation method for uplink transmission.

[0069] At each moment, the transmission data of the current video analysis transmission controller can be sorted according to the urgency, and the resource blocks can also be sorted according to the size of the uplink priority. Data with greater urgency should be transmitted through resource blocks with greater uplink priority, but considering that there will be frequency interference between resource blocks, if two resource blocks with similar frequencies are transmitting data, intermodulation interference will be generated due to the similar frequencies, affecting the transmission quality. Therefore, the channel resource allocation method of the embodiment of the present invention is not a simple corresponding allocation, but an iterative update allocation. In each allocation process, the unallocated and most urgent video analysis transmission controller is allocated to the resource block with the largest uplink priority, and after this allocation, the uplink priority of each unallocated resource block is updated according to the frequency difference between each unallocated resource block and the allocated resource block in the channel. That is, the smaller the frequency difference, the closer the frequency distance between the unallocated resource block and the allocated resource block, the more likely it is to cause intermodulation interference, and it is necessary to adjust the uplink priority of the unallocated resource block to facilitate the next allocation. Transmission can be carried out until all video analysis transmission controllers have completed the allocation.

[0070] As an example, see Figure 4 , which shows a schematic diagram of resource block allocation provided by an embodiment of the present invention. It should be noted that there are multiple resource blocks in actual situations. For the convenience of illustration, Figure 4 Only three resource blocks are used as an example. Figure 4 In the figure, the horizontal axis is the number of resource blocks, and the vertical axis is SINR (signal-to-noise ratio). The uplink priority calculated by the signal-to-noise ratio and the change trend is RB187, RB130, and RB41. At this time, there are three video analysis transmission controllers UE1, UE2, and UE3. The data urgency of these three video analysis transmission controllers is still ranked as UE1, UE2, and UE3. In the iterative allocation process, UE1 is first allocated to RB187, and then the uplink priority of RB130 and RB41 is updated according to the frequency distance between RB187 and RB187. The uplink priority after the update is ranked as RB41 and RB130. UE2 is allocated to RB41, and UE3 is allocated to RB130 to complete the uplink channel resource allocation.

[0071] Preferably, in one embodiment of the present invention, the method for updating the uplink priority includes:

[0072] For each unallocated resource block, the frequency distance between the unallocated resource block and the allocated resource block with the closest frequency distance is used as an update weight, and the update weight is multiplied by the uplink priority before updating to obtain the updated uplink priority.

[0073] It should be noted that the frequency distance can be calculated directly through the frequency interval represented by the resource blocks, or can be represented by the number difference of the resource blocks in the bandwidth.

[0074] In summary, the embodiments of the present invention determine the urgency by the change of information on the frame image, and use the urgency to characterize the importance of transmission of each frame image. Considering that the channel attenuation of the frequency resource blocks in the uplink channel of the 5G base station changes dynamically, not only the signal-to-noise ratio of the resource blocks but also the change trend of the signal-to-noise ratio are considered when allocating resource blocks. Further considering that the frequency problem between resource blocks that are too close will cause frequency band interference, thus affecting the stability of data transmission, the uplink priority is updated by the distance between the unallocated and allocated resource blocks. During the allocation process, the allocation is performed according to the urgency and uplink priority to ensure the stability of monitoring data transmission. Please refer to Figure 5 , which shows a schematic diagram of effect comparison provided by an embodiment of the present invention. Figure 5 The dark curve in the middle is the delay curve of the traditional SINR uplink frequency selection algorithm, and the light curve is the delay curve of this solution. The horizontal axis of the curve is the number of UE terminals of the video analysis transmission controller, and the vertical axis is the delay, and the unit is milliseconds. Figure 5 By comparison, it can be seen that the transmission delay of the embodiment of the present invention is significantly smaller than the delay in the prior art, which can significantly increase the stability and real-time performance of monitoring data during 5G transmission.

[0075] Furthermore, in one embodiment of the present invention, the transmitted monitoring video is a monitoring video of an unmanned water pump room. By effectively transmitting the monitoring video of the unmanned water pump room, the management efficiency of the unmanned water pump room can be improved.

[0076] It should be noted that the sequence of the above embodiments of the present invention is only for description and does not represent the advantages and disadvantages of the embodiments. The processes depicted in the accompanying drawings do not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0077] The various embodiments in this specification are described in a progressive manner, and the same or similar parts between the various embodiments can be referenced to each other, and each embodiment focuses on the differences from other embodiments.

Claims

1. A monitoring data transmission method based on 5G, characterized in that: The method comprises: The acquired surveillance video is transmitted to a video analysis transmission controller, wherein the surveillance video is composed of frame images at consecutive moments; for each moment, the urgency of the frame image at each moment is determined according to the information change on the frame image; At each moment, for each resource block in the uplink channel of the 5G base station, the uplink priority of each resource block is determined according to the signal-to-noise ratio of the resource block and the signal-to-noise ratio change trend; At each moment, all video analysis transmission controllers are sequentially allocated to resource blocks for uplink transmission according to the urgency level in accordance with an iterative allocation method; the iterative allocation method comprises: in each allocation process, the unallocated video analysis transmission controller with the highest urgency level is allocated to the resource block with the highest uplink priority; after the allocation is completed, the uplink priority of each unallocated resource block is updated according to the frequency difference between each unallocated resource block and the allocated resource block in the channel; after the update is completed, the next allocation is performed until all the video analysis transmission controllers are allocated.

2. The 5G-based monitoring data transmission method according to claim 1, characterized in that: The method for obtaining the urgency degree includes: For each moment, a grayscale difference image is obtained based on the difference between the frame image and the frame image at the previous moment; the picture deviation degree is determined based on the size of the pixel value in the grayscale difference image; the local change degree is obtained based on the degree of distribution and aggregation of the pixel values ​​in the grayscale difference image; the urgency degree is obtained based on the picture deviation degree and the local change degree.

3. The 5G-based monitoring data transmission method according to claim 2, characterized in that: The method for obtaining the picture deviation degree includes: The average pixel value in the grayscale difference image is used as the picture deviation degree.

4. The 5G-based monitoring data transmission method according to claim 2, characterized in that: The method for obtaining the local variation degree includes: The absolute value of the skewness in the grayscale difference image is multiplied by the range in the grayscale difference image to obtain the local variation degree.

5. The 5G-based monitoring data transmission method according to claim 1, characterized in that: After obtaining the urgency, the method further includes: The frame image in the video analysis transmission controller is divided into a plurality of data packets. For each data packet, the urgency of the corresponding frame image is embedded into the corresponding data packet as a label; and the data packet is transmitted during uplink transmission.

6. The 5G-based monitoring data transmission method according to claim 1, characterized in that: The method for obtaining the uplink priority includes: For each moment, taking the moment as a starting point, searching forward for a preset number of historical moments to form a time period to be analyzed, and obtaining a signal-to-noise ratio sequence of each resource block in the time period to be analyzed; obtaining a trend weight according to the change trend information in the signal-to-noise ratio sequence; multiplying the trend weight by the signal-to-noise ratio at the current moment, and obtaining the uplink priority of the corresponding resource block at the current moment.

7. The 5G-based monitoring data transmission method according to claim 6, characterized in that: The method for obtaining the trend weight includes: Performing STL decomposition on the signal-to-noise ratio sequence, obtaining the trend strength according to the trend item obtained by the decomposition; obtaining the slope of the fitting straight line of the signal-to-noise ratio sequence; The trend strength and the slope are multiplied to obtain a change trend feature; the variance of the signal-to-noise ratio sequence is negatively correlated to obtain a change stability feature; and the trend weight is obtained according to the change trend feature and the change stability feature.

8. The 5G-based monitoring data transmission method according to claim 1, characterized in that: The method for updating the uplink priority includes: For each unallocated resource block, the frequency distance between the unallocated resource block and the allocated resource block with the shortest frequency distance is used as an update weight, and the update weight is multiplied by the uplink priority before updating to obtain the updated uplink priority.

9. The 5G-based monitoring data transmission method according to claim 1, characterized in that: The video analysis transmission controller uses a traditional signal-to-noise ratio frequency selection method to determine resource blocks for transmission within a preset initial time period of the transmission period.

10. The 5G-based monitoring data transmission method according to any one of claims 1 to 9, characterized in that: The monitoring video is a monitoring video in an unmanned water pump room.

Images