Bank remote monitoring video acquisition system and method thereof

Abstract

The application relates to the field of electric communication technology, in particular to a bank remote monitoring video acquisition system and a method thereof, which comprises the following steps: acquiring a maximum time delay, a jitter value and a packet loss rate of a bank remote monitoring video transmission in a first predetermined period before a current time; determining the instability degree of a network in the first predetermined period according to the maximum time delay, the jitter value and the packet loss rate; determining a first adjustment redundancy rate of the current time; determining a real-time video code rate of the current time according to the CPU total load, the CPU load in the first predetermined period, the first adjustment redundancy rate of each time in the first predetermined period and the real-time video code rate of the current time, and performing forward error correction processing on the remote monitoring video transmitted at the current time based on the first adjustment redundancy rate and the real-time video code rate. The application improves the setting accuracy of the redundancy rate parameter, and further optimizes the smooth transmission effect of the video.

Description

Technical Field

[0001] This invention relates to the field of telecommunications technology, specifically to a remote monitoring video acquisition system and method for banks. Background Technology

[0002] In the financial security system, bank monitoring systems serve as the core infrastructure for risk prevention and incident tracing, placing stringent requirements on the real-time performance, continuity, and stability of video transmission. The network environment in bank monitoring scenarios is often complex and variable. Some branches and self-service outlets are located in remote areas, relying on broadband or dedicated wireless networks for data transmission. Data transmission between the core data center and various outlets requires traversing multiple network links, and issues such as link congestion and device forwarding delays frequently occur, all leading to data packet loss. Video streams consist of continuous data packets; even a small amount of packet loss can cause screen stuttering, glitches, or buffer interruptions.

[0003] In some scenarios, forward error correction (FEC) technology can effectively reduce video stuttering frequency and ensure transmission continuity by embedding redundant information in data packets, enabling the receiving end to autonomously recover lost data without requesting retransmission. However, current mainstream FEC implementations have technical limitations: their redundancy rate adjustments are based solely on unstable parameters such as the current network packet loss rate and latency, lacking consideration for system resource capacity. Furthermore, adding and parsing redundant information requires the terminal's central processing unit (CPU) computing power, and a higher redundancy rate results in a larger data transmission volume, consuming more bandwidth resources and increasing CPU load. When network fluctuations intensify, traditional methods blindly increase the redundancy rate to combat packet loss without assessing whether the current CPU can handle the additional computational pressure. If the CPU load is already close to its limit, an excessively high redundancy rate will increase data parsing latency, potentially causing new video stuttering; conversely, insufficient redundancy rate adjustment cannot effectively mitigate the impact of packet loss. Therefore, the traditional approach, which focuses only on network status and ignores the matching of system resources, results in insufficient accuracy in redundancy parameter settings. Ultimately, it fails to achieve the ideal smooth video transmission effect and cannot meet the transmission quality requirements of bank monitoring. Summary of the Invention

[0004] To address the technical problem of insufficient accuracy in setting redundancy rate parameters, which leads to poor video transmission performance, the present invention aims to provide a remote monitoring video acquisition system and method for banks.

[0005] To solve the above technical problems, the specific technical solution adopted is as follows:

[0006] In a first aspect, embodiments of the present invention provide a method for acquiring remote monitoring video of a bank, comprising: acquiring the maximum latency, jitter value, and packet loss rate of remote monitoring video transmission of the bank within a first predetermined time period prior to the current moment; determining the network instability within the first predetermined time period based on the maximum latency, jitter value, and packet loss rate; determining a first adjustment redundancy rate at the current moment based on the total CPU load at the current moment and all moments within the first predetermined time period, the CPU load during remote monitoring video transmission at the current moment, and the network instability; determining the real-time video bitrate at the current moment based on the total CPU load at the current moment and all moments within the first predetermined time period, the CPU load, and the first adjustment redundancy rate at each moment within the first predetermined time period; and performing forward error correction processing on the remote monitoring video transmitted at the current moment based on the first adjustment redundancy rate and the real-time video bitrate.

[0007] Optionally, determining the network instability level within the first predetermined time period based on the maximum latency, jitter value, and packet loss rate includes: determining the network congestion level within the first predetermined time period based on the maximum latency and jitter value; and determining the network instability level within the first predetermined time period based on the packet loss rate and network congestion level.

[0008] Optionally, determining the network congestion level within the first predetermined time period based on the maximum latency and jitter value includes: obtaining the maximum latency of the bank's remote monitoring video transmission at the current time and within the first predetermined time period adjacent to the current time, as well as the maximum jitter value among all jitter values ​​within the first predetermined time period before the current time; and determining the network congestion level within the first predetermined time period adjacent to the current time based on the maximum latency, the jitter value within the first predetermined time period, and the maximum jitter value.

[0009] Optionally, determining the network instability within a first predetermined time period based on packet loss rate and network congestion level includes: determining the maximum packet loss rate among all packet loss rates within the first predetermined time periods before the current time, and the maximum network congestion level among all network congestion levels within the first predetermined time periods before the current time; and determining the network instability within a first predetermined time period adjacent to the current time based on the packet loss rate and network congestion level, the maximum packet loss rate, and the maximum network congestion level of the first predetermined time periods adjacent to the current time before the current time.

[0010] Optionally, determining the first adjusted redundancy rate for the current moment based on the total CPU load at the current moment and all moments within the first predetermined time period, the CPU load during remote monitoring video transmission at the current moment, and the network instability includes: determining the first increase in redundancy rate at the current moment based on the total CPU load at the current moment and all moments within the first predetermined time period, the CPU load during remote monitoring video transmission at the current moment, and the network instability during the first predetermined time period; adjusting the initial redundancy rate during remote monitoring video transmission at the current moment based on the first increase in redundancy rate to obtain a second adjusted redundancy rate; determining the second increase in redundancy rate at the current moment to meet future changes based on the second adjusted redundancy rate at the current moment and the second adjusted redundancy rates at all moments within the second predetermined time period prior to the current moment; and adjusting the second adjusted redundancy rate at the current moment again using the second increase in redundancy rate to obtain the first adjusted redundancy rate at the current moment.

[0011] Optionally, determining the first increase in redundancy rate at the current moment based on the total CPU load at the current moment and all moments within the first predetermined time period, the CPU load during remote monitoring video transmission at the current moment, and the network instability within the first predetermined time period includes: determining the minimum total CPU load among the total CPU loads at the current moment and all moments within the first predetermined time period; and determining the first increase in redundancy rate at the current moment based on the total CPU load at the current moment, the minimum total CPU load, the CPU load, and the network instability within the first predetermined time period.

[0012] Optionally, determining the second increase in the redundancy rate to meet future changes at the current time, based on the second adjustment redundancy rate at the current time and the second adjustment redundancy rates at all times within the second predetermined time period prior to the current time, includes: determining a first difference between the second adjustment redundancy rates at the current time and at adjacent times within the second predetermined time period prior to the current time, wherein the first difference is the difference between the second adjustment redundancy rate at the later time and the second adjustment redundancy rate at the previous time; determining a first number of all first differences that are greater than a preset value and a second number of all first differences; determining a second difference between the second adjustment redundancy rate at the current time and the second adjustment redundancy rate at the earliest time within the second predetermined time period; and determining the second increase in the redundancy rate to meet future changes at the current time based on the first number, the second number, and the second difference.

[0013] Optionally, determining the real-time video bitrate at the current moment based on the total CPU load, CPU load, and first adjustment redundancy rate at each moment within the first predetermined time period, including: determining the degree of video bitrate reduction during remote monitoring video transmission at the current moment based on the total CPU load, CPU load during remote monitoring video transmission at the current moment, and first adjustment redundancy rate at each moment within the first predetermined time period; adjusting the video bitrate reference value based on the degree of video bitrate reduction to obtain the real-time video bitrate at the current moment.

[0014] Optionally, determining the degree of video bitrate reduction during remote monitoring video transmission at the current moment, based on the total CPU load at the current moment and all moments within the first predetermined time period, the CPU load during remote monitoring video transmission at the current moment, and the first adjustment redundancy rate at each moment within the current moment and the first predetermined time period, includes: determining the minimum total CPU load among the total CPU loads at the current moment and all moments within the first predetermined time period, and the maximum adjustment redundancy rate among the first adjustment redundancy rates at each moment within the current moment and the first predetermined time period; and determining the degree of video bitrate reduction during remote monitoring video transmission at the current moment based on the total CPU load at the current moment, the minimum total CPU load, the CPU load, the maximum adjustment redundancy rate, and the first adjustment redundancy rate at the current moment.

[0015] In a second aspect, embodiments of the present invention provide a bank remote monitoring video acquisition system, comprising: a processor and a memory; wherein the memory is used to store a computer program that can run on the processor; the processor is used to execute the program stored in the memory to implement the steps of the bank remote monitoring video acquisition method mentioned in the first aspect.

[0016] The present invention has the following beneficial effects: Based on feedback from basic information such as maximum latency, jitter, and packet loss rate during remote monitoring video frame transmission, the embodiments of the present invention analyze the stability of the network during video transmission. This allows for more accurate capture of historical patterns and current trends in network fluctuations, providing reliable data support for redundancy rate adjustment. Furthermore, the present invention incorporates CPU load into the redundancy rate adjustment considerations. By combining the total CPU load at the current moment and within a first predetermined time period, as well as the dedicated CPU load during video transmission, a first adjustment redundancy rate is determined based on an assessment of network instability. This effectively avoids the CPU overload problem caused by blindly increasing the redundancy rate in traditional solutions. It can both appropriately increase redundancy to combat packet loss during network fluctuations and control redundancy overhead through CPU load constraints, achieving a dynamic balance between network packet loss resistance requirements and CPU carrying capacity, thus improving the accuracy of redundancy rate parameter settings. Furthermore, this invention determines the real-time video bitrate by integrating CPU load and redundancy rate data, and then combines this with forward error correction processing based on the first adjustment of the redundancy rate, forming a dual optimization mechanism for redundancy rate and bitrate. On the one hand, precise redundancy rate adjustment significantly reduces video stuttering under unstable networks, ensuring the continuity and real-time performance of monitoring videos and achieving ideal smooth video transmission. On the other hand, dynamically adapted video bitrate can match the current network bandwidth and CPU performance while maintaining video clarity to meet monitoring requirements, avoiding transmission pressure caused by excessively high bitrate or image blurring caused by excessively low bitrate. Attached Figure Description

[0017] To more clearly illustrate the technical solutions and advantages in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0018] Figure 1 A flowchart illustrating a method for remote monitoring and video acquisition in a bank, as provided in one embodiment of the present invention;

[0019] Figure 2 This is a schematic diagram of the structure of a remote monitoring video acquisition system for banks, provided in one embodiment of the present invention. Detailed Implementation

[0020] To further illustrate the technical means and effects adopted by the present invention to achieve its intended purpose, the following, in conjunction with the accompanying drawings and preferred embodiments, details the specific implementation, structure, features, and effects of a bank remote monitoring video acquisition system and method proposed according to the present invention. In the following description, different "one embodiment" or "another embodiment" do not necessarily refer to the same embodiment. Furthermore, specific features, structures, or characteristics in one or more embodiments can be combined in any suitable form.

[0021] Unless otherwise defined, 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 pertains.

[0022] This invention addresses the scenario where forward error correction adds redundant information to data packets, enabling the receiving end to recover lost data automatically when encountering partial network packet loss without requesting retransmission. This significantly reduces video stuttering and buffering, ensuring the continuity and real-time performance of the video stream and greatly improving the viewing experience under unstable network conditions. This invention analyzes the network stability during video transmission based on basic information feedback during video frame transmission. It adjusts the redundancy rate during video frame transmission based on the system's task processing workload and network stability. It also reasonably adjusts the redundancy rate based on changes in video transmission performance after redundancy rate adjustments at consecutive time points. Finally, it adjusts the video bitrate accordingly when the redundancy rate is too high to ensure normal video data transmission.

[0023] The specific solution of the remote monitoring video acquisition method for banks provided by the present invention will be described in detail below with reference to the accompanying drawings.

[0024] Example 1:

[0025] Please see Figure 1 The diagram illustrates a flowchart of a bank remote monitoring video acquisition method according to an embodiment of the present invention, including:

[0026] Step S101: Obtain the maximum latency, jitter value, and packet loss rate of the bank's remote monitoring video transmission during the first predetermined time period before the current time.

[0027] Specifically, the first predetermined time period in this embodiment of the invention can be determined according to the actual scenario. In this embodiment, the length of the first time period is 30 minutes. The specific process is as follows: 30 minutes are counted backward from the current moment as the first predetermined time period for the current moment. The interval between moments can be determined according to the actual situation; in this embodiment, it is set to 20ms.

[0028] Furthermore, when obtaining the maximum latency, jitter value, and packet loss rate, this embodiment of the invention obtains remote video stream transmission indicators through the Real-time Transport Control Protocol (RTCP). The receiving end analyzes the RTP packet sequence number, counts the number of lost packets, and periodically feeds back the obtained packet loss rate to the sending end through the "fraction lost" and "cumulative number of packets lost" fields in the RTCP Receiver Report (RR) packet. Then, the sending end sends the Network Time Protocol Timestamp (NTP) when sending the RTCP Sender Report (SR) packet to the receiving end. The receiving end recovers the Last SR timestamp (last sender report timestamp) and the receiving end processing delay Delaysince last SR (delay since the last sender report) from the RR packet to calculate and obtain the Round-Trip Time (RTT). Finally, the receiving end calculates the variance of the time interval between consecutive RTP packets, smooths it using a first-order filter, obtains the jitter value during video data transmission, and fills the result into the "interarrival jitter" field of the RR packet before sending it back to the sending end.

[0029] Step S102: Determine the network instability level within the first predetermined time period based on the maximum latency, jitter value, and packet loss rate.

[0030] Specifically, when a bank's central monitoring and control system acquires real-time video from remote monitoring or previously unuploaded video, network instability can often cause video data transmission stuttering. To ensure smooth playback of remote video data under unstable network conditions, forward error correction can be used to reduce the time loss of data retransmission when packets are lost by carrying redundant packets during video frame transmission. However, carrying redundant packets increases bandwidth overhead during transmission; therefore, the redundancy rate should be adjusted accordingly based on real-time network conditions. The more frequent and severe the latency, jitter, and packet loss during video frame transmission, the more unstable the current network. Therefore, this embodiment of the invention judges the network stability based on feedback from basic information such as latency, jitter, and packet loss rate during remote monitoring video transmission.

[0031] Furthermore, as an optional embodiment of the present invention, determining the network instability level within a first predetermined time period based on the maximum latency, jitter value, and packet loss rate includes: determining the network congestion level within the first predetermined time period based on the maximum latency and jitter value; and determining the network instability level within the first predetermined time period based on the packet loss rate and network congestion level.

[0032] Specifically, when determining the network congestion level within a first predetermined time period, as an optional embodiment of the present invention, the maximum latency of remote monitoring video transmission of the bank during the current time and the first predetermined time period adjacent to the current time, as well as the maximum jitter value among all jitter values ​​in the first predetermined time periods before the current time, are first obtained; then, based on the maximum latency, the jitter value in the first predetermined time period, and the maximum jitter value, the network congestion level within the first predetermined time period adjacent to the current time is determined.

[0033] Specifically, in this embodiment of the invention, taking a first predetermined time period of 30 minutes as an example, all first predetermined time periods before the current time include the time period counting 30 minutes backward from the current time, and the 30-minute time periods corresponding to other times before the current time. Taking the current time i as an example, the maximum latency of the bank's remote monitoring video transmission within the 30-minute time period calculated backward from the current time i is denoted as... and jitter value . This jitter value The maximum jitter value is obtained by comparing the jitter values ​​of 30-minute intervals at other times. When the maximum delay The larger the value, the greater the jitter value within the 30-minute time period corresponding to the current time i. With maximum jitter value The difference between The smaller the time interval, the more unstable the latency, and the longer the latency duration, indicating more severe network congestion. Therefore, this embodiment of the invention uses the following formula to calculate the network congestion level within the first predetermined time period corresponding to the current time i:

[0034]

[0035] In the above formula, This indicates the network congestion level within the first predetermined time period corresponding to the current time i. This represents the maximum latency for remote monitoring video transmission within the first predetermined time period calculated backward from the current time i. This indicates the maximum jitter value. This represents the jitter value within the first predetermined time period calculated backward from the current time i. This is to prevent the denominator from being 0.

[0036] Furthermore, in determining the network instability level within a first predetermined time period, as an optional embodiment of the present invention, the maximum packet loss rate among all packet loss rates within the first predetermined time periods before the current time, and the maximum network congestion level among all network congestion levels within the first predetermined time periods before the current time are first determined; then, based on the packet loss rate and network congestion level, the maximum packet loss rate and the maximum network congestion level of the first predetermined time periods adjacent to the current time before the current time, the network instability level within the first predetermined time period adjacent to the current time is determined.

[0037] Specifically, this embodiment of the invention obtains the packet loss rate within the first predetermined time period corresponding to the current time i. The maximum packet loss rate under different first predetermined time periods was obtained by comparison. The packet loss rate within the first predetermined time period corresponding to the current time i. Compared to the maximum packet loss rate ratio The larger the value, the greater the network congestion level within the first predetermined time period corresponding to the current time i. Compare the maximum network congestion levels within different first scheduled time periods The difference The smaller the time frame, the more severe the network congestion, packet loss, and network instability within the first predetermined time period. To ensure smooth video playback, the transmitted video frames should carry more redundant data. Therefore, this embodiment of the invention uses the following formula to calculate the network instability within the first predetermined time period adjacent to the current time:

[0038]

[0039] In the above formula, This indicates the degree of network instability within the first predetermined time period corresponding to the current time i. This represents the packet loss rate within the first predetermined time period corresponding to the current time i. This represents the maximum packet loss rate. This indicates the maximum level of network congestion. This represents the network congestion level within the first predetermined time period corresponding to the current time i. Where, when The larger the value, the more unstable the network becomes within the first predetermined time period corresponding to the current time i, and the more likely data packet loss will occur.

[0040] Step S103: Determine the first adjustment redundancy rate for the current moment based on the total CPU load at the current moment and all moments within the first predetermined time period, the CPU load during remote monitoring video transmission at the current moment, and the network instability.

[0041] Specifically, to ensure smooth playback of remote video when the network is unstable, the redundancy rate of transmitted video frames should be increased. This allows for direct retrieval of video frame data from redundant data in case of packet loss, avoiding the time consumption of retransmission. However, carrying redundant data inevitably increases bandwidth overhead. When the CPU is heavily loaded, other tasks will compete for CPU computation cycles originally allocated to the video encoder, causing a decrease in encoding speed. To ensure real-time performance, an excessively high redundancy rate is not advisable in this situation. Conversely, when the CPU load is low, a higher redundancy rate can be used to ensure smooth video acquisition when the network is unstable. Therefore, this embodiment of the invention judges the variability of video transmission bandwidth overhead based on the current overall CPU load and the proportion of video transmission within it, and adjusts the redundancy rate of video frame transmission in conjunction with network stability. The redundancy rate is then readjusted based on the changes in feedback data after continuous redundancy rate adjustments.

[0042] Furthermore, as an optional embodiment of the present invention, determining the first adjusted redundancy rate at the current moment, based on the total CPU load at the current moment and all moments within the first predetermined time period, the CPU load during remote monitoring video transmission at the current moment, and the network instability, includes: determining a first increase in the redundancy rate at the current moment based on the total CPU load at the current moment and all moments within the first predetermined time period, the CPU load during remote monitoring video transmission at the current moment, and the network instability during the first predetermined time period; adjusting the initial redundancy rate during remote monitoring video transmission at the current moment based on the first increase in the redundancy rate to obtain a second adjusted redundancy rate; determining a second increase in the redundancy rate at the current moment to meet future changes based on the second adjusted redundancy rate at the current moment and the second adjusted redundancy rates at all moments within the second predetermined time period prior to the current moment; and adjusting the second adjusted redundancy rate at the current moment again using the second increase to obtain the first adjusted redundancy rate at the current moment.

[0043] Specifically, in this embodiment of the invention, the total CPU load at time i is first obtained. The total CPU load at time i is obtained by comparison. The minimum value of total CPU load at all times within the first predetermined time period. Then, obtain the CPU load at time i during remote monitoring video transmission, and the total CPU load at time i. The proportion of At the current time i, the total CPU load Minimum of total CPU load The difference The smaller the value, the higher the CPU load percentage during remote monitoring video transmission at the current moment. The larger the CPU load, the smaller the current CPU load, and the primary function is to handle the transmission of remote monitoring video. Therefore, the bandwidth available for transmitting remote monitoring video can be increased significantly, allowing for a larger redundancy rate. Thus, as an optional embodiment of the present invention, determining the first increase in redundancy rate at the current moment, based on the total CPU load at the current moment and all moments within the first predetermined time period, the CPU load during remote monitoring video transmission at the current moment, and the network instability within the first predetermined time period, includes: determining the minimum total CPU load among the total CPU loads at the current moment and all moments within the first predetermined time period; and determining the first increase in redundancy rate at the current moment based on the total CPU load at the current moment, the minimum total CPU load, the CPU load, and the network instability within the first predetermined time period.

[0044] Specifically, in this embodiment of the invention, the first increase in redundancy rate at the current moment is calculated using the following formula:

[0045]

[0046] In the above formula, This indicates the first increase in redundancy rate at time i. This represents the total CPU load at time i. This represents the minimum of the total CPU load at the current time i and the total CPU load at all times within the first predetermined time period. This indicates the degree of network instability within the first predetermined time period corresponding to the current time i. This represents the percentage of CPU load at time i during remote monitoring video transmission compared to the total CPU load at time i. This is to prevent the denominator from being 0. Among them, This indicates the extent to which the transmission bandwidth of the remote monitoring video can be increased at the current time i. A greater increase in transmission bandwidth corresponds to a higher degree of network instability within the first predetermined time period corresponding to the current time i. When the value is larger, a higher redundancy ratio can be used to ensure smooth video acquisition. The larger.

[0047] Furthermore, for ease of calculation, the embodiments of the present invention employ a maximum-minimum normalized pair. Normalization is performed to obtain the first increase after normalization. Its value range can be [0,5], and it participates in subsequent calculations.

[0048] Furthermore, when the redundancy rate increases to a certain extent... The larger the value, the greater the redundancy rate used after adjustment. Therefore, in this embodiment of the invention, the initial redundancy rate for remote monitoring video transmission at the current moment is adjusted using the following formula to obtain the second adjusted redundancy rate:

[0049]

[0050] In the above formula, This represents the second adjustment redundancy rate when remote monitoring video transmission is performed at the current time i. This represents the first increase in the normalized redundancy rate at time i. This represents the initial redundancy rate when remotely monitoring video transmission is performed at the current moment. It can be determined according to the actual scenario, and in this embodiment of the invention, it is set to 5%.

[0051] Furthermore, network instability and CPU load change in real time. Obtaining the redundancy rate based on information at the current moment may not meet the requirements for smooth transmission of future remote video data. Therefore, this embodiment of the invention predicts future network conditions by adjusting the redundancy rate obtained at consecutive moments, so as to appropriately adjust the redundancy rate used in the future to meet the transmission requirements of video data. Therefore, as an optional embodiment of the invention, determining the second increase degree of the redundancy rate at the current moment to meet future changes based on the second adjusted redundancy rate at the current moment and the second adjusted redundancy rates at all moments within the second predetermined time period before the current moment includes: determining a first difference between the second adjusted redundancy rates at the current moment and all moments within the second predetermined time period before the current moment, the first difference being the difference between the second adjusted redundancy rate at the next moment and the second adjusted redundancy rate at the previous moment; determining a first number of all first differences that are greater than a preset value and a second number of all first differences; determining a second difference between the second adjusted redundancy rate at the current moment and the second adjusted redundancy rate at the earliest moment of the second predetermined time period; and determining the second increase degree of the redundancy rate at the current moment to meet future changes based on the first number, the second number, and the second difference.

[0052] Specifically, in this embodiment of the invention, the length of the second predetermined time period can be shorter than the first predetermined time period, and it can be determined according to the actual scenario. In this embodiment, it is set to 10 minutes. The preset value can be 0. This embodiment of the invention first obtains the second adjustment redundancy rate calculated using the above steps and methods for different times within the second predetermined time period within 10 minutes prior to the current time i. Then, it calculates the first difference between the magnitudes of the second adjustment redundancy rates corresponding to adjacent times m-1 and m. Then calculate the first number of the first differences between adjacent time points where the first difference is greater than 0. The second quantity of the first difference between the second adjustment redundancy rate obtained at all adjacent times. ratio Secondly, calculate the second adjustment redundancy rate at the current time within the second predetermined time period. The second adjustment redundancy rate with the earliest time of the second predetermined time period The second difference between Among them, when the ratio Larger, and the difference When the redundancy rate is higher, within a 10-minute timeframe, to ensure smooth video playback, the second adjustment redundancy rate is significantly increased. This indicates a higher degree of network instability, causing video playback stuttering, and there is a high probability that network instability will worsen. To ensure smooth video playback even with future network changes, the current redundancy rate should be increased even further. Therefore, this embodiment of the invention uses the following formula to calculate the second increase in redundancy rate at the current time i to satisfy future changes:

[0053]

[0054] In the above formula, This indicates the second degree of increase in redundancy rate at the current time i to satisfy future changes. This represents the first number of first differences in the magnitude of the second adjustment redundancy rate obtained at adjacent time points that are greater than 0. The second quantity represents the first difference between the second adjustment redundancy rates at all adjacent time points. This represents the second adjustment redundancy rate at the current time i. The second adjustment redundancy rate represents the earliest time of the second predetermined time period.

[0055] Furthermore, to facilitate subsequent calculations, this embodiment of the invention utilizes a maximum-minimum normalization pair. Normalization is performed to obtain the normalized second increase. Its range is [0, 0.5].

[0056] Furthermore, when When the value is larger, the second adjustment redundancy rate at the current time i is... Furthermore, the redundancy should be increased further to meet the need for stable video playback during future network fluctuations. Therefore, this embodiment of the invention uses the following formula to calculate the first adjustment redundancy rate at the current time i:

[0057]

[0058] In the above formula, This represents the first adjustment redundancy rate at the current time i. This represents the second adjustment redundancy rate at the current time i. This indicates the second degree of increase in redundancy rate at the current time i after normalization to satisfy future changes.

[0059] Step S104: Determine the real-time video bitrate at the current moment based on the total CPU load and CPU load at all moments within the first predetermined time period, the first adjusted redundancy rate at the current moment and each moment within the first predetermined time period, and perform forward error correction processing on the remote monitoring video transmitted at the current moment based on the first adjusted redundancy rate and the real-time video bitrate.

[0060] Specifically, when there are too many processing tasks on the CPU, the presence of other tasks reduces the transmittable bandwidth for remote data transmission. However, when the network is unstable, a larger redundancy rate is still needed to ensure smooth video playback. In this case, to ensure normal data transmission, the video bitrate of the transmitted video frames should be reduced, thereby sacrificing video clarity to maintain video smoothness. Therefore, this embodiment of the invention determines whether to correct the video bitrate based on the extent to which the current video data transmission bandwidth can be increased and the size of the redundancy rate after the secondary modification.

[0061] Furthermore, as an optional embodiment of the present invention, determining the real-time video bitrate at the current moment based on the total CPU load, CPU load, and first adjustment redundancy rate at each moment within the first predetermined time period, including: determining the degree of reduction in video bitrate during remote monitoring video transmission at the current moment based on the total CPU load, CPU load during remote monitoring video transmission at the current moment, and first adjustment redundancy rate at each moment within the first predetermined time period; adjusting the video bitrate reference value based on the degree of reduction in video bitrate to obtain the real-time video bitrate at the current moment.

[0062] Specifically, the embodiments of the present invention can increase the transmission bandwidth of remote monitoring video at the current time i through the methods described in the above embodiments. To obtain. This indicates the extent to which the transmission bandwidth of the remote monitoring video can be increased at the current time i. This represents the total CPU load at time i. This represents the minimum total CPU load at time i and the minimum total CPU load at all times within the first predetermined time period. This represents the percentage of CPU load at time i during remote monitoring video transmission compared to the total CPU load at time i. This is to prevent the denominator from being 0.

[0063] Furthermore, in this embodiment of the invention, the first adjustment redundancy rate at the current time i is obtained by comparison. The maximum adjustment redundancy rate among the first adjustment redundancy rates at each time point within the first predetermined time period. .

[0064] Furthermore, when the transmission bandwidth can be increased to a greater extent... The smaller the value, the higher the first adjustment redundancy rate at time i. With maximum adjustment redundancy rate The difference The smaller the bandwidth available for video transmission, the less sufficient it is to meet the current redundancy requirements. Therefore, the video bitrate should be reduced accordingly to decrease the bandwidth overhead of transmitted video data and ensure normal data transmission. Thus, as an optional embodiment of the present invention, determining the degree of video bitrate reduction during remote monitoring video transmission at the current moment, based on the total CPU load at the current moment and all moments within the first predetermined time period, the CPU load during remote monitoring video transmission at the current moment, and the first adjusted redundancy rate at each moment within the current moment and the first predetermined time period, includes: determining the minimum total CPU load among the total CPU loads at the current moment and all moments within the first predetermined time period, and the maximum adjusted redundancy rate among the first adjusted redundancy rates at each moment within the current moment and the first predetermined time period; and determining the degree of video bitrate reduction during remote monitoring video transmission at the current moment based on the total CPU load at the current moment, the minimum total CPU load, the CPU load, the maximum adjusted redundancy rate, and the first adjusted redundancy rate at the current moment.

[0065] Specifically, in this embodiment of the invention, the following formula is used to calculate the degree of reduction in video bitrate during remote monitoring video transmission at the current time i:

[0066]

[0067] In the above formula, This indicates the degree of reduction in video bitrate during remote monitoring video transmission at the current time i. This represents the total CPU load at time i. This represents the minimum total CPU load at time i and the minimum total CPU load at all times within the first predetermined time period. This represents the percentage of CPU load at time i during remote monitoring video transmission compared to the total CPU load at time i. This represents the first adjustment redundancy rate at the current time i. This represents the maximum adjustment redundancy rate among the first adjustment redundancy rates at each time point within the first predetermined time period. This is to prevent the denominator from being 0.

[0068] Furthermore, for ease of calculation, embodiments of the present invention utilize the maximum-minimum normalization pair. Normalization is performed to obtain the normalized video bitrate reduction during remote monitoring video transmission at the current time i. Its range is [0, 0.5].

[0069] Furthermore, when The larger the value, the greater the decrease in video bitrate at current time i. The video bitrate reference value in this embodiment can be determined based on the actual scenario; in this embodiment, it is 3000 kbps. Therefore, this embodiment uses the following formula to calculate the real-time video bitrate at current time i:

[0070]

[0071] In the above formula, This represents the real-time video bitrate at the current moment i. This indicates a reference value for the video bitrate. This represents the degree of reduction in video bitrate during remote monitoring video transmission at the current time i after normalization.

[0072] Furthermore, this embodiment of the invention uses the above method to obtain the real-time video bitrate and the first adjusted redundancy rate of the uploaded video at different times during remote monitoring. The obtained real-time video bitrate and the first adjusted redundancy rate are then transmitted to the remote monitoring system via RTCP packets.

[0073] Furthermore, video data is acquired through remote monitoring. Remote monitoring extracts fields such as stream_id (stream identifier), action (operation behavior), and value (parameter value) from the parsed data packets. Here, stream_id represents the identifier of the video stream, action represents the processing actions performed on the video stream, such as adjusting redundancy and video bitrate adaptation, and value represents the initial redundancy adjustment and real-time video bitrate that need to be adjusted. Then, the encoder's application programming interface (API) is called to dynamically adjust parameters such as video bitrate and redundancy, restarting the process with the new parameters (initial redundancy adjustment, real-time video bitrate). A new video stream is generated using forward error correction, and the new video stream is further encoded using a graphics processing unit (GPU).

[0074] Furthermore, the encoded data is transmitted to the client via the router using the RTSP protocol. Upon receiving the network data packets, the client first decrypts the protocol (e.g., decrypts RTSP) to obtain a clean H.264 / H.265 bitstream, which is then sent to the decoder. The decoder decodes the compressed bitstream back to the original YUV / RGB image sequence. The decoded original YUV / RGB image sequence is then written to a file and stored in the database.

[0075] This invention analyzes network stability during video transmission based on feedback from basic information such as maximum latency, jitter, and packet loss rate during remote monitoring video frame transmission. This allows for more accurate capture of historical patterns and current status of network fluctuations, providing reliable data support for redundancy rate adjustment. Furthermore, this invention incorporates CPU load into the redundancy rate adjustment considerations. By combining the total CPU load at the current moment and within a first predetermined time period, as well as the dedicated CPU load during video transmission, a first adjustment redundancy rate is determined based on an assessment of network instability. This effectively avoids the CPU overload problem caused by blindly increasing redundancy rates in traditional solutions. It can appropriately increase redundancy to combat packet loss during network fluctuations while controlling redundancy overhead through CPU load constraints, achieving a dynamic balance between network packet loss resistance requirements and CPU carrying capacity, thus improving the accuracy of redundancy rate parameter settings. Furthermore, this invention determines the real-time video bitrate by integrating CPU load and redundancy rate data, and then combines this with forward error correction processing based on the first adjustment of the redundancy rate, forming a dual optimization mechanism for redundancy rate and bitrate. On the one hand, precise redundancy rate adjustment significantly reduces video stuttering under unstable networks, ensuring the continuity and real-time performance of monitoring videos and achieving ideal smooth video transmission. On the other hand, dynamically adapted video bitrate can match the current network bandwidth and CPU performance while maintaining video clarity to meet monitoring requirements, avoiding transmission pressure caused by excessively high bitrate or image blurring caused by excessively low bitrate.

[0076] Furthermore, this embodiment of the invention analyzes the network stability during video transmission based on feedback from basic information such as maximum latency, jitter, and packet loss rate during video frame transmission. The redundancy rate during video frame transmission is adjusted based on the workload of tasks in the system and network stability. The redundancy rate is then adjusted reasonably based on changes in video transmission performance after the redundancy rate adjustment at consecutive time points. If the redundancy rate is too high, the video bitrate is adjusted accordingly to ensure normal video data transmission. This allows the client to smoothly acquire real-time video from remote monitoring even under network instability, enabling more timely detection of problems and events in the bank.

[0077] Example 2:

[0078] Corresponding to the bank remote monitoring video acquisition method provided in the above embodiments, based on the same technical concept, this invention also provides a bank remote monitoring video acquisition system, which is used to execute the above-described bank remote monitoring video acquisition method. Figure 2 This is a schematic diagram of the structure of a remote monitoring video acquisition system for banks, provided in one embodiment of the present invention. Figure 2 As shown. Bank remote monitoring video acquisition systems can vary significantly due to differences in configuration or performance. They may include one or more processors 201 and memory 202. Memory 202 stores computer programs that can run on processor 201. Processor 201 executes the programs stored in memory 202 to achieve the above... Figure 1 The various steps in the method embodiment are described. The memory 202 can be temporary or persistent storage. The application stored in the memory 202 may include one or more modules (not shown in the figures), each module may include a series of computer-executable instructions for the bank's remote monitoring video acquisition system.

[0079] Furthermore, the processor 201 can be configured to communicate with the memory 202 and execute a series of computer-executable instructions stored in the memory 202 on the bank's remote monitoring video acquisition system. The bank's remote monitoring video acquisition system may also include one or more power supplies 203, one or more wired or wireless network interfaces 204, one or more input / output interfaces 205, and one or more keyboards 206.

[0080] Specifically, in this embodiment, the bank remote monitoring video acquisition system includes a processor, a communication interface, a memory, and a communication bus; wherein, the processor, communication interface, and memory communicate with each other via the bus; the memory stores computer programs; and the processor executes the programs stored in the memory to achieve the above... Figure 1 The various steps in the method embodiments are the same as those in the above method embodiments, and have the same beneficial effects. To avoid repetition, the embodiments of the present invention will not be described again here.

[0081] It should be noted that the bank remote monitoring video acquisition system provided in this embodiment of the invention and the bank remote monitoring video acquisition method provided in this embodiment of the invention are based on the same application concept. Therefore, the specific implementation of this embodiment can refer to the implementation of the aforementioned bank remote monitoring video acquisition method, and has the same or similar beneficial effects. Repeated parts will not be described again.

[0082] It should be noted that the order of the above embodiments of the present invention is merely for descriptive purposes and does not represent the superiority or inferiority of the embodiments. The processes depicted in the accompanying drawings do not necessarily require a specific or sequential order to achieve the desired result. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0083] The various embodiments in this specification are described in a progressive manner. The same or similar parts between the various embodiments can be referred to each other. Each embodiment focuses on describing the differences from other embodiments.

[0084] This invention also proposes a computer-readable storage medium storing one or more programs, which, when executed by a bank remote monitoring video acquisition system including multiple applications, cause the bank remote monitoring video acquisition system to perform... Figure 1 The methods disclosed in the embodiments shown achieve the functions and beneficial effects of the methods in the preceding method embodiments, and will not be repeated here.

[0085] The computer-readable storage media include read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

Claims

1. A method for remote monitoring video acquisition in banks, characterized in that, The method for acquiring remote monitoring video of a bank includes: Obtain the maximum latency, jitter, and packet loss rate of the bank's remote monitoring video transmission during the first predetermined time period before the current moment; The network instability level within the first predetermined time period is determined based on the maximum latency, the jitter value, and the packet loss rate. The first adjustment redundancy rate is determined based on the total CPU load at the current moment and all moments within the first predetermined time period, the CPU load during remote monitoring video transmission at the current moment, and the instability of the network. Based on the total CPU load at the current time and all times within the first predetermined time period, the CPU load, and the first adjusted redundancy rate at each time within the first predetermined time period, the real-time video bitrate at the current time is determined, and forward error correction processing is performed on the remote monitoring video transmitted at the current time based on the first adjusted redundancy rate and the real-time video bitrate. The determination of the first adjustment redundancy rate at the current moment includes: The step of determining the first adjustment redundancy rate at the current moment based on the total CPU load at the current moment and all moments within the first predetermined time period, the CPU load during remote monitoring video transmission at the current moment, and the network instability includes: The first increase in redundancy rate at the current moment is determined based on the total CPU load at the current moment and all moments within the first predetermined time period, the CPU load when remote monitoring video transmission is performed at the current moment, and the network instability within the first predetermined time period. Based on the first increase in the redundancy rate, the initial redundancy rate during remote monitoring video transmission at the current moment is adjusted to obtain a second adjusted redundancy rate. Based on the second adjustment redundancy rate at the current moment and the second adjustment redundancy rates at all moments within the second predetermined time period prior to the current moment, determine the second increase in redundancy rate at the current moment to satisfy future changes; The second adjustment redundancy rate at the current moment is adjusted again using the second increase degree to obtain the first adjustment redundancy rate at the current moment; The first increase in the redundancy rate at the current moment includes: Determine the minimum total CPU load among the total CPU load at the current time and all times within the first predetermined time period; The first increase in redundancy rate at the current moment is determined based on the current total CPU load, the minimum total CPU load, the CPU load, and the network instability during the first predetermined time period.

2. The bank remote monitoring video acquisition method according to claim 1, characterized in that, Determining the network instability level within the first predetermined time period based on the maximum latency, the jitter value, and the packet loss rate includes: The network congestion level within the first predetermined time period is determined based on the maximum latency and the jitter value. The degree of network instability during the first predetermined time period is determined based on the packet loss rate and the network congestion level.

3. The bank remote monitoring video acquisition method according to claim 2, characterized in that, Determining the network congestion level within the first predetermined time period based on the maximum latency and the jitter value includes: The maximum latency of remote monitoring video transmission of the bank during the current time and the first predetermined time period adjacent to the current time is obtained, as well as the maximum jitter value among all jitter values ​​in the first predetermined time period before the current time; Based on the maximum latency, the jitter value within the first predetermined time period, and the maximum jitter value, the network congestion level within the first predetermined time period adjacent to the current time is determined.

4. The bank remote monitoring video acquisition method according to claim 2, characterized in that, Determining the network instability level within the first predetermined time period based on the packet loss rate and the network congestion level includes: Determine the maximum packet loss rate among all packet loss rates within all first predetermined time periods prior to the current time, and the maximum network congestion level among all network congestion levels within all first predetermined time periods prior to the current time; The instability of the network within the first predetermined time period adjacent to the current time is determined based on the packet loss rate and network congestion level of the first predetermined time period preceding the current time, the maximum packet loss rate, and the maximum network congestion level.

5. The bank remote monitoring video acquisition method according to claim 1, characterized in that, The step of determining the second increase degree of the redundancy rate to meet future changes at the current time based on the second adjustment redundancy rate at the current time and the second adjustment redundancy rates at all times within the second predetermined period prior to the current time includes: Determine a first difference between the second adjustment redundancy rates of adjacent times within a second predetermined time period prior to the current time and the current time, wherein the first difference is the difference between the second adjustment redundancy rate of the next time and the second adjustment redundancy rate of the previous time. Determine the first number of all first differences that are greater than a preset value and the second number of all first differences; Determine the second difference between the second adjustment redundancy rate at the current time and the second adjustment redundancy rate at the earliest time of the second predetermined time period; Based on the first quantity, the second quantity, and the second difference, the current moment is determined to be the second degree of increase in redundancy rate to meet future changes.

6. The bank remote monitoring video acquisition method according to any one of claims 1-5, characterized in that, The step of determining the real-time video bitrate at the current moment based on the total CPU load at the current moment and all moments within the first predetermined time period, the CPU load, and the first adjusted redundancy rate at the current moment and each moment within the first predetermined time period includes: Based on the total CPU load at the current time and all times within the first predetermined time period, the CPU load when remote monitoring video transmission is performed at the current time, and the first adjustment redundancy rate at each time within the first predetermined time period, the degree of reduction in video bitrate when remote monitoring video transmission is performed at the current time is determined. The video bitrate reference value is adjusted based on the degree of reduction in video bitrate to obtain the real-time video bitrate at the current moment.

7. The bank remote monitoring video acquisition method according to claim 6, characterized in that, The step of determining the degree of video bitrate reduction during remote monitoring video transmission at the current moment based on the total CPU load at the current moment and all moments within the first predetermined time period, the CPU load during remote monitoring video transmission at the current moment, and the first adjustment redundancy rate at each moment within the first predetermined time period includes: Determine the minimum total CPU load among the total CPU load at the current time and all times within the first predetermined time period, and the maximum adjustment redundancy rate among the first adjustment redundancy rates at each time within the current time and the first predetermined time period; The degree of video bitrate reduction during remote monitoring video transmission at the current moment is determined based on the current total CPU load, the minimum total CPU load, the CPU load, the maximum adjustment redundancy rate, and the first adjustment redundancy rate at the current moment.

8. A remote monitoring video acquisition system for banks, characterized in that, include: Processor and memory; wherein the memory is used to store computer programs that can run on the processor; A processor is used to execute a program stored in memory to implement the steps of the bank remote monitoring video acquisition method as described in any one of claims 1-7.

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