Monitoring method based on wireless digital information transmission

Abstract

The invention discloses a monitoring method based on wireless digital information transmission, relates to the technical field of wireless digital information transmission, and solves the technical problem of data transmission. A communication system comprises a front end part, a transmission monitoring part and a terminal part; according to the monitoring method, wireless digital information is sent through the front-end part, and the front-end part improves the encoding or decoding speed and data transmission efficiency of wireless digital information transmission through an improved data compression algorithm; the improved data compression algorithm comprises an ANS data compression algorithm, an LZ77 data compression algorithm and a TSC-SC data compression algorithm; monitoring in a wireless digital information transmission process is realized through the transmission monitoring part; the CRSG risk isolation method is adopted to analyze the transmitted wireless digital flow information, and the CD4512BE decoder is used to decode the encrypted data, so that the network data information interaction capability is greatly improved.

Description

Technical Field

[0001] This invention relates to the field of wireless digital information transmission technology, and more specifically to a monitoring method based on wireless digital information transmission. Background Technology

[0002] With social development and the advancement of electronic technology, wireless information transmission technology has been widely applied. Home security has gradually become a necessity for more and more families, attracting increasing attention. This has led to the existence of various wireless communication protocols in practical applications. Each of these protocols has its advantages, and their coexistence allows people to more easily enjoy the benefits they bring. Meanwhile, monitoring the terminals of the wireless communication network is a crucial step in ensuring the quality of network service. However, due to the large number of terminals and the potential use of multiple communication protocols to connect these terminal devices to the central monitoring equipment, a monitoring system uses fiber optics, coaxial cables, or microwaves to transmit video signals within a closed loop. From camera to image display and recording, it forms an independent and complete system that can reflect the monitored object in real time, vividly, and realistically. It can replace manual monitoring for extended periods in harsh environments, recording the footage via a video recorder. Video surveillance and control system (VSCS) Security monitoring systems (SMS) refer to electronic systems or networks that use video detection technology to monitor and display and record images of the protected area in real time. While this method can improve data display capabilities, the transmission of signals in existing security monitoring systems generally relies on optical fibers and cables. During construction, dedicated lines need to be laid for signal transmission, which incurs significant costs. Furthermore, when the signal transmission lines are damaged, repairs take a long time and consume considerable manpower and resources.

[0003] In summary, although there are cameras in the existing technology that can achieve wireless transmission, their anti-interference ability is poor. When encountering malicious interference, they cannot perform the recording and shooting effect, which affects the normal use of network data information and security monitoring systems. How to achieve wireless data information monitoring has become an urgent technical problem to be solved. The existing technology using surveillance cameras is outdated and cannot achieve artificial intelligence-based data information analysis. Summary of the Invention

[0004] To address the shortcomings of the aforementioned technologies, this invention discloses a monitoring method based on wireless digital information transmission. By setting up a CRSG risk isolation method to analyze the transmitted wireless digital traffic information, the network asset information of the target host is obtained based on the analysis data, and the isolated data information is encrypted through an encryption module; this greatly improves the wireless information transmission and monitoring capabilities.

[0005] To achieve the above-mentioned technical effects, the present invention adopts the following technical solution:

[0006] like Figure 1 As shown, a monitoring method based on wireless digital information transmission is disclosed, wherein the wireless digital information transmission includes a front-end part, a transmission monitoring part, and a terminal part; the monitoring method includes the following steps:

[0007] (S1) Transmit wireless digital information through the front-end section;

[0008] In this step, the wireless digital information includes digital information from self-storage systems, faulty systems, local area communication systems, solar charging systems, emergency power supply systems, or wireless communication systems. The front-end uses improved data compression algorithms to enhance the encoding or decoding speed and data transmission efficiency of the wireless digital information. These improved data compression algorithms include ANS data compression, LZ77 data compression, and TSC-SC data compression algorithms.

[0009] The ANS data compression algorithm is used to convert wireless data information into neural network structure data information, so as to achieve data compression through neural network, thereby improving the regional wireless information compression calculation and transmission capabilities; the ANS data compression algorithm is also equipped with an automatic encoder to balance compression ratio and speed.

[0010] The LZ77 data compression algorithm is used to compress wireless digital information during transmission, and achieves wireless data information output through a data compression ratio of 1:N and reconstruction with a resolution greater than 3 times; where N is greater than 10.

[0011] The TSC-SC data compression algorithm improves the accuracy of wireless data information prediction by more than 5 times through 100 iterations of calculation.

[0012] The front-end component also includes a wireless communication monitoring camera;

[0013] (S2) Monitoring during the wireless digital information transmission process is achieved through the transmission monitoring section;

[0014] In this step, traffic information of the target host is captured using vulnerability detection methods, and the transmitted wireless digital traffic information is analyzed using the CRSG risk isolation method. Based on the analysis data, the network asset information of the target host is obtained, and the isolated data information is encrypted using an encryption module. The risk isolation method includes wireless digital information security encryption.

[0015] (S3) Receive wireless digital information through the terminal section;

[0016] In this step, the encrypted data is decoded using the CD4512BE decoder. The CD4512BE decoder uses 8 ports to achieve signal interaction, enabling rapid data signal conversion and data reception.

[0017] As a further technical solution of the present invention, the front-end part further includes a terminal transmitting device, a wireless communication module, a monitoring camera, an asynchronous transceiver, a UART interface, and a USB interface; wherein the terminal transmitting device, the wireless communication module, and the monitoring camera are respectively connected to the asynchronous transceiver, and the asynchronous transceiver is connected to the UART interface and the USB interface.

[0018] As a further technical solution of the present invention, when the front-end part transmits wireless digital information, the wireless communication network used includes 4G network, 5G network and Internet network; the digital information medium of the self-storage system includes a TF memory card, the capacity of which is 64GB or more; the digital information of the local area communication system realizes data communication through a Bluetooth module or a local area network module; the digital information of the solar charging system is output through a solar charging panel, which is located on the upper side of the wireless communication monitoring camera; the digital information of the emergency power supply system is output through a high-energy lithium-ion battery.

[0019] As a further technical solution of the present invention, the vulnerability detection method uses a DSP chip processor with error calculation function to detect vulnerability data information. The DSP chip is a TMS32F28377D data chip, and the error calculation function set in the DSP chip is the mean relative error (MRE) and the minimum squared error (LSE).

[0020] As a further technical solution of the present invention, the mean relative error (MRE) function is:

[0021] (1)

[0022] In formula (1), The total amount of wireless digital information transmitted by the front-end part. This indicates the number of elements in the total data volume of wireless digital information. This refers to different data samples within the total amount of wireless digital information. In actual wireless data transmission, the first... A true diagnostic information value;

[0023] The LSE (Least Squares Error) function is:

[0024] (2)

[0025] In formula (2), Indicates the number of times the calculation is performed.

[0026] As a further technical solution of the present invention, the working method of the CRSG risk isolation method is as follows:

[0027] (1) Construct an initial wireless information risk matrix;

[0028] In this step, a risk indicator system for wireless digital information transmission is established using a matrix approach. The matrix equation is denoted as A:

[0029] (3)

[0030] In formula (3), m is the number of risk assessment objects, and n is the number of risk indicators. Let m be the risk data object and n be the value of the risk indicator.

[0031] (2) The wireless information risk information matrix is ​​standardized using the following formula:

[0032] (4)

[0033] In formula (4), where Let i be the value of the j-th risk indicator for the i-th risk object, i = 1, 2, ..., m, j = 1, 2, ..., n; Let x be the value of the i-th risk object and the j-th risk indicator in the homogeneity matrix x, and k be the output dimension indicator.

[0034] (3) Compile the ranks. Compile the ranks of the wireless information risk matrix after homogenization. For m wireless information transmission risk assessment objects, sort them in order of the size of the index values. Assign the largest observation value to the m-rank and the smallest observation value to the 1-rank. Compile the wireless information transmission ranks of the remaining index values ​​using a method similar to linear interpolation.

[0035] (5)

[0036] In formula (5), Let be the rank of the j-th indicator for the i-th risk object; It is the minimum value among the j-th index values; The maximum value among the j-th index values ​​is obtained by calculating the Z value in the wireless information transmission risk rank matrix (5).

[0037] (6)

[0038] In formula (6), This represents the m-th rank of the n-th risk indicator; to improve the wireless digital information transmission capability, the weighted rank sum ratio of the input dimensions is set, where:

[0039] (7)

[0040] In formula (7), The weighted rank sum ratio of the input dimensions for the i-th wireless information transmission risk object; The weighted rank sum ratio of the output dimension for the i-th wireless information transmission risk object; The weighted rank sum ratio of the i-th wireless information transmission risk object; Represented as , and The weight value of the j-th indicator during the calculation process, Represented as an intermediate variable;

[0041] (4) Calculate the rank sum and ratio distribution, based on , and Arrange the values ​​by size, list the frequency f and cumulative frequency f↓ for each group, and determine the rank range and average rank value for each group accordingly. Then the cumulative frequency is calculated. List the probability unit values ​​corresponding to the percentiles based on the table of percentiles and their corresponding probability units;

[0042] (5) Determine the risk level of wireless information transmission. After the risk isolation model is constructed, group the risk assessment objects of each wireless information transmission according to... , and It is worth classifying into formula (3) R matrix to determine the degree of security risk in wireless information transmission, and to determine the priority of security measures.

[0043] As a further technical solution of the present invention, the method for wireless digital information security encryption is the RSA encryption algorithm.

[0044] As a further technical solution of the present invention, the encrypted data is decoded by a CD4512BE decoder, and the control model is CY7C1012AV25.

[0045] As a further technical solution of the present invention, the CD4512BE decoder decoding method is as follows:

[0046] First, the encoded and compressed wireless digital information is input through the data input pin. Then, the Predic prediction value and StepSize data size value are set and updated. The computing chip captures these two values ​​in the data stream. When the data information is not lost, the encoding pin and the decoding pin have the same Predic prediction value and StepSize data size value. In wireless transmission, in order to improve the data packet transmission evaluation capability, the computing chip calculates the Predic prediction value and StepSize data size value of the wireless digital information every 1 second to realize the real-time sampling information prediction of subsequent wireless information transmission. Then, the encrypted sampling data information is decoded, and signal interaction is realized through 8 ports.

[0047] The beneficial effects of this invention are as follows:

[0048] Unlike conventional technologies, the present invention aims to provide a monitoring method based on wireless digital information transmission, comprising a front-end section, a transmission monitoring section, and a terminal section. The monitoring method transmits wireless digital information through the front-end section, which improves the encoding or decoding speed and data transmission efficiency of wireless digital information transmission using an improved data compression algorithm. The improved data compression algorithm includes the ANS data compression algorithm, the LZ77 data compression algorithm, and the TSC-SC data compression algorithm. The transmission monitoring section monitors the wireless digital information transmission process. The CRSG risk isolation method is used to analyze the transmitted wireless digital traffic information, and the encrypted data is decoded using a CD4512BE decoder, significantly improving the network data information interaction capability. Attached Figure Description

[0049] To more clearly illustrate the technical solutions 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, wherein:

[0050] Figure 1 This is a schematic diagram of a monitoring method based on wireless digital information transmission according to the present invention.

[0051] Figure 2 This is a schematic diagram of the risk isolation method of CRSG of the present invention. Detailed Implementation

[0052] The preferred embodiments of the present invention will be described below with reference to the accompanying drawings. It should be understood that the embodiments described herein are for illustration and explanation only and are not intended to limit the present invention.

[0053] A monitoring method based on wireless digital information transmission includes a front-end section, a transmission monitoring section, and a terminal section; the monitoring method includes the following steps:

[0054] (S1) Transmit wireless digital information through the front-end section;

[0055] In this step, the wireless digital information includes digital information from self-storage systems, faulty systems, local area communication systems, solar charging systems, emergency power supply systems, or wireless communication systems. The front-end uses improved data compression algorithms to enhance the encoding or decoding speed and data transmission efficiency of the wireless digital information. These improved data compression algorithms include ANS data compression, LZ77 data compression, and TSC-SC data compression algorithms.

[0056] The ANS data compression algorithm is used to convert wireless data information into neural network structure data information, so as to achieve data compression through neural network, thereby improving the regional wireless information compression calculation and transmission capabilities; the ANS data compression algorithm is also equipped with an automatic encoder to balance compression ratio and speed.

[0057] The LZ77 data compression algorithm is used to compress wireless digital information during transmission, and achieves wireless data information output through a data compression ratio of 1:N and reconstruction with a resolution greater than 3 times; where N is greater than 10.

[0058] The TSC-SC data compression algorithm improves the accuracy of wireless data information prediction by more than 5 times through 100 iterations of calculation.

[0059] The front-end component also includes a wireless communication monitoring camera;

[0060] (S2) Monitoring during the wireless digital information transmission process is achieved through the transmission monitoring section;

[0061] In this step, traffic information of the target host is captured using vulnerability detection methods, and the transmitted wireless digital traffic information is analyzed using the CRSG risk isolation method. Based on the analysis data, the network asset information of the target host is obtained, and the isolated data information is encrypted using an encryption module. The risk isolation method includes wireless digital information security encryption.

[0062] (S3) Receive wireless digital information through the terminal section;

[0063] In this step, the encrypted data is decoded using the CD4512BE decoder. The CD4512BE decoder uses 8 ports to achieve signal interaction, enabling rapid data signal conversion and data reception.

[0064] In specific embodiments, the ANS data compression algorithm is called Asymmetric numeral systems (ANS). In these embodiments, ANS is also an entropy compression algorithm, achieving a good balance between compression ratio and speed, offering both high compression efficiency and fast speed. In specific embodiments, neural network structure data information can be incorporated, continuously integrating input data information. The basic idea of ​​an autoencoder is to "compress" the original high-dimensional data into high-information-content low-dimensional data, and then project the compressed data into a new space. Autoencoders have many applications, including dimensionality reduction, image compression, data denoising, feature extraction, image generation, and recommendation systems. It can be an unsupervised or supervised method, providing insights into the essence of the data. In computer systems where information is measured in binary bits, ANS can use a natural number x and a symbol probability table to simultaneously store all previous information and the information of the compressed symbol s in x. All data in a computer exists in binary form. Therefore, the most direct implementation is to treat the message as a sequence of 0s and 1s. This ANS implementation that compresses two types of symbols is called Uniform Binary Asymmetric System (uABS).

[0065] In a specific embodiment, the LZ77 data compression algorithm, when two identical communication data messages exist during network data transmission, determines the content of the second message by retrieving the position and size of the first message. Due to the distance between the two messages and the length of the identical content, the size of the second message can be replaced by the size of the replacement content, thus compressing the information during wireless data transmission. Unlike conventional technologies, this method, applied to wireless data transmission, not only has compression capabilities but also enables data retrieval.

[0066] In a specific embodiment, the two-step data compression algorithm (TSC-SC) is applied by executing respective compression algorithms at the cluster head and within cluster nodes in the network. The cluster head first executes a correlation grouping algorithm to group the data, reducing the computational load on within cluster nodes and eliminating spatial correlations in the data. Within cluster nodes then classify and compress multi-attribute data, transmitting the compression parameters to the cluster head. The cluster head decompresses the data and performs further classification and compression to eliminate data correlations, reduce node data redundancy, and lower communication energy consumption. In this specific embodiment, the TSC-SC algorithm effectively reduces the compression ratio and compression error, significantly reducing data transmission volume and network communication energy consumption.

[0067] In the above embodiments, when the front-end part transmits wireless digital information, the wireless communication network used includes 4G network, 5G network and Internet network; the digital information medium of the self-storage system includes a TF memory card with a capacity of 64GB or more; the digital information of the local area communication system is realized through a Bluetooth module or a local area network module; the digital information of the solar charging system is output through a solar charging panel located on the upper side of the wireless communication monitoring camera; and the digital information of the emergency power supply system is output through a high-energy lithium-ion battery.

[0068] In the above embodiments, the front-end portion further includes a terminal transmitting device, a wireless communication module, a surveillance camera, an asynchronous transceiver, a UART interface, and a USB interface; wherein the terminal transmitting device, the wireless communication module, and the surveillance camera are respectively connected to the asynchronous transceiver, and the asynchronous transceiver is connected to the UART interface and the USB interface.

[0069] In a specific embodiment, the Bluetooth technology module is a short-range wireless connection technology used to replace cables or wires used on portable or fixed electronic devices. The surveillance camera can form a one-to-many wireless connection through a Bluetooth remote control device, creating a "micro-network" around the surveillance camera. Any Bluetooth device in China can communicate with this device. The typical effective communication range of Bluetooth devices is 10 meters, with some reaching up to approximately 100 meters.

[0070] In the above embodiments, the vulnerability detection method uses a DSP chip processor with error calculation function to detect vulnerability data information. The DSP chip is a TMS32F28377D data chip, and the error calculation functions set in the DSP chip are the mean relative error (MRE) and the minimum squared error (LSE).

[0071] In the above embodiments, the mean relative error (MRE) function is:

[0072] (1)

[0073] In formula (1), The total amount of wireless digital information transmitted by the front-end part. This indicates the number of elements in the total data volume of wireless digital information. This refers to different data samples within the total amount of wireless digital information. In actual wireless data transmission, the first... A true diagnostic information value;

[0074] The LSE (Least Squares Error) function is:

[0075] (2)

[0076] In formula (2), Indicates the number of times the calculation is performed.

[0077] In another embodiment, the vulnerability detection method can also employ a risk matrix analysis approach. This method uses a hybrid model to process different input data through filtering or comparative analysis (e.g., template matching). The calculated rank-sum ratio of the input and output dimensions is used as the basis for classifying risk inputs and incident outputs, constructing a wireless information risk judgment matrix. The risk level calculation results of wireless information transmission are then incorporated into the R matrix to determine the degree of risk in the wireless information transmission. Finally, through model analysis and evaluation, security benchmarks and sensitive risk factors are identified, and corresponding wireless information transmission improvement measures and implementation sequences are proposed. This aims to achieve greater security benefits in wireless information transmission with less investment in the next phase, thereby reducing the overall risk level of wireless digital information transmission.

[0078] In the above embodiments, the risk isolation method of CRSG works as follows:

[0079] (2) Construct an initial wireless information risk matrix;

[0080] In this step, a risk indicator system for wireless digital information transmission is established using a matrix approach. The matrix equation is denoted as A:

[0081] (3)

[0082] In formula (3), m is the number of risk assessment objects, and n is the number of risk indicators. Let m be the risk data object and n be the value of the risk indicator.

[0083] (2) The wireless information risk information matrix is ​​standardized using the following formula:

[0084] (4)

[0085] In formula (4), where Let i be the value of the j-th risk indicator for the i-th risk object, i = 1, 2, ..., m, j = 1, 2, ..., n; Let x be the value of the i-th risk object and the j-th risk indicator in the homogeneity matrix x, and k be the output dimension indicator.

[0086] The standard deviation of each indicator and the linear correlation coefficient between indicators are calculated to determine the amount of information transmitted by each indicator and thus the weighting coefficient of the indicator. In a specific implementation, the data information in wireless data transmission is expressed by formulas, enabling a clear analysis of the transmission status.

[0087] (3) Compile the ranks. Compile the ranks of the wireless information risk matrix after homogenization. For m wireless information transmission risk assessment objects, sort them in order of the size of the index values. Assign the largest observation value to the m-rank and the smallest observation value to the 1-rank. Compile the wireless information transmission ranks of the remaining index values ​​using a method similar to linear interpolation.

[0088] (5)

[0089] In formula (5), Let be the rank of the j-th indicator for the i-th risk object; It is the minimum value among the j-th index values; The maximum value among the j-th index values ​​is obtained by calculating the Z value in the wireless information transmission risk rank matrix (5).

[0090] (6)

[0091] In formula (6), This represents the m-th rank of the n-th risk indicator; to improve the wireless digital information transmission capability, the weighted rank sum ratio of the input dimensions is set, where:

[0092] (7)

[0093] In equation (7), The weighted rank sum ratio of the input dimensions for the i-th wireless information transmission risk object;

[0094] The weighted rank sum ratio of the output dimension for the i-th wireless information transmission risk object; The weighted rank sum ratio of the i-th wireless information transmission risk object; Represented as , and The weight value of the j-th indicator during the calculation process, Represented as an intermediate variable;

[0095] (4) Calculate the rank sum and ratio distribution, based on , and Arrange the values ​​by size, list the frequency f and cumulative frequency f↓ for each group, and determine the rank range and average rank value for each group accordingly. Then the cumulative frequency is calculated. List the probability unit values ​​corresponding to the percentiles based on the table of percentiles and their corresponding probability units;

[0096] (5) Determine the risk level of wireless information transmission. After the risk isolation model is constructed, group the risk assessment objects of each wireless information transmission according to... , and It is worth classifying into formula (3) R matrix to determine the degree of security risk in wireless information transmission, and to determine the priority of security measures.

[0097] In the above embodiments, a combined approach of the CRITIC (Criteria Importance Through Intercrieria Correlation) method and the Rank Sum Ration (RSR) method was used to establish a two-dimensional input and output risk index system and risk isolation model for wireless digital information, classifying and assessing the degree of risk in wireless digital information. In other embodiments, a combined approach based on Gap Analysis (GA) and Sensitivity Analysis (SA) can also be used to assess the risk status of threat factors during wireless digital information transmission. The analysis method based on the CRSG (CRITIC-RSR-SA-GA) risk isolation model has high operability and adaptability, and can be adaptively classified according to the requirements of risk level differentiation, more intuitively displaying the risk classification of wireless digital information. This is conducive to formulating targeted wireless digital information security improvement measures and ensuring the orderly operation of wireless digital information networks.

[0098] In the above embodiments, the CRSG risk isolation method benchmarks channels with low security risk levels in wireless digital information transmission to identify their own gaps and deficiencies. Then, through sensitivity analysis of factors affecting wireless digital information transmission security, it identifies and ranks sensitivity indicators, thereby proposing targeted security improvement strategies for wireless digital information transmission.

[0099] In the above embodiments, the method for secure encryption of wireless digital information is the RSA encryption algorithm.

[0100] RSA (Real-time Standard Public-Key) cryptography is a cryptosystem that uses different encryption and decryption keys, making it computationally infeasible to derive the decryption key from the known encryption key. In RSA, the encryption key (public key) PK is public information, while the decryption key (secret key) SK is kept secret. The encryption algorithm E and decryption algorithm D are also public. Although the decryption key SK is determined by the public key PK, it cannot be calculated from PK. This method encrypts data using coprime factors. For example, if two positive integers have no common factors other than 1, they are said to be coprime. For instance, 15 and 32 have no common factors, so they are coprime. This shows that non-prime numbers can also be coprime. RSA's security relies on large number factorization.

[0101] In the above embodiment, the encrypted data is decoded by a CD4512BE decoder, and the control model is CY7C1012AV25.

[0102] The CD4512BE decoder decodes data using a buffered 8-channel data selector. Its pins are composed of complementary MOS (CMOS) circuits with N and P-channel enhancement-mode transistors. This data selector primarily functions as a digital signal multiplexer, selecting one of the eight inputs and routing the signal to the TRI-STATE output. A high level at the disable input forces the output low. A high level at the output enable (OE) input forces the output into a tri-state. A low level at the disable (OE) input allows normal operation.

[0103] In the above embodiment, the CD4512BE decoder decoding method is as follows:

[0104] First, the encoded and compressed wireless digital information is input through the data input pin. Then, the Predic prediction value and StepSize data size value are set and updated. The computing chip captures these two values ​​in the data stream. When the data information is not lost, the encoding pin and the decoding pin have the same Predic prediction value and StepSize data size value. In wireless transmission, in order to improve the data packet transmission evaluation capability, the computing chip calculates the Predic prediction value and StepSize data size value of the wireless digital information every 1 second to realize the real-time sampling information prediction of subsequent wireless information transmission. Then, the encrypted sampling data information is decoded, and signal interaction is realized through 8 ports.

[0105] While specific embodiments of the present invention have been described above, those skilled in the art should understand that these specific embodiments are merely illustrative. Those skilled in the art can omit, substitute, and modify the details of the above methods and systems in various ways without departing from the principles and essence of the present invention. For example, combining the above method steps to perform substantially the same function in substantially the same way to achieve substantially the same result falls within the scope of the present invention. Therefore, the scope of the present invention is defined only by the appended claims.

Claims

1. A monitoring method based on wireless digital information transmission, characterized in that... Wireless digital information transmission includes a front-end section, a transmission monitoring section, and a terminal section; the monitoring method includes the following steps: (S1) Transmit wireless digital information through the front-end section; In this step, the wireless digital information includes digital information from self-storage systems, faulty systems, local area communication systems, solar charging systems, emergency power supply systems, or wireless communication systems. The front-end uses improved data compression algorithms to enhance the encoding or decoding speed and data transmission efficiency of the wireless digital information. These improved data compression algorithms include ANS data compression, LZ77 data compression, and TSC-SC data compression algorithms. The ANS data compression algorithm is used to convert wireless data information into neural network structure data information, so as to achieve data compression through neural network, thereby improving the regional wireless information compression calculation and transmission capabilities; the ANS data compression algorithm is also equipped with an automatic encoder to balance compression ratio and speed. The LZ77 data compression algorithm is used to compress wireless digital information during transmission, and achieves wireless data information output through a data compression ratio of 1:N and reconstruction with a resolution greater than 3 times; where N is greater than 10. The TSC-SC data compression algorithm improves the accuracy of wireless data information prediction by more than 5 times through 100 iterations of calculation. The front-end component also includes a wireless communication monitoring camera; (S2) Monitoring during the wireless digital information transmission process is achieved through the transmission monitoring section; In this step, traffic information of the target host is captured using vulnerability detection methods, and the transmitted wireless digital traffic information is analyzed using the CRSG risk isolation method. Based on the analysis data, the network asset information of the target host is obtained, and the isolated data information is encrypted using an encryption module. The risk isolation method includes wireless digital information security encryption. (S3) Receive wireless digital information through the terminal section; In this step, the encrypted data is decoded using the CD4512BE decoder. The CD4512BE decoder uses 8 ports to achieve signal interaction, enabling rapid data signal conversion and data reception.

2. The monitoring method based on wireless digital information transmission according to claim 1, characterized in that: The front-end portion also includes a terminal transmitting device, a wireless communication module, a monitoring camera, an asynchronous transceiver, a UART interface, and a USB interface; wherein the terminal transmitting device, the wireless communication module, and the monitoring camera are respectively connected to the asynchronous transceiver, and the asynchronous transceiver is connected to the UART interface and the USB interface.

3. The monitoring method based on wireless digital information transmission according to claim 2, characterized in that: When the front-end transmits wireless digital information, the wireless communication network used includes 4G network, 5G network and Internet network; the digital information medium of the self-storage system includes TF memory card, and the capacity of the TF memory card is 64GB or more; the digital information of the local area communication system realizes data communication through Bluetooth module or local area network module; the digital information of the solar charging system is output through solar charging panel, which is located on the top of the wireless communication monitoring camera; the digital information of the emergency power supply system is output through high-energy lithium-ion battery.

4. The monitoring method based on wireless digital information transmission according to claim 1, characterized in that: The vulnerability detection method uses a DSP chip processor with error calculation function to detect vulnerability data information. The DSP chip is a TMS32F28377D data chip, and the error calculation functions set in the DSP chip are the mean relative error (MRE) and the minimum squared error (LSE).

5. The monitoring method based on wireless digital information transmission according to claim 4, characterized in that: The mean relative error (MRE) function is: （1）； In formula (1), The total amount of wireless digital information transmitted by the front-end part. This indicates the number of elements in the total data volume of wireless digital information. This refers to different data samples within the total amount of wireless digital information. In actual wireless data transmission, the first... A true diagnostic information value; The LSE (Least Squares Error) function is: （2）； In formula (2), Indicates the number of times the calculation is performed.

6. The monitoring method based on wireless digital information transmission according to claim 1, characterized in that: The working method of the risk isolation method of CRSG is as follows: (1) Construct an initial wireless information risk matrix; In this step, a risk indicator system for wireless digital information transmission is established using a matrix approach. The matrix equation is denoted as A: （3）； In formula (3), m is the number of risk assessment objects, and n is the number of risk indicators. Let m be the risk data object and n be the value of the risk indicator. (2) The wireless information risk information matrix is ​​standardized using the following formula: （4）； In formula (4), where Let i be the value of the j-th risk indicator for the i-th risk object, i = 1, 2, ..., m, j = 1, 2, ..., n; Let x be the value of the i-th risk object and the j-th risk indicator in the homogeneity matrix x, and k be the output dimension indicator. (3) Compile the ranks. Compile the ranks of the wireless information risk matrix after homogenization. For m wireless information transmission risk assessment objects, sort them in order of the size of the index values. Assign the largest observation value to the m-rank and the smallest observation value to the 1-rank. Compile the wireless information transmission ranks of the remaining index values ​​using a method similar to linear interpolation. （5）； In formula (5), Let be the rank of the j-th indicator for the i-th risk object; It is the minimum value among the j-th index values; The maximum value among the j-th index values ​​is obtained by calculating the Z value in the wireless information transmission risk rank matrix (5). （6）； In formula (6), This represents the m-th rank of the n-th risk indicator; to improve the wireless digital information transmission capability, the weighted rank sum ratio of the input dimensions is set, where: （7）； In formula (7), The weighted rank sum ratio of the input dimensions for the i-th wireless information transmission risk object; The weighted rank sum ratio of the output dimension for the i-th wireless information transmission risk object; The weighted rank sum ratio of the i-th wireless information transmission risk object; Represented as , and The weight value of the j-th indicator during the calculation process, Represented as an intermediate variable; (4) Calculate the rank sum and ratio distribution, based on , and Arrange the values ​​by size, list the frequency f and cumulative frequency f↓ for each group, and determine the rank range and average rank value for each group accordingly. Then the cumulative frequency is calculated. List the probability unit values ​​corresponding to the percentiles based on the table of percentiles and their corresponding probability units; (5) Determine the risk level of wireless information transmission. After the risk isolation model is constructed, group the risk assessment objects of each wireless information transmission according to... , and It is worth classifying into formula (3) R matrix to determine the degree of security risk in wireless information transmission, and to determine the priority of security measures.

7. The monitoring method based on wireless digital information transmission according to claim 1, characterized in that: The method for secure encryption of wireless digital information is the RSA encryption algorithm.

8. The monitoring method based on wireless digital information transmission according to claim 1, characterized in that: The encrypted data is decoded using a CD4512BE decoder, controlled by a CY7C1012AV25.

9. A monitoring method based on wireless digital information transmission according to claim 8, characterized in that: The CD4512BE decoder decoding method is as follows: First, the encoded and compressed wireless digital information is input through the data input pin. Then, the Predic prediction value and StepSize data size value are set and updated. The computing chip captures these two values ​​in the data stream. When the data information is not lost, the encoding pin and the decoding pin have the same Predic prediction value and StepSize data size value. In wireless transmission, in order to improve the data packet transmission evaluation capability, the computing chip calculates the Predic prediction value and StepSize data size value of the wireless digital information every 1 second to realize the real-time sampling information prediction of subsequent wireless information transmission. Then, the encrypted sampling data information is decoded, and signal interaction is realized through 8 ports.

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