A network data module for cameras

Abstract

The invention discloses a network data module for a camera, and relates to the technical field of cameras. The invention effectively reduces the usage of copper cables and labor costs. The module provided by the invention is directly installed near the camera or serves as a mounting base for the camera. In terms of line structure, the module is brought in by a weak current shaft or a monitoring center through an optical cable and a power supply, and the modules are connected with each other by a power composite optical cable. The module has a power module, a network module, a switch quantity module and a 485 communication module. The module has convenient expansion capability. If network equipment is added later, the network expansion module can be connected nearby, which solves the problem of arbitrarily expanding the network requirements of the equipment according to needs. The module can reduce construction costs and construction difficulties, and reduces waste of resources.

Description

Technical Field

[0001] The invention relates to the technical field of cameras, in particular to a network data module for cameras. Background Art

[0002] Cameras, waterproof digital cameras, there are many types of cameras, and their basic working principles are the same: converting optical image signals into electrical signals for storage or transmission. When we shoot an object, the light reflected from the object is collected by the camera lens and focused on the light-receiving surface of the camera device (such as the target surface of the camera tube). The camera device then converts the light into electrical energy, thus obtaining a "video signal". The photoelectric signal is very weak and needs to be amplified by a pre-amplifier circuit, and then processed and adjusted by various circuits. Finally, the standard signal can be sent to a recording medium such as a video recorder for recording, or transmitted through a communication system or sent to a monitor for display.

[0003] For example, a Chinese patent discloses a data transmission method, system and network camera for a network camera, application number CN105338311A, the method includes: the network camera receives a wireless connection request sent to the network camera by an external device when collecting audio data that meets preset conditions; the network camera establishes a wireless connection with the external device according to the wireless connection request; receives the audio data sent by the external device; integrates the audio data into the audio data collected by the built-in microphone of the network camera; and then uploads it to the server synchronously with the video data captured by the built-in camera of the network camera, and the server sends it to the designated terminal device. This solution greatly expands and improves the audio collection range and audio collection effect of the network camera by utilizing the flexibility of the external device; wherein, through the audio integration process, audio data with both integrity and validity is obtained, and then through the synchronization process of audio data and video data, synchronized audio and video data that meets the requirements is obtained.

[0004] Although the above scheme has the above advantages, in reality, new and renovated projects have built-in weak current systems such as monitoring and alarm. The equipment of each system is introduced into the network shaft or the switch of the computer room through network cables, etc. A large amount of copper cables and labor costs are used in the project, resulting in great waste. It is difficult to lay cables for additional equipment in the later stage. Therefore, a network data module for cameras that can arbitrarily expand the network requirements of equipment as needed is urgently needed to solve such problems. Summary of the invention

[0005] In view of the deficiencies of the prior art, the present invention provides a network data module for a camera, which solves the problem that a large amount of copper cables and labor costs are used in projects in the prior art, resulting in great waste, and it is difficult to lay cables for additional equipment at a later stage.

[0006] To achieve the above objectives, the present invention is implemented through the following technical solutions:

[0007] The present invention provides a network data module for a camera, comprising:

[0008] The power module is used to provide the stable power required by the camera system to ensure the normal operation of the auxiliary modules including the camera. The auxiliary modules are regarded as the whole camera system. The power module provides efficient power output for the camera system and has intelligent energy management function;

[0009] The network module is used for data transmission in the camera system, and the integrated monitoring module is used to transmit the data of the monitoring equipment to the monitoring center. The intelligent routing algorithm is used to monitor the real-time network load and equipment demand through the monitoring module, so as to dynamically adjust the data transmission path;

[0010] The switch quantity module is used to process switch quantity information and support the linkage between monitoring devices. It uses a high-speed digital signal processor DSP and a dedicated microcontroller to accelerate the processing and response of switch quantity signals.

[0011] 485 communication module, used to realize communication between devices, supports data transmission and interaction of control commands, 485 communication module adopts differential signal transmission, and introduces error detection and correction mechanism;

[0012] Intelligent network module uses deep learning algorithm to intelligently allocate network module routing and bandwidth by learning device usage patterns; it realizes real-time traffic monitoring and adaptively adjusts the transmission rate according to monitoring needs to ensure efficient transmission of camera monitoring images;

[0013] The self-diagnosis module integrates self-diagnosis algorithms, monitors the status of each module, adopts a secure encrypted communication protocol, and establishes a remote management interface. It cooperates with the network module to provide remote status monitoring, fault diagnosis and firmware upgrades for the camera system.

[0014] The present invention is further configured as follows: in the power supply module, a power consumption monitoring chip is used to monitor the power consumption of the system in real time, and dynamic voltage adjustment is used to enable the power supply to adaptively adjust the power output under different workloads;

[0015] In the power module, a remote communication module is integrated, and a connection is established through a secure communication protocol, so that the remote monitoring center can obtain the power status in real time, perform remote diagnosis, and adjust the power output operation;

[0016] The present invention is further configured as follows: in the network module, the data transmission path is dynamically adjusted by the intelligent routing algorithm:

[0017] Perform data collection and monitoring, and define the time series data set of equipment status and performance parameters as D t , the current network bandwidth utilization is BW t , the load data of the device is LD t , using sensors and monitoring modules to collect D t , Bandwidth utilization BW t and the load data LD of the device t ;

[0018] Perform data preprocessing and define the time series data set of the preprocessed equipment status and performance parameters as D′ t , the load data of the preprocessed equipment is LD′ t , for D t and LD t Normalize, filter and process outliers to get D′ t and LD′ t ;

[0019] The recurrent neural network and convolutional neural network training models are used to learn the usage pattern of the equipment. The weight and bias parameters of the neural network are set as W and b, and D′ t and LD′ t is the input, P t is the output, P t is the probability distribution of device usage patterns, which is calculated as follows: t =σ(WD′ t +b), where σ is the activation function;

[0020] The present invention is further configured as follows: in the network module, the method for dynamically adjusting the data transmission path further includes:

[0021] Determine the network module routing decision, define the current network topology as G, and according to the learned probability distribution of device usage patterns P t and the current network topology G, using the routing decision algorithm to determine the data transmission path R t ;

[0022] The final data transmission path is R t ;

[0023] According to the final data transmission path R t Dynamically adjust the path;

[0024] The present invention is further configured as follows: the network module integrates a flow monitoring module and a remote configuration interface, and adaptively adjusts the transmission rate through real-time monitoring of the transmission data;

[0025] Establish connection with monitoring center through secure communication protocol;

[0026] The present invention is further configured as follows: in the network module, the transmission rate is adaptively adjusted in the following manner:

[0027] Perform bandwidth allocation and rate adjustment, and define the bandwidth allocation vector as B t , the transmission rate vector is T t ;

[0028] Based on the current network bandwidth utilization BW t and data transmission path R t , use the bandwidth allocation algorithm to determine the bandwidth allocation vector B t ;

[0029] Based on real-time flow monitoring F t and the probability distribution P of device usage patterns t , using the rate adjustment algorithm to determine the transmission rate vector T t , specifically: B t =g(BW t ,R t ), T t =h(F t ,P t ), where h is the rate adjustment function and g is the bandwidth allocation vector function;

[0030] Then the decision feedback is defined as F t , including data transmission success rate and device status information;

[0031] The network module routing decision and the results of bandwidth allocation and rate adjustment R t , B t and T t As feedback information F t ;

[0032] Then according to the feedback information F t , adjust the parameters and configuration of the network module to adapt to changes in network status in real time;

[0033] The present invention is further configured as follows: in the 485 communication module, differential signal transmission is adopted, and the introduced error detection is specifically as follows:

[0034] For differential signal transmission, the positive logic level is defined as V A , the inverse logic level is V B , data is D, using differential signal transmission, that is, transmitting signals through two lines A and B, where (V A -V B ) indicates a positive logic level, (V B -V A ) indicates negative logic level;

[0035] Then error detection is performed, defining the number of data bits to be sent as M and the cyclic redundancy check code as CRC. In data transmission, after each M-bit data is sent, the CRC check code is calculated and appended to the data;

[0036] After receiving the data, the receiving end recalculates the CRC check code of the received data and compares it with the attached CRC;

[0037] If the two are inconsistent, it means an error has occurred and retransmission or other error handling is required;

[0038] The present invention is further configured as follows: in the 485 communication module, differential signal transmission is adopted, and the error correction mechanism is specifically as follows:

[0039] The number of error bits is defined as E. If an error is found during error detection, error correction is performed based on the error location information E.

[0040] Hamming code is used to correct errors based on the erroneous position information and restore the original data;

[0041] Specific:

[0042] The sender adds an error correction code: C = D × G, where G is the error correction code generator matrix;

[0043] After receiving C, the receiving end calculates the received error correction code C recive =C+E, where E is the error vector;

[0044] Through the processing of error correction code, the receiving end can recive Restore the original data D;

[0045] The present invention is further configured as follows: in the intelligent network module, the network module routing and bandwidth are intelligently allocated in the following manner:

[0046] First, data collection and monitoring are performed. Assume that the real-time flow demand of device i is T i , the network link load from device i to device j is L ij ;

[0047] Use sensors and monitoring modules to collect the flow demand of equipment in real time i and network link load L ij ;

[0048] Assume that the routing decision from device i to device j is R ij , based on the traffic demand between devices T i , link load L ij And the learned device usage pattern, use the routing algorithm to determine the optimal transmission path R ij ;

[0049] The present invention is further configured as follows: in the intelligent network module, the intelligent allocation method for network module routing and bandwidth also includes:

[0050] Assume that the bandwidth allocation from device i to device j is B ij , according to the routing decision R ij , link load L ij and equipment flow demand T i , use bandwidth allocation algorithm to dynamically adjust bandwidth allocation B ij ;

[0051] The flow demand estimation method is as follows:

[0052] The real-time traffic demand from device i to device j is estimated to be T i =α×T i,avg +(1-α)×T i,current , where α is the smoothing coefficient, T i,avg is the average traffic demand of device i, T i,current is the current real-time traffic demand;

[0053] The link load is updated in the following ways:

[0054] The link load is dynamically updated using a weighted sliding average method, denoted as L ij =β×L ij,avg +(1-β)×L ij,current Where β is the second smoothing coefficient, L ij,avg is the average load of link i to j, L ij,current is the current real-time load.

[0055] Compared with the prior art, the present invention has the following beneficial effects:

[0056] The present invention maximizes the efficiency of electric energy utilization on the power module through real-time monitoring of the power consumption monitoring chip, dynamic voltage adjustment and intelligent energy management, and realizes remote power management through the integration of the remote communication module, thereby improving the maintainability of the system. The network module adopts intelligent routing algorithm and deep learning, so that the data transmission path can be adjusted in real time according to the device usage mode to ensure the effective use of bandwidth. The integration of the flow monitoring module and the remote configuration interface increases the intelligence and management convenience of the system, and the adaptive adjustment of the transmission rate further improves the transmission efficiency of the monitoring screen.

[0057] In the present invention, the switch quantity module and the 485 communication module adopt a high-speed digital signal processor and a dedicated microcontroller at the hardware level, so that the switch quantity signal can be processed and responded more quickly, and the differential signal transmission and error detection and correction mechanism are introduced into the 485 communication module, which greatly improves the communication quality and system stability. The self-diagnosis module realizes the monitoring of the status of each module and the remote management of the camera system by integrating advanced self-diagnosis algorithms, secure encryption communication protocols and establishing a remote management interface, thereby providing all-round support for the stability and maintainability of the system.

[0058] In summary, it can be seen that the present invention can effectively reduce the use of copper cables and labor costs. The module provided by the present invention is directly installed near the camera or used as a mounting base for the camera. In terms of line structure, the module is brought in by a weak current shaft or a monitoring center through an optical cable and a power supply. The modules are connected with a power composite optical cable. The module has a power module, a network module, a switch module and a 485 communication module. The module has convenient expansion capabilities. If network equipment is added later, the network expansion module can be connected nearby, which solves the problem of arbitrarily expanding the equipment network according to needs. The module can reduce construction costs and construction difficulties and reduce waste of resources.

[0059] The invention solves the problem that a large amount of copper cables and labor costs are used in projects in the prior art, resulting in great waste, and it is difficult to lay cables for adding equipment later. BRIEF DESCRIPTION OF THE DRAWINGS

[0060] Figure 1 A structural diagram of a network data module for a camera of the present invention;

[0061] Figure 2 This is an example diagram of a practical application scenario of the network data module for a camera of the present invention. DETAILED DESCRIPTION

[0062] In order to enable those skilled in the art to better understand the scheme of the present invention, the technical scheme in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present invention.

[0063] It should be noted that the terms "first", "second", etc. in the specification and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchanged where appropriate, so that the embodiments of the present invention described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units that are clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0064] The present invention is further described in detail below in conjunction with the accompanying drawings:

[0065] Example 1

[0066] See also Figure 1-Figure 2 The present invention provides a network data module for a camera, comprising: a power module, which is used to provide stable power required by a camera system, ensure the normal operation of accessory modules including the camera, and take the accessory modules as the whole camera system. The power module provides efficient power output for the camera system and has an intelligent energy management function; it maximizes the energy utilization efficiency;

[0067] In the power module, a power consumption monitoring chip is used to monitor the power consumption of the system in real time, and dynamic voltage adjustment is adopted to enable the power supply to adaptively adjust the power output under different workloads to improve energy utilization;

[0068] Intelligent energy management, dynamically adjusting power output according to the working status of the camera and auxiliary modules;

[0069] In the power module, a remote communication module is integrated to establish a connection through a secure communication protocol. The remote monitoring center can obtain the power status in real time, perform remote diagnosis, and adjust the power output operation, thereby improving the maintainability of the system.

[0070] Remote power management is achieved through the power module, and the power module is remotely monitored and controlled through the network. Through the integration of power consumption monitoring and remote communication, the power module can be more efficient and stable, and has intelligent energy management and remote monitoring functions to meet the actual needs of the camera monitoring system;

[0071] The network module is used for data transmission in the camera system. The integrated monitoring module is used to transmit the data of the monitoring equipment to the monitoring center. The intelligent routing algorithm is used to monitor the real-time network load and equipment demand through the monitoring module, so as to dynamically adjust the data transmission path to ensure the effective use of bandwidth;

[0072] In the network module, the data transmission path is dynamically adjusted through the intelligent routing algorithm as follows:

[0073] Perform data collection and monitoring, and define the time series data set of equipment status and performance parameters as D t , the current network bandwidth utilization is BW t , the load data of the device is LD t , using sensors and monitoring modules to collect D t , Bandwidth utilization BW t and the load data LD of the device t ;

[0074] Perform data preprocessing and define the time series data set of the preprocessed equipment status and performance parameters as D′ t , the load data of the preprocessed equipment is LD′ t , for D t and LD t Normalize, filter and process outliers to get D′ t and LD′ t ;

[0075] The recurrent neural network and convolutional neural network training models are used to learn the usage pattern of the equipment. The weight and bias parameters of the neural network are set as W and b, and D′ t and LD′ t is the input, P t is the output, P t is the probability distribution of device usage patterns, which is calculated as follows: t =σ(WD′ t +b), where σ is the activation function;

[0076] In the network module, the method for dynamically adjusting the data transmission path also includes:

[0077] Determine the network module routing decision, define the current network topology as G, and according to the learned probability distribution of device usage patterns P t and the current network topology G, using the routing decision algorithm to determine the data transmission path R t ;

[0078] The final data transmission path is R t ;

[0079] According to the final data transmission path R t Dynamically adjust the path;

[0080] The network module integrates a traffic monitoring module and a remote configuration interface, and can adaptively adjust the transmission rate through real-time monitoring of the transmitted data.

[0081] Realize real-time traffic monitoring to dynamically adjust the transmission rate and ensure efficient transmission of monitoring images;

[0082] Establish connection with monitoring center through secure communication protocol;

[0083] In the network module, the specific method of adaptively adjusting the transmission rate is as follows:

[0084] Perform bandwidth allocation and rate adjustment, and define the bandwidth allocation vector as B t , the transmission rate vector is T t ;

[0085] Based on the current network bandwidth utilization BW t and data transmission path R t , use the bandwidth allocation algorithm to determine the bandwidth allocation vector B t ;

[0086] Based on real-time flow monitoring F t and the probability distribution P of device usage patterns t , using the rate adjustment algorithm to determine the transmission rate vector T t , specifically: B t =g(BW t ,R t ), T t =h(F t ,P t ), where h is the rate adjustment function;

[0087] Then the decision feedback is defined as F t , including data transmission success rate and device status information;

[0088] The network module routing decision and the results of bandwidth allocation and rate adjustment R t , B t and T t As feedback information F t ;

[0089] Then according to the feedback information F t , adjust the parameters and configuration of the network module to adapt to changes in network status in real time;

[0090] The network module is more intelligent, efficient, and has security and remote management functions, meeting the high requirements of camera monitoring systems for data transmission;

[0091] The switch quantity module is used to process switch quantity information and support the linkage between monitoring devices. It uses a high-speed digital signal processor DSP and a dedicated microcontroller to accelerate the processing and response of switch quantity signals.

[0092] 485 communication module is used to realize communication between devices and support the interaction of data transmission and control commands. The 485 communication module adopts differential signal transmission and introduces error detection and correction mechanism to improve communication quality, thereby enhancing the anti-interference ability of the 485 communication module, improving communication stability and ensuring reliable data transmission;

[0093] In the 485 communication module, differential signal transmission is adopted, and the error detection introduced is as follows:

[0094] For differential signal transmission, the positive logic level is defined as V A , the inverse logic level is V B , data is D, using differential signal transmission, that is, transmitting signals through two lines A and B, where (V A -V B ) indicates a positive logic level, (V B -V A ) indicates negative logic level;

[0095] The advantage of differential transmission is its anti-interference ability, which can effectively resist external electromagnetic interference and improve the stability of communication;

[0096] Then error detection is performed, defining the number of data bits to be sent as M and the cyclic redundancy check code as CRC. In data transmission, after each M-bit data is sent, the CRC check code is calculated and appended to the data;

[0097] After receiving the data, the receiving end recalculates the CRC check code of the received data and compares it with the attached CRC;

[0098] If the two are inconsistent, it means an error has occurred and retransmission or other error handling is required;

[0099] In the 485 communication module, differential signal transmission is adopted, and the error correction mechanism is as follows:

[0100] The number of error bits is defined as E. If an error is found during error detection, error correction is performed based on the error location information E.

[0101] Hamming code is used to correct errors based on the erroneous position information and restore the original data;

[0102] Specific:

[0103] The sender adds an error correction code: C = D × G, where G is the error correction code generator matrix;

[0104] After receiving C, the receiving end calculates the received error correction code C recive =C+E, where E is the error vector;

[0105] Through the processing of error correction code, the receiving end canrecive Restore the original data D; thereby ensuring the reliability and stability of data transmission;

[0106] The intelligent network module uses a deep learning algorithm to intelligently allocate network module routing and bandwidth by learning device usage patterns. It implements real-time traffic monitoring and adaptively adjusts the transmission rate according to monitoring needs to ensure efficient transmission of camera monitoring images. The intelligent network module gives the camera system intelligent capabilities and dynamically adjusts the transmission rate and priority to improve system adaptability.

[0107] In the intelligent network module, the intelligent allocation of network module routing and bandwidth is as follows:

[0108] First, data collection and monitoring are performed. Assume that the real-time flow demand of device i is T i , the network link load from device i to device j is L ij ;

[0109] Use sensors and monitoring modules to collect the flow demand of equipment in real time i and network link load L ij ;

[0110] Assume that the routing decision from device i to device j is R ij , based on the traffic demand between devices T i , link load L ij And the learned device usage pattern, use the routing algorithm to determine the optimal transmission path R ij ;

[0111] In the intelligent network module, the intelligent allocation of network module routing and bandwidth also includes:

[0112] Assume that the bandwidth allocation from device i to device j is B ij , according to the routing decision R ij , link load L ij and equipment flow demand T i , use bandwidth allocation algorithm to dynamically adjust bandwidth allocation B ij ;

[0113] The flow demand estimation method is as follows:

[0114] The real-time traffic demand from device i to device j is estimated to be T i =α×T i,avg +(1-α)×T i,current , where α is the smoothing coefficient, T i,avg is the average traffic demand of device i, T i,current is the current real-time traffic demand;

[0115] The link load is updated in the following ways:

[0116] The link load is dynamically updated using a weighted sliding average method, denoted as L ij =β×L ij,avg +(1-β)×L ij,current Where β is the second smoothing coefficient, L ij,avg is the average load of link i to j, L ij,current is the current real-time load;

[0117] In the intelligent network module, the routing decision method is:

[0118] Routing decision R from device i to device j ij Minimize the cost function by taking into account the actual traffic demand between devices, link loads, and device usage patterns;

[0119] The specific cost function design depends on the specific network optimization goal and is determined according to the actual link load balancing and transmission delay reduction requirements;

[0120] Bandwidth allocation is: Bandwidth allocation B ij The adjustment balances bandwidth allocation through the actual traffic demand from device i to j, routing decisions, and link load to ensure that the real-time transmission needs of the device are met;

[0121] The self-diagnosis module integrates self-diagnosis algorithms, monitors the status of each module, adopts a secure encrypted communication protocol, and establishes a remote management interface. It cooperates with the network module to provide remote status monitoring, fault diagnosis and firmware upgrades for the camera system to ensure the stable operation of the camera system. Through the self-diagnosis module, real-time monitoring is achieved, and remote management is used to improve maintainability.

[0122] The present invention maximizes the efficiency of electric energy utilization on the power module through real-time monitoring of the power consumption monitoring chip, dynamic voltage adjustment and intelligent energy management, and realizes remote power management through the integration of the remote communication module, thereby improving the maintainability of the system. The network module adopts intelligent routing algorithm and deep learning, so that the data transmission path can be adjusted in real time according to the device usage mode to ensure the effective use of bandwidth. The integration of the flow monitoring module and the remote configuration interface increases the intelligence and management convenience of the system, and the adaptive adjustment of the transmission rate further improves the transmission efficiency of the monitoring screen.

[0123] In the present invention, the switch quantity module and the 485 communication module adopt a high-speed digital signal processor and a dedicated microcontroller at the hardware level, so that the switch quantity signal can be processed and responded more quickly, and the differential signal transmission and error detection and correction mechanism are introduced into the 485 communication module, which greatly improves the communication quality and system stability. The self-diagnosis module realizes the monitoring of the status of each module and the remote management of the camera system by integrating advanced self-diagnosis algorithms, secure encryption communication protocols and establishing a remote management interface, thereby providing all-round support for the stability and maintainability of the system.

[0124] In summary, it can be seen that the present invention can effectively reduce the usage of copper cables and labor costs. The module provided by the present invention is directly installed near the camera or used as a mounting base for the camera. In terms of line structure, the module is brought in by a weak current shaft or a monitoring center through an optical cable and a power supply. The modules are connected to each other using a power composite optical cable. The module has a power module, a network module, a switch module and a 485 communication module. The module has convenient expansion capabilities. If network equipment is added later, the network expansion module can be connected nearby, which solves the requirement of arbitrarily expanding the device network as needed. The module can reduce construction costs and construction difficulties and reduce waste of resources.

[0125] The above contents are only for explaining the technical idea of ​​the present invention and cannot be used to limit the protection scope of the present invention. Any changes made on the basis of the technical solution in accordance with the technical idea proposed by the present invention shall fall within the protection scope of the claims of the present invention.

Claims

1. A network data module for a camera, characterized in that: include: The power module is used to provide the stable power required by the camera system to ensure the normal operation of the auxiliary modules including the camera. The auxiliary modules are regarded as the whole camera system. The power module provides efficient power output for the camera system and has intelligent energy management function; The network module is used for data transmission in the camera system, and the integrated monitoring module is used to transmit the data of the monitoring equipment to the monitoring center. The intelligent routing algorithm is used to monitor the real-time network load and equipment demand through the monitoring module, so as to dynamically adjust the data transmission path; The switch quantity module is used to process switch quantity information and support the linkage between monitoring devices. It uses a high-speed digital signal processor DSP and a dedicated microcontroller to accelerate the processing and response of switch quantity signals. 485 communication module, used to realize communication between devices, supports data transmission and interaction of control commands, 485 communication module adopts differential signal transmission, and introduces error detection and correction mechanism; Intelligent network module uses deep learning algorithm to intelligently allocate network module routing and bandwidth by learning device usage patterns; it realizes real-time traffic monitoring and adaptively adjusts the transmission rate according to monitoring needs to ensure efficient transmission of camera monitoring images; Self-diagnosis module, integrated with self-diagnosis algorithm, monitors the status of each module, adopts secure encrypted communication protocol, and establishes remote management interface, cooperating with network module to provide remote status monitoring, fault diagnosis and firmware upgrade of camera system; The network data module is installed on the mounting base of the camera, and is connected to the weak current shaft or monitoring center via a power composite optical cable. When a new camera is added, the network data module of the new camera is connected to the existing network data module nearby via the power composite optical cable.

2. A network data module for a camera according to claim 1, characterized in that: In the power module, a power consumption monitoring chip is used to monitor the power consumption of the system in real time, and dynamic voltage adjustment is used to enable the power supply to adaptively adjust the power output under different workloads; The power module is integrated with a remote communication module, and a connection is established through a secure communication protocol. The remote monitoring center obtains the power status in real time, performs remote diagnosis, and adjusts the power output operation.

3. A network data module for a camera according to claim 2, characterized in that: In the network module, the data transmission path is dynamically adjusted by the intelligent routing algorithm as follows: Perform data collection and monitoring, and define the time series data set of equipment status and performance parameters as D t , the current network bandwidth utilization is BW t , the load data of the device is LD t , using sensors and monitoring modules to collect D t , Bandwidth utilization BW t and the load data LD of the device t ; Perform data preprocessing and define the time series data set of equipment status and performance parameters after preprocessing as D′ t , the load data of the preprocessed equipment is LD′ t , for D t and LD t Normalize, filter and process outliers to get D′ t and LD′ t ; The recurrent neural network and convolutional neural network training models are used to learn the usage pattern of the equipment. The weight and bias parameters of the neural network are set as W and b, and D′ t and LD′ t is the input, P t is the output, P t is the probability distribution of device usage patterns, which is calculated as follows: t =σ(WD′ t +b), where σ is the activation function.

4. A network data module for a camera according to claim 3, characterized in that: In the network module, the method for dynamically adjusting the data transmission path also includes: Determine the network module routing decision, define the current network topology as G, and according to the learned probability distribution of device usage patterns P t and the current network topology G, using the routing decision algorithm to determine the data transmission path R t ; The final data transmission path is R t ; According to the final data transmission path R t Dynamically adjust the path.

5. A network data module for a camera according to claim 4, characterized in that: The network module integrates a traffic monitoring module and a remote configuration interface, and adaptively adjusts the transmission rate through real-time monitoring of the transmission data; Establish a connection with the monitoring center through a secure communication protocol.

6. A network data module for a camera according to claim 5, characterized in that: In the network module, the transmission rate is adaptively adjusted in the following manner: Perform bandwidth allocation and rate adjustment, and define the bandwidth allocation vector as B t , the transmission rate vector is T t ; Based on the current network bandwidth utilization BW t and data transmission path R t , use the bandwidth allocation algorithm to determine the bandwidth allocation vector B t ; Based on real-time flow monitoring F t and the probability distribution P of device usage patterns t , using the rate adjustment algorithm to determine the transmission rate vector T t , specifically: B t =g(BW t ,R t ), T t =h(F t ,P t ), where h is the rate adjustment function and g is the bandwidth allocation vector function; Then the decision feedback is defined as F t , including data transmission success rate and device status information; The network module routing decision and the results of bandwidth allocation and rate adjustment R t , B t and T t As feedback information F t ; Then according to the feedback information F t , adjust the parameters and configuration of the network module to adapt to changes in network status in real time.

7. A network data module for a camera according to claim 6, characterized in that: In the 485 communication module, differential signal transmission is adopted, and the error detection introduced is specifically as follows: For differential signal transmission, the positive logic level is defined as V A , the inverse logic level is V B , data is D, using differential signal transmission, that is, transmitting signals through two lines A and B, where (V A -V B ) indicates a positive logic level, (V B -V A ) indicates negative logic level; Then error detection is performed, defining the number of data bits to be sent as M and the cyclic redundancy check code as CRC. In data transmission, after each M-bit data is sent, the CRC check code is calculated and appended to the data; After receiving the data, the receiving end recalculates the CRC check code of the received data and compares it with the attached CRC; If the two are inconsistent, it means an error has occurred and retransmission or other error handling is required.

8. A network data module for a camera according to claim 7, characterized in that: In the 485 communication module, differential signal transmission is adopted, and the error correction mechanism is specifically as follows: The number of error bits is defined as E. If an error is found during error detection, error correction is performed based on the error location information E. Hamming code is used to correct errors based on the erroneous position information and restore the original data; Specific: The sender adds an error correction code: C = D × G, where G is the error correction code generator matrix; After receiving C, the receiving end calculates the received error correction code C recive =C+E, where E is the error vector; Through the processing of error correction code, the receiving end can recive Restore the original data D.

9. A network data module for a camera according to claim 8, characterized in that: In the intelligent network module, the specific method of intelligently allocating network module routing and bandwidth is as follows: First, data collection and monitoring are performed. Assume that the real-time flow demand of device i is T i , the network link load from device i to device j is L ij ; Use sensors and monitoring modules to collect the flow demand of equipment in real time i and network link load L ij ; Assume that the routing decision from device i to device j is R ij , based on the traffic demand between devices T i , link load L ij And the learned device usage pattern, use the routing algorithm to determine the optimal transmission path R ij .

10. A network data module for a camera according to claim 9, characterized in that: In the intelligent network module, the intelligent allocation of network module routing and bandwidth also includes: Assume that the bandwidth allocation from device i to device j is B ij , according to the routing decision R ij , link load L ij and equipment flow demand T i , use bandwidth allocation algorithm to dynamically adjust bandwidth allocation B ij ; The flow demand estimation method is as follows: The real-time traffic demand from device i to device j is estimated to be T i =α×T i,avg +(1-α)×T i,current , where α is the smoothing coefficient, T i,avg is the average traffic demand of device i, T i,current is the current real-time traffic demand; The link load is updated in the following ways: The link load is dynamically updated using a weighted sliding average method, denoted as L ij =β×L ij,avg +(1-β)×L ij,current Where β is the second smoothing coefficient, L ij,avg is the average load of link i to j, L ij,current is the current real-time load.

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