A remote network control system based on intelligent robots

Abstract

This invention relates to the field of intelligent robot technology, specifically to a remote network control system based on intelligent robots, comprising: a monitoring module for monitoring the packet loss rate of environmental parameters collected during historical robot operation and during transmission; and a creation module for acquiring the number of online robots, creating a data transmission channel based on the number of online robots, and configuring the data transmission channel on the robots. This invention combines the packet loss rate of the robot's movement scenario and the packet loss rate of the robot when transmitting environmental parameter data packets to prioritize the robots for data transmission through the data transmission channel. Furthermore, it resets the operation control based on the system, enabling the system to continuously adapt to the actual performance state of the robots in real time, ensuring that robots with good performance can prioritize the execution of environmental parameter transmission tasks, thereby improving the effectiveness of the robot swarm in collecting environmental parameters and making the collection of environmental parameters in robot application scenarios more comprehensive.

Description

Technical Field

[0001] This invention relates to the field of intelligent robot technology, and more specifically to a remote network control system based on intelligent robots. Background Technology

[0002] A robot network is a system that connects multiple robots to each other and allows them to interact with an external control center or network environment. It enables information sharing and collaborative work among robots, such as multi-robot collaborative assembly in industrial production or group robots coordinating search and rescue operations in rescue scenarios. Through network command transmission and data interaction, it greatly improves the efficiency and intelligence of robot operations.

[0003] Patent application number 202410037400.3 discloses an artificial intelligence-based remote control system for intelligent robot operation. Its features include a patrol control module and a personnel identification module. The patrol control module controls the robot to patrol, identify target areas, obtain target area information, establish a region model based on the target area information, and divide the region model into several patrol zones. It dynamically calculates the patrol value of each patrol zone, marks each patrol value at the corresponding patrol zone in the region model, dynamically sorts the patrol zones according to their patrol values ​​from highest to lowest, and marks the first-ranked patrol zone as a priority patrol zone, controlling the robot to... When the robot reaches the priority patrol area, it patrols according to the patrol plan corresponding to the priority patrol area. The personnel identification module is used to identify personnel during the robot's patrol, optimize the robot's equipment, collect relevant personnel information in real time during the robot's patrol, analyze the obtained personnel information, and determine whether a person has been identified. If no person is identified, no corresponding operation is performed. If a person is identified, the corresponding person's identity is determined based on the personnel information. After the person's identity is determined, the corresponding identification record is marked, and the monitoring data of the identified person is obtained in real time. The obtained monitoring data and identification record are saved. If the person's identity cannot be determined, personnel anomaly handling is performed.

[0004] The application aims to address the following issues: "Existing robots often follow preset navigation routes when performing tasks. However, these routes are relatively fixed, allowing malicious individuals to predict when and where the patrol robots will appear based on daily observations. This presents an opportunity for malicious individuals to take advantage of the situation, posing a certain security risk. The identification and handling of abnormal individuals also presents certain problems, making it difficult to effectively identify abnormal individuals within the target area and prone to misjudgments, thus deviating from the original intention of setting up patrol robots."

[0005] However, robots that automatically find their way and collect environmental parameters are susceptible to interference from external factors during operation, which can affect the integrity and accuracy of the collected and transmitted environmental parameters due to network issues.

[0006] To address this, a remote network control system based on intelligent robots is proposed. Summary of the Invention

[0007] In view of the above-mentioned shortcomings of the existing technology, the present invention provides a remote network control system based on intelligent robots, which solves the technical problems mentioned in the background.

[0008] To achieve the above objectives, the present invention is implemented through the following technical solutions:

[0009] A remote network control system based on intelligent robots, comprising:

[0010] The system comprises the following modules: a monitoring module for monitoring the packet loss rate of environmental parameters collected during robot operation history; a creation module for obtaining the number of online robots, creating data transmission channels based on this number, configuring these channels on the robots, and configuring the robots to transmit the environmental parameters collected during operation; a configuration module for configuring the data transmission channels created in the creation module; a refresh module for refreshing the system operation; a control module for monitoring network security and controlling the robots' permissions to transmit environmental parameters using the data transmission channels based on the network security monitoring results; and a feedback module for calculating the average packet loss rate of the robots' historical operation and feeding back the average packet loss rate statistics to the system user.

[0011] In this system, users can read the average packet loss rate of each robot's historical operation from the feedback module, and perform offline system upgrades and optimizations based on the average packet loss rate of each robot.

[0012] Furthermore, the monitoring module has sub-modules at its lower level, including:

[0013] The identification unit is used to receive the robot's movement path during operation and to identify the complexity of the robot's movement scene based on the movement path.

[0014] The recording unit is used to acquire the packet loss rate and the corresponding complexity of the robot's movement scene during the transmission of environmental parameters monitored by the monitoring module, and to store the acquired packet loss rate and the complexity of the robot's movement scene.

[0015] Among them, when the recording unit stores the packet loss rate and the complexity of the robot's movement scene, it stores the packet loss rate and the complexity of the robot's movement scene in a one-to-one correspondence.

[0016] Furthermore, the packet loss rate of the environmental parameters collected during robot operation during transmission is calculated using the following formula:

[0017]

[0018] In the formula; P loss The packet loss rate during transmission is the environmental parameter; M is the number of data transmission rounds; n ri n is the number of data packets sent in the i-th round of data transmission; ti n represents the number of data packets successfully received in the i-th round of data transmission; oi n represents the number of data packets lost due to timeout in the i-th round of data transmission; bi This represents the number of data packets lost during the i-th round of data transmission due to buffer overflow at the receiving end.

[0019] Furthermore, the logic for recognizing the complexity of the robot's movement scene in the recognition unit is expressed as follows:

[0020]

[0021] In the formula: C represents the complexity of the robot's movement scenario; α, β, and γ are weighting coefficients; n is the total number of points on the robot's movement path; θ j Let L be the sequence of turning angles at the j-th point; L is the length of the robot's movement path; L0 is the straight-line distance between the start and end points of the robot's movement path.

[0022] The values ​​of the weighting coefficients α, β, and γ are user-defined on the system side, and all weighting coefficients are positive numbers less than 1. The turning angle sequence θ at the j-th point... j obey:

[0023] In the formula: It is the vector of the path segment defined by the j-th point and the (j+1)-th point in the robot's movement path; It is the vector of the road segment defined by the (j+1)th and (j+2)th points in the robot's movement path.

[0024] Furthermore, during the operation phase of the creation module, when the number of online robots is obtained and a data transmission channel is created based on the number of online robots, the number of data transmission channels created is always one less than the number of online robots.

[0025] The operation of creating a data transmission channel in the creation module is reset every time the number of online robots is updated.

[0026] Furthermore, the robot and the robot management backend that receives environmental parameters are deployed in the same network, and the data transmission channels created in the creation module are all created in this network;

[0027] The configuration module contains sub-modules, including:

[0028] The logic unit is used to set the configuration logic of the data transmission channel and the robot, and to execute the mutual configuration operation between the data transmission channel and the robot based on the configuration logic;

[0029] The data transmission channel and robot configuration logic set in the logic unit are as follows:

[0030] Obtain the current path the robot has moved, and retrieve the packet loss rate and the complexity of the robot's movement scenario from the corresponding records.

[0031] The complexity of the movement scene along the robot's current path is denoted as C. now ;

[0032] Further estimate the overall packet loss rate during transmission of the environmental parameters currently collected by the robot;

[0033]

[0034] In the formula: C represents the complexity of the robot's movement scenario; P loss The packet loss rate during transmission of environmental parameters collected by the robot; C now λ represents the complexity of the scene along the robot's current path; P is the correction factor. loss ′ represents the estimated overall packet loss rate during transmission of the environmental parameters currently being collected by the robot;

[0035] Data transmission channels are configured for each robot based on the estimated overall packet loss rate, with priority given to robots with higher estimated overall packet loss rates.

[0036] Furthermore, robots not configured with a data transmission channel will use an idle data transmission channel to perform data transmission operations when robots with a configured data transmission channel are not using their configured data transmission channel.

[0037] The value of the modified λ follows the following:

[0038] 2≥λ≥1, and C now The shorter the robot's traveled path or the shorter the time it took to travel that path, the larger the correction λ value; conversely, the larger the traveled path or the shorter the time it took to travel that path, the smaller the correction λ value.

[0039] Furthermore, the refresh module has sub-modules at its lower level, including:

[0040] The iteration unit is used to iterate the packet loss rate and the complexity of the robot's movement scenario stored in the recording unit.

[0041] The refresh module is triggered synchronously after each online robot completes an environmental parameter transmission operation. The iteration unit runs synchronously with the refresh module, iterating the data content originally stored in the recording unit based on the latest packet loss rate and the complexity of the mobile scene for each robot.

[0042] Furthermore, the control module shuts down all data transmission channels when it detects that the network status is insecure, and opens all data transmission channels when it detects that the network status is secure.

[0043] The network status security monitoring logic in the control module is as follows:

[0044] The ratio of network attack frequency to network attack interception probability is monitored in real time. If the ratio is equal to the network attack frequency itself, the network is secure; otherwise, the network is insecure.

[0045] Furthermore, the monitoring module is interconnected with an identification unit and a recording unit via a wireless network at its lower level. The monitoring module is also interconnected with a creation module and a configuration module via a wireless network. The configuration module contains a logic unit interconnected with a wireless network. The logic unit is interconnected with the recording unit via a wireless network. The configuration module is interconnected with a refresh module via a wireless network. The refresh module is interconnected with an iteration unit via a wireless network at its lower level. The refresh module is interconnected with a control module and a feedback module via a wireless network.

[0046] Compared with known public technologies, the technical solution provided by this invention has the following beneficial effects:

[0047] This invention provides a remote network control system based on intelligent robots. During operation, the system combines the packet loss rate of the robot's movement scenario and the packet loss rate of the robot when transmitting environmental parameter data packets to prioritize and configure the robots to perform data transmission through data transmission channels. Furthermore, based on system reset operation control, the system continuously adapts to the actual performance state of the robots in real time, ensuring that robots with good performance can prioritize the execution of environmental parameter transmission tasks. This improves the effectiveness of the robot swarm in collecting environmental parameters and makes the collection of environmental parameters in robot application scenarios more comprehensive. Attached Figure Description

[0048] To more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are only some embodiments of the present invention. Those skilled in the art can also derive other drawings based on these drawings without inventive effort.

[0049] Figure 1This is a schematic diagram of a remote network control system based on an intelligent robot. Detailed Implementation

[0050] To make the purpose, technical solutions, and advantages of the embodiments of the present invention more clear, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying 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 making any creative efforts shall fall within the scope of protection of the present invention.

[0051] The present invention will be further described below with reference to embodiments.

[0052] Example:

[0053] This embodiment provides a remote network control system based on an intelligent robot, such as... Figure 1 Shown, including:

[0054] The monitoring module is used to monitor the packet loss rate of environmental parameters collected during the transmission of historical data from the robot's operation.

[0055] The monitoring module has sub-modules, including:

[0056] The identification unit is used to receive the robot's movement path during operation and to identify the complexity of the robot's movement scene based on the movement path.

[0057] The recording unit is used to acquire the packet loss rate and the corresponding complexity of the robot's movement scene during the transmission of environmental parameters monitored by the monitoring module, and to store the acquired packet loss rate and the complexity of the robot's movement scene.

[0058] Among them, when the recording unit stores the packet loss rate and the complexity of the robot's movement scene, it binds the packet loss rate and the complexity of the robot's movement scene in a one-to-one correspondence.

[0059] Create a module to obtain the number of online robots, create a data transmission channel based on the number of online robots, and apply the data transmission channel configuration to the robot so that the robot can transmit the environmental parameters it collects during operation;

[0060] The packet loss rate of environmental parameters collected during robot operation during transmission is calculated using the following formula:

[0061]

[0062] In the formula; P loss The packet loss rate during transmission is the environmental parameter; M is the number of data transmission rounds; n rin is the number of data packets sent in the i-th round of data transmission; ti n represents the number of data packets successfully received in the i-th round of data transmission; oi n represents the number of data packets lost due to timeout in the i-th round of data transmission; bi This represents the number of data packets lost during the i-th round of data transmission due to buffer overflow at the receiving end;

[0063] The above logical formula limits the calculation method of packet loss rate of environmental parameters during transmission, providing further data support for the operation of modules in this system.

[0064] The logic for recognizing the complexity of robot movement scenes in the recognition unit is represented as follows:

[0065]

[0066] In the formula: C represents the complexity of the robot's movement scenario; α, β, and γ are weighting coefficients; n is the total number of points on the robot's movement path; θ j Let L be the sequence of turning angles at the j-th point; L is the length of the robot's movement path; L0 is the straight-line distance between the start and end points of the robot's movement path.

[0067] The values ​​of the weighting coefficients α, β, and γ are user-defined on the system side, and all weighting coefficients are positive numbers less than 1. The turning angle sequence θ at the j-th point... j obey:

[0068] In the formula: It is the vector of the path segment defined by the j-th point and the (j+1)-th point in the robot's movement path; It is the vector of the path segment defined by the (j+1)th and (j+2)th points in the robot's movement path;

[0069] The above logical formula is used to calculate the complexity of the robot's movement scenario, providing support for further calculation of the overall packet loss rate during transmission of the robot's current environmental parameters.

[0070] The configuration module is used to configure the data transmission channel created in the robot configuration module;

[0071] The robot and the robot management backend that receives environmental parameters are deployed on the same network, and the data transmission channels created in the creation module are all created in this network;

[0072] The configuration module contains sub-modules, including:

[0073] The logic unit is used to set the configuration logic of the data transmission channel and the robot, and to execute the mutual configuration operation between the data transmission channel and the robot based on the configuration logic;

[0074] The data transmission channel and robot configuration logic set in the logic unit are as follows:

[0075] Obtain the current path the robot has moved, and retrieve the packet loss rate and the complexity of the robot's movement scenario from the corresponding records.

[0076] The complexity of the movement scene along the robot's current path is denoted as C. now ;

[0077] Further estimate the overall packet loss rate during transmission of the environmental parameters currently collected by the robot;

[0078]

[0079] In the formula: C represents the complexity of the robot's movement scenario; P loss The packet loss rate during transmission of environmental parameters collected by the robot; C now λ represents the complexity of the scene along the robot's current path; P is the correction factor. loss ′ represents the estimated overall packet loss rate during transmission of the environmental parameters currently being collected by the robot;

[0080] The overall packet loss rate of the robot's current environmental parameters during transmission is calculated using the above logical formula, thus providing logical support for the configuration of the data transmission channel and the robot.

[0081] Data transmission channels are configured for each robot based on the estimated overall packet loss rate, with priority given to robots with higher estimated overall packet loss rates.

[0082] For robots not configured to a data transmission channel, when robots with configured data transmission channels are not using their configured data transmission channels, the idle data transmission channel will be used to perform data transmission operations.

[0083] The value of λ is modified to follow the following:

[0084] 2≥λ≥1, and C now The shorter the robot's path or the shorter the time it takes to move, the larger the correction λ value; conversely, the smaller the correction λ value.

[0085] The refresh module is used to refresh the system operation.

[0086] The refresh module has sub-modules, including:

[0087] The iteration unit is used to iterate the packet loss rate and the complexity of the robot's movement scenario stored in the recording unit.

[0088] The refresh module is triggered synchronously after each online robot completes an environmental parameter transmission operation. The iteration unit runs synchronously with the refresh module, and iterates the data content originally stored in the recording unit based on the latest packet loss rate of each robot and the complexity of the mobile scene.

[0089] The control module is used to monitor network security and, based on the network security monitoring results, control the robot's permissions to transmit environmental parameters through the data transmission channel.

[0090] When the control module detects that the network status is insecure, it shuts down all data transmission channels; when it detects that the network status is secure, it opens all data transmission channels.

[0091] The network status security monitoring logic in the control module is as follows:

[0092] The ratio of network attack frequency to network attack interception probability is monitored in real time. If the ratio is equal to the network attack frequency itself, the network is secure; otherwise, the network is insecure.

[0093] The feedback module is used to calculate the average packet loss rate of the robot's historical operations and to feed the average packet loss rate statistics back to the system user.

[0094] Among them, the system user reads the average packet loss rate of each robot's historical operation in the feedback module, and performs offline system upgrades and optimizations for each robot based on the robot's average packet loss rate.

[0095] The monitoring module has identification and recording units connected to its lower level via a wireless network. It also has creation and configuration modules connected via a wireless network. The configuration module has logic units connected via a wireless network. These logic units are connected to the recording units via a wireless network. The configuration module has a refresh module connected via a wireless network. The refresh module has an iteration unit connected via a wireless network. The refresh module also has a control and feedback module connected via a wireless network.

[0096] In this embodiment, the monitoring module monitors the packet loss rate of environmental parameters collected during the historical operation of the robot during transmission. The identification unit synchronously receives the robot's movement path during operation and identifies the complexity of the robot's movement scene based on the movement path. The recording unit obtains the packet loss rate of environmental parameters monitored by the monitoring module during transmission and the corresponding complexity of the robot's movement scene in real time, and stores the obtained packet loss rate and robot movement scene complexity. The creation module further obtains the number of online robots, creates a data transmission channel based on the number of online robots, and applies the data transmission channel to the robot for transmitting the environmental parameters collected during its operation. The configuration module runs afterward to configure the data transmission channel created in the creation module for the robot. The logic unit synchronously sets the configuration logic of the data transmission channel and the robot, and performs the mutual configuration operation of the data transmission channel and the robot based on the configuration logic. Then, the refresh module refreshes the system operation. The iteration unit synchronously iterates the packet loss rate and robot movement scene complexity stored in the recording unit. Finally, the control module monitors network security and controls the robot's permission to use the data transmission channel to transmit environmental parameters based on the network security monitoring results. The feedback module runs and counts the average packet loss rate of the robot's historical operation, and feeds back the average packet loss rate statistics to the system user.

[0097] Through the system operation described in the above embodiments, network management services are provided for robots that automatically find their way and collect environmental parameters, ensuring that the robots can transmit the environmental parameters they collect more stably and improving the effectiveness and comprehensiveness of the environmental parameters collected by the robot swarm.

[0098] like Figure 1 As shown, during the module operation phase, after obtaining the number of online robots, the data transmission channel is created based on the number of online robots. The number of data transmission channels created is always 1 less than the number of online robots.

[0099] The operation of creating a data transmission channel in the creation module is reset every time the number of online robots is updated.

[0100] The above settings provide further operational data support for the system operation in the above embodiments, ensuring the stable operation of the system in the above embodiments.

[0101] In summary, during operation, the system in the above embodiments combines the packet loss rate of the robot's movement scenario and the packet loss rate of the robot when transmitting environmental parameter data packets to prioritize and configure the robots to perform data transmission through the data transmission channel. Furthermore, based on the system's reset operation control, the system continuously adapts to the actual performance state of the robot's real-time operation, ensuring that robots with good performance can prioritize the execution of environmental parameter transmission tasks. This improves the effectiveness of the robot swarm in collecting environmental parameters and makes the collection of environmental parameters in robot application scenarios more comprehensive.

[0102] The above embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit it. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions will not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A remote network control system based on an intelligent robot, characterized in that, include: The monitoring module is used to monitor the packet loss rate of environmental parameters collected during the transmission of historical data from the robot's operation. Create a module to obtain the number of online robots, create a data transmission channel based on the number of online robots, and apply the data transmission channel configuration to the robot so that the robot can transmit the environmental parameters it collects during operation; The configuration module is used to configure the data transmission channel created in the robot configuration module; The refresh module is used to refresh the system operation. The control module is used to monitor network security and, based on the network security monitoring results, control the robot's permissions to transmit environmental parameters through the data transmission channel. The feedback module is used to calculate the average packet loss rate of the robot's historical operations and to feed the average packet loss rate statistics back to the system user. Among them, the system user reads the average packet loss rate of each robot's historical operation in the feedback module, and performs offline system upgrades and optimizations for each robot based on the robot's average packet loss rate. The robot and the robot management backend that receives environmental parameters are deployed on the same network, and the data transmission channels created in the creation module are all created in this network; The configuration module contains sub-modules, including: The logic unit is used to set the configuration logic of the data transmission channel and the robot, and to execute the mutual configuration operation between the data transmission channel and the robot based on the configuration logic; The data transmission channel and robot configuration logic set in the logic unit are as follows: Obtain the current path the robot has moved, and retrieve the packet loss rate and the complexity of the robot's movement scenario from the corresponding records. The complexity of the movement scene along the robot's current path is denoted as C. now ; Further estimate the overall packet loss rate during transmission of the environmental parameters currently collected by the robot; In the formula: C represents the complexity of the robot's movement scenario; P loss The packet loss rate during transmission of environmental parameters collected by the robot; C now λ represents the complexity of the scene along the robot's current path; P is the correction factor. loss ′ represents the estimated overall packet loss rate during transmission of the environmental parameters currently being collected by the robot; Data transmission channels are configured for each robot based on the estimated overall packet loss rate, with priority given to robots with higher estimated overall packet loss rates. For robots not configured to a data transmission channel, when robots with configured data transmission channels are not using their configured data transmission channels, the idle data transmission channel will be used to perform data transmission operations. The value of the modified λ follows the following: 2≥λ≥1, and C now The shorter the robot's traveled path or the shorter the time it took to travel that path, the larger the correction λ value; conversely, the larger the traveled path or the shorter the time it took to travel that path, the smaller the correction λ value.

2. The remote network control system based on an intelligent robot according to claim 1, characterized in that, The monitoring module has sub-modules at its lower level, including: The identification unit is used to receive the robot's movement path during operation and to identify the complexity of the robot's movement scene based on the movement path. The recording unit is used to acquire the packet loss rate and the corresponding complexity of the robot's movement scene during the transmission of environmental parameters monitored by the monitoring module, and to store the acquired packet loss rate and the complexity of the robot's movement scene. Among them, when the recording unit stores the packet loss rate and the complexity of the robot's movement scene, it stores the packet loss rate and the complexity of the robot's movement scene in a one-to-one correspondence.

3. A remote network control system based on an intelligent robot according to claim 2, characterized in that, The logic for recognizing the complexity of robot movement scenarios in the recognition unit is expressed as follows: In the formula: C represents the complexity of the robot's movement scenario; α, β, and γ are weighting coefficients; n is the total number of points on the robot's movement path; θ j Let L be the sequence of turning angles at the j-th point; L is the length of the robot's movement path; L0 is the straight-line distance between the start and end points of the robot's movement path. The values ​​of the weighting coefficients α, β, and γ are user-defined on the system side, and all weighting coefficients are positive numbers less than 1. The turning angle sequence θ at the j-th point... j obey: In the formula: It is the vector of the path segment defined by the j-th point and the (j+1)-th point in the robot's movement path; It is the vector of the road segment defined by the (j+1)th and (j+2)th points in the robot's movement path.

4. A remote network control system based on an intelligent robot according to claim 1, characterized in that, During the operation of the creation module, when the number of online robots is obtained and a data transmission channel is created based on the number of online robots, the number of data transmission channels created is always one less than the number of online robots. The operation of creating a data transmission channel in the creation module is reset every time the number of online robots is updated.

5. A remote network control system based on an intelligent robot according to claim 1, characterized in that, The refresh module has sub-modules at its lower level, including: The iteration unit is used to iterate the packet loss rate and the complexity of the robot's movement scenario stored in the recording unit. The refresh module is triggered synchronously after each online robot completes an environmental parameter transmission operation. The iteration unit runs synchronously with the refresh module, iterating the data content originally stored in the recording unit based on the latest packet loss rate and the complexity of the mobile scene for each robot.

6. A remote network control system based on an intelligent robot according to claim 1, characterized in that, When the control module detects that the network status is insecure, it shuts down all data transmission channels; when it detects that the network status is secure, it opens all data transmission channels. The network status security monitoring logic in the control module is as follows: The ratio of network attack frequency to network attack interception probability is monitored in real time. If the ratio is equal to the network attack frequency itself, the network is secure; otherwise, the network is insecure.

7. A remote network control system based on an intelligent robot according to claim 1, characterized in that, The monitoring module has an identification unit and a recording unit connected to it via a wireless network. The monitoring module also has a creation module and a configuration module connected to it via a wireless network. The configuration module has a logic unit connected to it via a wireless network. The logic unit is connected to the recording unit via a wireless network. The configuration module has a refresh module connected to it via a wireless network. The refresh module has an iteration unit connected to it via a wireless network. The refresh module also has a control module and a feedback module connected to it via a wireless network.

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