CN118430107B - Intelligent monitoring system for access control robot - Google Patents
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Abstract
The invention discloses an intelligent monitoring system for an access control robot, which comprises a robot information acquisition module, an image information acquisition module, a user information acquisition module, a robot hardware acquisition module, an environment information acquisition module, a data processing module and an information sending module, wherein the robot information acquisition module is used for acquiring information of the access control robot; the robot information acquisition module is used for acquiring relevant information of the robot; the image information acquisition module comprises a first image acquisition unit and a second image acquisition unit, wherein the first image acquisition unit is arranged on the access control robot and is used for acquiring images of the access control robot, the first image acquisition unit is used for acquiring first image information, and the second image acquisition unit is used for acquiring second image information; the robot image acquisition module is used for acquiring related information of robot hardware; the environment information acquisition module is used for acquiring environment information of the access control robot. The invention can monitor the access control robot more intelligently and comprehensively, and ensures more stable operation of the access control robot.
Description
Technical Field
The invention relates to the field of monitoring systems, in particular to an intelligent monitoring system for an access control robot.
Background
The entrance guard robot is a service robot, is widely applied to the management of entrance and exit gates of property companies, enterprises, communities and the like, can realize the intelligent management and recording of entrance and exit personnel and vehicles, and improves the efficiency and safety of entrance guard management. In addition, the entrance guard robot can be combined with scenes such as schools, communities, office buildings and the like to realize various functional applications such as temperature measurement epidemic prevention, entrance guard attendance, visitor management and the like;
the entrance guard robot can be applied to the monitoring system to monitor the entrance guard robot in the actual use process so as to ensure the stable operation of the entrance guard robot.
The existing monitoring system is single in monitoring type, so that the overall monitoring is poor, whether the access control robot is abnormal or not cannot be found timely, and certain influence is brought to the use of the monitoring system.
Disclosure of Invention
The technical problems to be solved by the invention are as follows: how to solve the problem that the use of the monitoring system is affected to a certain extent because the existing monitoring system is single in monitoring type, which results in poor overall monitoring and can not find out whether the access control robot is abnormal in time, provides an intelligent monitoring system for the access control robot.
The invention solves the technical problems through the following technical scheme that the invention comprises a robot information acquisition module, an image information acquisition module, a user information acquisition module, a robot hardware acquisition module, an environment information acquisition module, a data processing module and an information sending module;
The robot information acquisition module is used for acquiring relevant information of the robot;
The image information acquisition module comprises a first image acquisition unit and a second image acquisition unit, wherein the first image acquisition unit is arranged on the access control robot and is used for acquiring images of the access control robot, the first image acquisition unit is used for acquiring first image information, and the second image acquisition unit is used for acquiring second image information;
the robot image acquisition module is used for acquiring related information of robot hardware;
the environment information acquisition module is used for acquiring environment information of the access control robot;
The data processing module is used for processing the related information of the robot, the first image information, the second image information, the related information of the robot hardware and the environmental information of the access robot, and generating first monitoring management information, second monitoring management information, third monitoring management information and fourth monitoring management information;
The information sending module is used for sending the first monitoring management information, the second monitoring management information, the third monitoring management information and the fourth monitoring management information to a preset receiving terminal after the first monitoring management information, the second monitoring management information, the third monitoring management information and the fourth monitoring management information are generated.
Further, the specific processing procedure of the first monitoring management information is as follows: extracting collected relevant information of the robot, wherein the relevant information of the robot comprises hardware fault information, software fault information, robot operation response information and robot maintenance information;
processing the hardware fault information to obtain hardware fault evaluation parameters;
The software fault information is processed to obtain software evaluation parameters;
processing the robot operation response information to obtain response evaluation parameters;
when any one of the hardware fault evaluation parameter, the software evaluation parameter and the reaction evaluation parameter is abnormal, and the robot maintenance information is abnormal, first monitoring management information is generated.
Further, the hardware fault evaluation parameter acquiring process and the abnormality determining process are as follows:
The method comprises the steps of extracting collected hardware fault information and robot maintenance information, wherein the hardware fault information comprises human face identification failure frequency information, power supply failure frequency information and matched electric control lock failure frequency information within a preset time period;
Marking the failure times information of the face recognition equipment in the preset time as F1, marking the failure times information of the power supply in the preset time as F2, and marking the failure times information of the matched electric control lock as F3;
When any one of F1, F2 and F3 is larger than a preset value, directly generating first monitoring management information;
when each of F1, F2 and F3 is smaller than a preset value, giving F1 a correction value m1, F2 a correction value m2, F3 a correction value m3, m3 > m1 > m2, m1+m2+m3=1;
obtaining a hardware fault evaluation parameter Ff through a formula f1×m1+f2×m2+f3×m3=ff, and indicating that an abnormality exists when the hardware fault evaluation parameter Ff is greater than a preset value;
The software evaluation parameter acquisition process and the abnormality judgment process are as follows:
Extracting collected hardware fault information, wherein the hardware fault information comprises the abnormal times of a face database within a preset time length, the setting or configuration fault times of access control equipment and the number of software loopholes;
Marking the abnormal times of the face database within a preset time length as E1, marking the set or configured fault times of the access control equipment as E2 and marking the number of software vulnerabilities as E3;
when any one of E1, E2 and E3 is larger than a preset value, directly generating first monitoring management information;
When E1, E2 and E3 are smaller than the preset value, giving a correction value g1 to E1, a correction value g2 to E2, and a correction value g3 to E3, wherein g3 is larger than g2 and larger than g1, and g1+g2+g3=1;
the software fault evaluation parameter Ee is obtained through the formula e1+m1+e2+m2+e3=e3, and when the hardware fault evaluation parameter Ee is greater than a preset value, the abnormality exists.
Further, the specific acquisition process of the reaction evaluation parameters is as follows: the collected robot operation response information is extracted, the robot operation response information is speed information for allowing the gate to be opened after the entrance guard robot recognizes the passers, x times of robot operation response information is continuously collected, the average value of the x times of robot operation response information is calculated, namely, a response evaluation parameter is obtained, and when the response evaluation parameter is larger than a preset value, the condition that the response evaluation parameter is abnormal is indicated.
Further, the specific processing procedure of the second monitoring management information is as follows: extracting first image information acquired during personnel identity recognition of the access control robot;
the method comprises the steps of performing human body recognition on a first image, performing human body height recognition after recognizing a human body, acquiring estimated height information, and extracting robot hardware related information when the estimated height information is larger than a preset value, wherein the robot hardware related information comprises the height of face acquisition equipment on an access control robot;
processing the estimated height information and the height of the face acquisition equipment to obtain control estimated parameters;
when the control evaluation parameter is abnormal, generating second monitoring management information;
And extracting the acquired second image information, processing the second image information, acquiring real-time appearance information of the access control robot, comparing the real-time appearance information of the access control robot with the standard robot appearance information of a preset value, acquiring appearance comparison similarity, and generating second monitoring management information when the appearance comparison similarity is smaller than the preset value.
Further, the specific processing procedure for processing the estimated height information and the height of the face acquisition equipment to obtain the control estimated parameters is as follows: extracting the acquired estimated height information and the height of the face acquisition equipment, marking the estimated height information as H1, marking the height of the face acquisition equipment as H2, and setting a correction value alpha;
By the formula h1×α -h2=hh, when Hh is greater than a preset value, it indicates that the control evaluation parameter is abnormal.
Further, the specific processing procedure of the evaluation of the height information is as follows: extracting a first image which is acquired, identifying a human body image from the first image, identifying the nose tip and the earlobe in the human body image, marking the nose tip and any one of two earlobe points as a point a1 when only identifying the nose tip and the earlobe, taking the point a1 as an endpoint to make a vertical line section perpendicular to the plane of the human foot, and measuring the length of the vertical line section to obtain the estimated height information;
When at least any two points of a nose point and two earlobe points are identified, marking the two identified points as points a1 and a2, taking the points a1 and a2 as endpoints to make a vertical line section perpendicular to a plane where the feet of a human body are positioned, measuring the lengths of the two vertical line sections, and calculating the average value of the lengths of the two vertical line sections to obtain estimated height information;
When the nose point and the two earlobe points are identified at the same time, the two identified points are marked as points a1, a2 and a3, a perpendicular line section perpendicular to the plane of the foot of the human body is made by taking the points a1, a2 and a3 as endpoints, the lengths of the three perpendicular line sections are measured, and the average value of the lengths of the three perpendicular line sections is calculated, so that the estimated height information is obtained.
Further, the specific processing procedure of the third monitoring management information is as follows: the method comprises the steps of extracting collected related information of robot hardware, wherein the related information of the robot hardware comprises external stress information of the robot hardware, stress information of barrier gate equipment of the robot and identification equipment information;
The method comprises the steps of extracting the acquired external stress information of the robot hardware, generating third monitoring management information when the external stress information of the robot hardware is larger than a preset value z1, processing the external stress information of the robot hardware to acquire stress evaluation parameters, and generating the third monitoring management information when the stress evaluation parameters are abnormal;
when the stress information of the barrier gate equipment of the robot is larger than a preset value, third monitoring management information of the robot is generated;
the identification equipment information comprises card reading equipment identification accuracy, face identification equipment accuracy and fingerprint identification equipment identification accuracy;
Calculating the difference between the identification accuracy of the card reading equipment and the standard card reading identification accuracy, acquiring the difference between the card reading identification difference, the accuracy of the face recognition equipment and the standard face recognition accuracy, acquiring the face recognition difference, and acquiring the difference between the fingerprint identification equipment identification accuracy and the standard fingerprint identification accuracy;
And when any one of the card reading identification difference, the face recognition difference and the fingerprint identification difference is smaller than a preset value, generating third monitoring management information.
Further, the specific processing procedure of the fourth monitoring management information is as follows: extracting the collected environment information of the access control robot, wherein the environment information of the access control robot comprises environment temperature information, environment humidity information and equipment illumination time length information;
when the environmental temperature information is larger than a preset value u1 or smaller than a preset value u2 for longer than a preset time period, fourth monitoring management information is generated, and u1 is larger than u2;
when the environmental humidity information is larger than the preset value and exceeds the preset time, fourth monitoring management information is generated;
And when the equipment illumination duration information is greater than the preset value duration and the environment temperature information is greater than the preset value, generating fourth monitoring management information.
Compared with the prior art, the invention has the following advantages: this an intelligent monitoring system for entrance guard robot, through the first monitoring management information that generates, the second monitoring management information, third monitoring management information and fourth monitoring management information, the comprehensive intelligent monitoring management to entrance guard robot has been realized, the first supervision information of generation, it is unusual to produce at entrance guard robot self state, prompt manager's maintenance, the steady operation that entrance guard robot can be long between has been guaranteed, the second monitoring management information of generation has been realized intelligent control entrance guard robot, make entrance guard robot can adjust face acquisition equipment's height according to the user's of verification identity height, and then carry out more accurate face image acquisition, promote face recognition degree of accuracy, whether the outside of entrance guard robot receives the damage through carrying out analysis to entrance guard robot simultaneously, the security of entrance guard robot has been guaranteed in realizing intelligent control, the third monitoring management information of generation and fourth monitoring management information carry out the analysis to entrance guard robot's hardware state and environmental condition, and generate corresponding prompt information, and then realized the intelligent monitoring to entrance guard robot's integration, let this system be worth more popularization and application.
Drawings
Fig. 1 is a system block diagram of the present invention.
Detailed Description
The following describes in detail the examples of the present invention, which are implemented on the premise of the technical solution of the present invention, and detailed embodiments and specific operation procedures are given, but the scope of protection of the present invention is not limited to the following examples.
As shown in fig. 1, this embodiment provides a technical solution: an intelligent monitoring system for an access control robot comprises a robot information acquisition module, an image information acquisition module, a user information acquisition module, a robot hardware acquisition module, an environment information acquisition module, a data processing module and an information sending module;
The robot information acquisition module is used for acquiring relevant information of the robot;
The image information acquisition module comprises a first image acquisition unit and a second image acquisition unit, wherein the first image acquisition unit is arranged on the access control robot and is used for acquiring images of the access control robot, the first image acquisition unit is used for acquiring first image information, and the second image acquisition unit is used for acquiring second image information;
the robot image acquisition module is used for acquiring related information of robot hardware;
the environment information acquisition module is used for acquiring environment information of the access control robot;
The data processing module is used for processing the related information of the robot, the first image information, the second image information, the related information of the robot hardware and the environmental information of the access robot, and generating first monitoring management information, second monitoring management information, third monitoring management information and fourth monitoring management information;
The information sending module is used for sending the first monitoring management information, the second monitoring management information, the third monitoring management information and the fourth monitoring management information to a preset receiving terminal after the first monitoring management information, the second monitoring management information, the third monitoring management information and the fourth monitoring management information are generated;
according to the intelligent monitoring method, the first monitoring management information, the second monitoring management information, the third monitoring management information and the fourth monitoring management information are generated, so that comprehensive intelligent monitoring management of the entrance guard robot is realized, the generated first monitoring management information is generated when the state of the entrance guard robot is abnormal, a manager is prompted to carry out maintenance, the entrance guard robot is guaranteed to stably operate for a long time, the generated second monitoring management information is used for intelligently controlling the entrance guard robot, the entrance guard robot can adjust the height of face acquisition equipment according to the height of a user verifying identity, further more accurate face image acquisition is performed, face recognition accuracy is improved, meanwhile, whether the outside of the entrance guard robot is damaged is known through analysis of the appearance image of the entrance guard robot, safety of the entrance guard robot is guaranteed while intelligent control is realized, the hardware state and the environment state of the entrance guard robot are analyzed by the generated third monitoring management information and the fourth monitoring management information, corresponding prompt information is generated, and further integrated intelligent monitoring of the entrance guard robot is realized.
The specific processing procedure of the first monitoring management information is as follows: extracting collected relevant information of the robot, wherein the relevant information of the robot comprises hardware fault information, software fault information, robot operation response information and robot maintenance information;
processing the hardware fault information to obtain hardware fault evaluation parameters;
The software fault information is processed to obtain software evaluation parameters;
processing the robot operation response information to obtain response evaluation parameters;
When any one of the hardware fault evaluation parameter, the software evaluation parameter and the reaction evaluation parameter is abnormal, and the robot maintenance information is abnormal, first monitoring management information is generated, wherein the specific content of the first monitoring management information is that the hardware state of the access control robot is abnormal, equipment of the access control robot needs to be maintained, and meanwhile overhaul and maintenance frequency is improved.
The hardware fault evaluation parameter acquisition process and the abnormality judgment process are as follows:
The method comprises the steps of extracting collected hardware fault information and robot maintenance information, wherein the hardware fault information comprises human face identification failure frequency information, power supply failure frequency information and matched electric control lock failure frequency information within a preset time period;
Marking the failure times information of the face recognition equipment in the preset time as F1, marking the failure times information of the power supply in the preset time as F2, and marking the failure times information of the matched electric control lock as F3;
When any one of F1, F2 and F3 is larger than a preset value, directly generating first monitoring management information;
when each of F1, F2 and F3 is smaller than a preset value, giving F1 a correction value m1, F2 a correction value m2, F3 a correction value m3, m3 > m1 > m2, m1+m2+m3=1;
obtaining a hardware fault evaluation parameter Ff through a formula f1×m1+f2×m2+f3×m3=ff, and indicating that an abnormality exists when the hardware fault evaluation parameter Ff is greater than a preset value;
The software evaluation parameter acquisition process and the abnormality judgment process are as follows:
Extracting collected hardware fault information, wherein the hardware fault information comprises the abnormal times of a face database within a preset time length, the setting or configuration fault times of access control equipment and the number of software loopholes;
Marking the abnormal times of the face database within a preset time length as E1, marking the set or configured fault times of the access control equipment as E2 and marking the number of software vulnerabilities as E3;
when any one of E1, E2 and E3 is larger than a preset value, directly generating first monitoring management information;
When E1, E2 and E3 are smaller than the preset value, giving a correction value g1 to E1, a correction value g2 to E2, and a correction value g3 to E3, wherein g3 is larger than g2 and larger than g1, and g1+g2+g3=1;
Obtaining a software fault evaluation parameter Ee through a formula e1+e2+m2+e3+m3=ee, wherein when the hardware fault evaluation parameter Ee is greater than a preset value, the software fault evaluation parameter Ee is abnormal;
the specific acquisition process of the reaction evaluation parameters is as follows: extracting collected robot operation response information, wherein the robot operation response information is speed information for allowing the entrance guard robot to recognize that the gate is opened after passing personnel, continuously collecting x times of robot operation response information, calculating the average value of the x times of robot operation response information, namely obtaining response evaluation parameters, and indicating that the response evaluation parameters are abnormal when the response evaluation parameters are larger than preset values;
Through the process, more accurate parameter information can be obtained, and the accuracy of the first monitoring management information generation is further guaranteed.
The specific processing procedure of the second monitoring management information is as follows: extracting first image information acquired during personnel identity recognition of the access control robot;
the method comprises the steps of performing human body recognition on a first image, performing human body height recognition after recognizing a human body, acquiring estimated height information, and extracting robot hardware related information when the estimated height information is larger than a preset value, wherein the robot hardware related information comprises the height of face acquisition equipment on an access control robot;
processing the estimated height information and the height of the face acquisition equipment to obtain control estimated parameters;
When the control evaluation parameters are abnormal, generating second monitoring management information, wherein the second monitoring management information is sent to the access control robot, and the access control robot controls and adjusts the height of the face acquisition equipment, wherein the adjusted height numerical range is the current evaluation height + -5 cm;
extracting the collected second image information, processing the second image information to obtain real-time appearance information of the access control robot, comparing the real-time appearance information of the access control robot with the standard robot appearance information of a preset value to obtain appearance comparison similarity, and generating second monitoring management information when the appearance comparison similarity is smaller than the preset value, wherein the specific content of the second monitoring management information is that the exterior of the access control robot is possibly damaged and needs to be adjusted;
Above-mentioned process, when realizing the intelligent control to access robot through image analysis, the outside that discovers access robot that can be timely has suffered the damage, and then guaranteed access robot's safe and stable operation, better completion access protection work.
The specific processing procedure for processing the estimated height information and the height of the face acquisition equipment to obtain the control estimated parameters is as follows: extracting the acquired estimated height information and the height of the face acquisition equipment, marking the estimated height information as H1, marking the height of the face acquisition equipment as H2, and setting a correction value alpha;
By the formula h1×α -h2=hh, when Hh is greater than a preset value, it indicates that the control evaluation parameter is abnormal.
Further, the specific processing procedure of the evaluation of the height information is as follows: extracting a first image which is acquired, identifying a human body image from the first image, identifying the nose tip and the earlobe in the human body image, marking the nose tip and any one of two earlobe points as a point a1 when only identifying the nose tip and the earlobe, taking the point a1 as an endpoint to make a vertical line section perpendicular to the plane of the human foot, and measuring the length of the vertical line section to obtain the estimated height information;
When at least any two points of a nose point and two earlobe points are identified, marking the two identified points as points a1 and a2, taking the points a1 and a2 as endpoints to make a vertical line section perpendicular to a plane where the feet of a human body are positioned, measuring the lengths of the two vertical line sections, and calculating the average value of the lengths of the two vertical line sections to obtain estimated height information;
When the nose point and the two earlobe points are identified at the same time, the two identified points are marked as points a1, a2 and a3, the points a1, a2 and a3 are taken as endpoints to form a vertical line section perpendicular to the plane where the feet of the human body are positioned, the lengths of the three vertical line sections are measured, and the average value of the lengths of the three vertical line sections is calculated, so that the estimated height information is obtained.
The specific processing procedure of the third monitoring management information is as follows: the method comprises the steps of extracting collected related information of robot hardware, wherein the related information of the robot hardware comprises external stress information of the robot hardware, stress information of barrier gate equipment of the robot and identification equipment information;
The method comprises the steps of extracting the acquired external stress information of the robot hardware, generating third monitoring management information when the external stress information of the robot hardware is larger than a preset value z1, processing the external stress information of the robot hardware to acquire stress evaluation parameters, and generating the third monitoring management information when the stress evaluation parameters are abnormal;
when the stress information of the barrier gate equipment of the robot is larger than a preset value, third monitoring management information of the robot is generated;
the identification equipment information comprises card reading equipment identification accuracy, face identification equipment accuracy and fingerprint identification equipment identification accuracy;
Calculating the difference between the identification accuracy of the card reading equipment and the standard card reading identification accuracy, acquiring the difference between the card reading identification difference, the accuracy of the face recognition equipment and the standard face recognition accuracy, acquiring the face recognition difference, and acquiring the difference between the fingerprint identification equipment identification accuracy and the standard fingerprint identification accuracy;
When any one of the card reading identification difference, the face recognition difference and the fingerprint identification difference is smaller than a preset value, third monitoring management information is generated;
The stress information of the access control robot is analyzed, the stability of equipment can be improved, and the stress conditions of the access control robot in different working states can be known by analyzing the stress information of the access control robot and the gateway, so that the design of the equipment is optimized, and the stability and durability of the equipment are improved.
For example, if the access robot is easily damaged when it is subjected to an abnormal external force, the structure thereof may be reinforced or improved according to the result of the force analysis to improve the impact resistance thereof.
The monitoring of stress information can help to find potential problems and hidden dangers and prevent faults and damages caused by uneven stress or overlarge stress.
The method has important significance for ensuring continuous and stable operation of the access control system, and can avoid safety risks caused by equipment faults.
The operation flow is optimized, and the stress information analysis can also help to optimize the operation flow of the access control system, so that abnormal stress of equipment caused by improper operation is reduced.
For example, the lifting speed and the lifting force of the barrier gate can be adjusted by analyzing the stress information of the barrier gate, so that the barrier gate meets the use habit and the requirement of a user.
Meanwhile, the safety can be improved by analyzing the identification accuracy, and only authorized personnel can enter the protected area by improving the identification accuracy, so that the safety of the access control system is greatly improved.
This has an important role in preventing unauthorized intrusion and the like.
The user experience is improved, the waiting time of the user can be reduced through accurate and rapid identity recognition, the passing efficiency of the user is improved, and therefore the use experience of the user is improved.
For example, the access control system adopting the face recognition technology can complete the authentication and release operation within a few seconds, thereby bringing great convenience to users.
The performance of the access control system is optimized, the improvement of the identification accuracy can also help to optimize the performance of the access control system, and the waste of system resources and the reduction of efficiency caused by misidentification or missed identification are reduced.
By combining the analysis, the analysis of the stress information of the access robot, the stress information of the barrier gate and the identification accuracy has the following advantages: the method and the device have the advantages of improving equipment stability, preventing faults, optimizing operation flow, improving safety, improving user experience and optimizing system performance. The advantages are that the operation of the access control system is more stable, reliable and efficient, and better use experience and safety guarantee are brought to users.
The specific processing procedure of the fourth monitoring management information is as follows: extracting the collected environment information of the access control robot, wherein the environment information of the access control robot comprises environment temperature information, environment humidity information and equipment illumination time length information;
when the environmental temperature information is larger than a preset value u1 or smaller than a preset value u2 for longer than a preset time period, fourth monitoring management information is generated, and u1 is larger than u2;
when the environmental humidity information is larger than the preset value and exceeds the preset time, fourth monitoring management information is generated;
The equipment illumination time length information is the time length of the entrance guard robot irradiated by sunlight, and when the equipment illumination time length information is longer than a preset value time length and the environment temperature information is longer than a preset value, fourth monitoring management information is generated;
The device stability can be improved by performing temperature monitoring: the proper temperature range is the key for ensuring the normal operation of the access control robot. Through monitoring and analysis of the environmental temperature, the entrance guard robot can be ensured to run in the working temperature range, and equipment faults or performance degradation caused by overhigh or overlow temperature are avoided.
Preventing the equipment from overheating: the high temperature may cause overheating of internal components of the access robot, thereby causing malfunction of the equipment. Through temperature analysis, potential overheating problems can be found and processed in time, and equipment damage is avoided.
Optimizing the performance of equipment: the performance of certain access robot assemblies may be affected by temperature. By temperature analysis, the operating state or operating environment of the device can be adjusted to obtain optimal performance.
Preventing the equipment from being wetted: the high humidity may cause the internal components of the access control robot to be wetted, causing problems such as short circuit or corrosion. Through humidity analysis, potential humidity problems can be found and treated in time, and equipment is protected from damage.
Prolonging the service life of equipment: the suitable humidity environment is favorable for prolonging the service life of the access control robot. Through humidity analysis, the equipment can be ensured to operate in a proper humidity range, and equipment faults and damages caused by humidity problems are reduced.
The benefits of solar irradiation duration analysis on an access control robot are mainly realized in the following aspects:
And (3) temperature control: the duration of the solar irradiation directly influences the temperature of the device. Long direct sunlight may cause the device to overheat, thereby affecting its performance and lifetime. By analyzing the sunlight irradiation time, the temperature control design can be performed on the equipment in a targeted manner, such as heat dissipation elements including heat dissipation fins, fans and the like, so that the equipment can be ensured to stably run in a high-temperature environment.
Image recognition effect: for an access control robot relying on a camera for identity recognition, the sunlight irradiation time can influence the image quality. By analyzing the sunlight irradiation time, parameters such as exposure time, gain and the like of the camera can be optimized, so that a clearer and accurate image can be obtained, and the recognition rate can be improved.
And the false alarm rate is reduced: solar radiation may lead to equipment misinterpretation, such as misinterpreting shadows under solar radiation as personnel. Through the analysis of the sunlight irradiation duration, the recognition algorithm of the equipment can be optimized, the false alarm rate is reduced, and the reliability of the system is improved.
Furthermore, the terms "first," "second," and the like, are used for descriptive purposes only and are not to be construed as indicating or implying a relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defining "a first" or "a second" may explicitly or implicitly include at least one such feature. In the description of the present invention, the meaning of "plurality" means at least two, for example, two, three, etc., unless specifically defined otherwise.
In the description of the present specification, a description referring to terms "one embodiment," "some embodiments," "examples," "specific examples," or "some examples," etc., means that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the present invention. In this specification, schematic representations of the above terms are not necessarily directed to the same embodiment or example. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples. Furthermore, the different embodiments or examples described in this specification and the features of the different embodiments or examples may be combined and combined by those skilled in the art without contradiction.
While embodiments of the present invention have been shown and described above, it will be understood that the above embodiments are illustrative and not to be construed as limiting the invention, and that variations, modifications, alternatives and variations may be made to the above embodiments by one of ordinary skill in the art within the scope of the invention.
Claims (5)
1. The intelligent monitoring system for the access control robot is characterized by comprising a robot information acquisition module, an image information acquisition module, a user information acquisition module, a robot hardware acquisition module, an environment information acquisition module, a data processing module and an information sending module;
The robot information acquisition module is used for acquiring relevant information of the robot;
The image information acquisition module comprises a first image acquisition unit and a second image acquisition unit, wherein the first image acquisition unit is arranged on the access control robot and is used for acquiring images of the access control robot, the first image acquisition unit is used for acquiring first image information, and the second image acquisition unit is used for acquiring second image information;
The robot hardware acquisition module is used for acquiring related information of the robot hardware;
the environment information acquisition module is used for acquiring environment information of the access control robot;
The data processing module is used for processing the related information of the robot, the first image information, the second image information, the related information of the robot hardware and the environmental information of the access robot, and generating first monitoring management information, second monitoring management information, third monitoring management information and fourth monitoring management information;
The information sending module is used for sending the first monitoring management information, the second monitoring management information, the third monitoring management information and the fourth monitoring management information to a preset receiving terminal after the first monitoring management information, the second monitoring management information, the third monitoring management information and the fourth monitoring management information are generated;
The specific processing procedure of the first monitoring management information is as follows: extracting collected relevant information of the robot, wherein the relevant information of the robot comprises hardware fault information, software fault information, robot operation response information and robot maintenance information;
processing the hardware fault information to obtain hardware fault evaluation parameters;
The software fault information is processed to obtain software evaluation parameters;
processing the robot operation response information to obtain response evaluation parameters;
When any one of the hardware fault evaluation parameter, the software evaluation parameter and the reaction evaluation parameter is abnormal, and the robot maintenance information is abnormal, generating first monitoring management information;
the specific processing procedure of the second monitoring management information is as follows: extracting first image information acquired during personnel identity recognition of the access control robot;
the method comprises the steps of performing human body recognition on a first image, performing human body height recognition after recognizing a human body, acquiring estimated height information, and extracting robot hardware related information when the estimated height information is larger than a preset value, wherein the robot hardware related information comprises the height of face acquisition equipment on an access control robot;
processing the estimated height information and the height of the face acquisition equipment to obtain control estimated parameters;
when the control evaluation parameter is abnormal, generating second monitoring management information;
Extracting the collected second image information, processing the second image information to obtain real-time appearance information of the access control robot, comparing the real-time appearance information of the access control robot with the standard robot appearance information of a preset value to obtain appearance comparison similarity, and generating second monitoring management information when the appearance comparison similarity is smaller than the preset value;
the specific processing procedure of the third monitoring management information is as follows: the method comprises the steps of extracting collected related information of robot hardware, wherein the related information of the robot hardware comprises external stress information of the robot hardware, stress information of barrier gate equipment of the robot and identification equipment information;
The method comprises the steps of extracting the acquired external stress information of the robot hardware, generating third monitoring management information when the external stress information of the robot hardware is larger than a preset value z1, processing the external stress information of the robot hardware to acquire stress evaluation parameters, and generating the third monitoring management information when the stress evaluation parameters are abnormal;
when the stress information of the barrier gate equipment of the robot is larger than a preset value, third monitoring management information of the robot is generated;
the identification equipment information comprises card reading equipment identification accuracy, face identification equipment accuracy and fingerprint identification equipment identification accuracy;
Calculating the difference between the identification accuracy of the card reading equipment and the standard card reading identification accuracy, acquiring the difference between the card reading identification difference, the accuracy of the face recognition equipment and the standard face recognition accuracy, acquiring the face recognition difference, and acquiring the difference between the fingerprint identification equipment identification accuracy and the standard fingerprint identification accuracy;
When any one of the card reading identification difference, the face recognition difference and the fingerprint identification difference is smaller than a preset value, third monitoring management information is generated;
the specific processing procedure of the fourth monitoring management information is as follows: extracting the collected environment information of the access control robot, wherein the environment information of the access control robot comprises environment temperature information, environment humidity information and equipment illumination time length information;
when the environmental temperature information is larger than a preset value u1 or smaller than a preset value u2 for longer than a preset time period, fourth monitoring management information is generated, and u1 is larger than u2;
when the environmental humidity information is larger than the preset value and exceeds the preset time, fourth monitoring management information is generated;
And when the equipment illumination duration information is greater than the preset value duration and the environment temperature information is greater than the preset value, generating fourth monitoring management information.
2. The intelligent monitoring system for an access robot of claim 1, wherein: the hardware fault evaluation parameter acquisition process and the abnormality judgment process are as follows:
The method comprises the steps of extracting collected hardware fault information and robot maintenance information, wherein the hardware fault information comprises human face identification failure frequency information, power supply failure frequency information and matched electric control lock failure frequency information within a preset time period;
Marking the failure times information of the face recognition equipment in the preset time as F1, marking the failure times information of the power supply in the preset time as F2, and marking the failure times information of the matched electric control lock as F3;
When any one of F1, F2 and F3 is larger than a preset value, directly generating first monitoring management information;
when each of F1, F2 and F3 is smaller than a preset value, giving F1 a correction value m1, F2 a correction value m2, F3 a correction value m3, m3 > m1 > m2, m1+m2+m3=1;
obtaining a hardware fault evaluation parameter Ff through a formula f1×m1+f2×m2+f3×m3=ff, and indicating that an abnormality exists when the hardware fault evaluation parameter Ff is greater than a preset value;
The software evaluation parameter acquisition process and the abnormality judgment process are as follows:
Extracting collected hardware fault information, wherein the hardware fault information comprises the abnormal times of a face database within a preset time length, the setting or configuration fault times of access control equipment and the number of software loopholes;
Marking the abnormal times of the face database within a preset time length as E1, marking the set or configured fault times of the access control equipment as E2 and marking the number of software vulnerabilities as E3;
when any one of E1, E2 and E3 is larger than a preset value, directly generating first monitoring management information;
When E1, E2 and E3 are smaller than the preset value, giving a correction value g1 to E1, a correction value g2 to E2, and a correction value g3 to E3, wherein g3 is larger than g2 and larger than g1, and g1+g2+g3=1;
the software fault evaluation parameter Ee is obtained through the formula e1+m1+e2+m2+e3=e3, and when the hardware fault evaluation parameter Ee is greater than a preset value, the abnormality exists.
3. The intelligent monitoring system for an access robot of claim 1, wherein: the specific acquisition process of the reaction evaluation parameters is as follows: the collected robot operation response information is extracted, the robot operation response information is speed information for allowing the gate to be opened after the entrance guard robot recognizes the passers, x times of robot operation response information is continuously collected, the average value of the x times of robot operation response information is calculated, namely, a response evaluation parameter is obtained, and when the response evaluation parameter is larger than a preset value, the condition that the response evaluation parameter is abnormal is indicated.
4. The intelligent monitoring system for an access robot of claim 1, wherein: the specific processing procedure for processing the estimated height information and the height of the face acquisition equipment to obtain the control estimated parameters is as follows: extracting the acquired estimated height information and the height of the face acquisition equipment, marking the estimated height information as H1, marking the height of the face acquisition equipment as H2, and setting a correction value alpha;
By the formula h1×α -h2=hh, when Hh is greater than a preset value, it indicates that the control evaluation parameter is abnormal.
5. The intelligent monitoring system for an access robot of claim 1, wherein: the specific processing procedure of the estimated height information is as follows: extracting a first image which is acquired, identifying a human body image from the first image, identifying the nose tip and the earlobe in the human body image, marking the nose tip and any one of two earlobe points as a point a1 when only identifying the nose tip and the earlobe, taking the point a1 as an endpoint to make a vertical line section perpendicular to the plane of the human foot, and measuring the length of the vertical line section to obtain the estimated height information;
When at least any two points of a nose point and two earlobe points are identified, marking the two identified points as points a1 and a2, taking the points a1 and a2 as endpoints to make a vertical line section perpendicular to a plane where the feet of a human body are positioned, measuring the lengths of the two vertical line sections, and calculating the average value of the lengths of the two vertical line sections to obtain estimated height information;
When the nose point and the two earlobe points are identified at the same time, the two identified points are marked as points a1, a2 and a3, a perpendicular line section perpendicular to the plane of the foot of the human body is made by taking the points a1, a2 and a3 as endpoints, the lengths of the three perpendicular line sections are measured, and the average value of the lengths of the three perpendicular line sections is calculated, so that the estimated height information is obtained.
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| CN108284449A (en) * | 2018-03-16 | 2018-07-17 | 苏州博众机器人有限公司 | A kind of method on duty of door guard robot and door guard robot |
| CN113650028A (en) * | 2021-08-23 | 2021-11-16 | 国中绿电(苏州)碳中和研究院有限公司 | Intelligent entrance guard robot and operation method thereof |
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| US20210256466A1 (en) * | 2020-02-14 | 2021-08-19 | Zoox, Inc. | Mobile delivery vehicle management and routing |
| JP2021135895A (en) * | 2020-02-28 | 2021-09-13 | 三菱重工業株式会社 | Detection device, detection method, robot, and program |
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| CN108284449A (en) * | 2018-03-16 | 2018-07-17 | 苏州博众机器人有限公司 | A kind of method on duty of door guard robot and door guard robot |
| CN113650028A (en) * | 2021-08-23 | 2021-11-16 | 国中绿电(苏州)碳中和研究院有限公司 | Intelligent entrance guard robot and operation method thereof |
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