Monitoring system and monitoring method

Abstract

The embodiment of the invention discloses a monitoring system, and belongs to the field of monitoring. The monitoring system comprises a data acquisition module which is used for acquiring operation data of equipment and personnel data of personnel, and the personnel data comprises physical and psychological data representing physiological conditions and psychological conditions of the personnel; the personnel side writing module is used for dynamically generating physical and mental portraits according to the personnel data; and the monitoring module is used for monitoring the abnormity of the equipment and / or the personnel according to the physical and mental portrait and the operation data to obtain a monitoring result. According to the embodiment of the invention, the root cause of the abnormality of the monitoring system can be determined more accurately, and the monitoring accuracy is improved. In addition, fusion of a digital space and a psychological space is realized through the operation data and the physical and psychological data, and the technical effects of monitoring intelligence and monitoring accuracy of the monitoring system are improved.

Description

Technical Field

[0001] This application relates to the field of monitoring, and more particularly, to a monitoring system and a monitoring method. Background Art

[0002] During the daily work of personnel and the daily use of equipment, unexpected situations are likely to occur, resulting in the failure to smoothly achieve the work objectives. Therefore, the monitoring of personnel and equipment is particularly important. By monitoring, the actual situations of personnel and equipment can be obtained in a timely manner, thus ensuring the smooth completion of work objectives.

[0003] Taking the operation and maintenance system as an example, the current monitoring of the operation and maintenance system only stays at the monitoring of equipment. When a device fails, it is difficult to accurately determine the cause of the failure, and the monitoring effect is poor. Summary of the Invention

[0004] Embodiments of this application provide a monitoring system and a monitoring method to at least solve the technical problem of poor monitoring effect.

[0005] According to the first aspect of the embodiments of this application, a monitoring system is provided. The monitoring system includes:

[0006] A data acquisition module, configured to acquire the operation data of the device and the personnel data of the personnel. Among them, the personnel data includes physical and mental data representing the physical and mental conditions of the personnel;

[0007] A personnel profiling module, configured to dynamically generate a physical and mental portrait according to the personnel data;

[0008] A monitoring module, configured to monitor the anomalies of the device and / or the personnel according to the physical and mental portrait and the operation data, and obtain a monitoring result.

[0009] By adopting this embodiment, the operation data and the personnel data can be collected, and the personnel data includes physical and mental data that can represent the physical and mental conditions of the personnel. Then, the physical and mental portrait formed by the personnel data is combined with the operation data to monitor the device and / or the personnel. Since the physical and mental data of the personnel is involved, when monitoring the device and / or the personnel, the mental condition of the personnel is taken into account, so that the root cause of the anomaly of the monitoring system can be more accurately determined, and the accuracy of the monitoring is improved. In addition, the operation data and the physical and mental data realize the integration of the digital space and the mental space, improving the monitoring intelligence and monitoring accuracy of the monitoring system.

[0010] Combined with the first aspect, in an alternative implementation manner of the embodiments of this application, the monitoring module includes a personnel monitoring unit and / or a device monitoring unit;

[0011] The personnel monitoring unit is used to determine the target personnel to be detected according to the operation data, and generate a first monitoring result for the target personnel based on the physical and mental portraits of the target personnel;

[0012] The equipment monitoring unit is used to determine the target equipment to be detected according to the physical and mental portraits of the personnel, and generate a second monitoring result for the target equipment based on the operation data of the target equipment.

[0013] In this implementation manner, when monitoring personnel, the physical and mental portraits are utilized, so that the first monitoring result involves the psychological conditions of the personnel, which is conducive to improving the accuracy of personnel monitoring. At the same time, when monitoring equipment, the physical and mental portraits are also utilized, which is conducive to analyzing the association between equipment anomalies and personnel, and improving the accuracy of equipment monitoring.

[0014] Combined with the first aspect, in an alternative implementation manner of the embodiments of the present application, the personnel monitoring unit includes a target personnel determination unit, which is used to determine the warning equipment and warning time period based on the operation data, and determine the target personnel according to the warning equipment and warning time period;

[0015] A first monitoring unit, which is used to generate the first monitoring result according to the first comparison result between the physical and mental portraits of the target personnel during the warning time period and the physical and mental portraits of the target personnel before the warning time period.

[0016] In this implementation manner, when a warning appears in the operation data, the warning equipment and warning time period can be determined according to the operation data, and then the target personnel can be further determined, improving the accuracy of the personnel to be monitored. Then, the first monitoring result is generated according to the physical and mental portraits of the target personnel, which is conducive to accurately reflecting whether the reason for the warning is related to the change in the psychological conditions of the personnel, and improving the accuracy and fineness of the monitoring.

[0017] Combined with the first aspect, in an alternative implementation manner of the embodiments of the present application, the physical and mental portraits include at least one of heart rate, activity level, and emotional state;

[0018] The first monitoring unit is used to generate the first monitoring result of personnel anomaly when the first comparison result indicates that the increase amplitude of the heart rate of the target personnel exceeds a preset heart rate threshold and / or the decrease amplitude of the activity level exceeds a preset activity level threshold and / or the emotional state changes to a preset negative emotional state.

[0019] In this implementation manner, generating the first monitoring result from at least one of heart rate, activity level, and emotional state is conducive to accurately reflecting whether the reason for the warning is related to the change in the psychological conditions of the personnel, and improving the accuracy and fineness of the monitoring.

[0020] In combination with the first aspect, in an alternative implementation manner of the embodiment of the present application, the device monitoring unit includes a device determination unit, configured to use the device operated by the person as the target device when an abnormality appears in the physical and mental portrait of the person;

[0021] A second monitoring unit, configured to retrieve the work order information participated by the person from the operation data of the target device, and generate the second monitoring result indicating whether the target device is abnormal according to the second comparison result between the work order information and the corresponding historical work order information.

[0022] By adopting this implementation manner, when it is monitored that an abnormality appears in the physical and mental portrait, the target device is first determined, and then the second monitoring result is generated according to the operation data of the target device, which is beneficial to improving the monitoring accuracy of the device.

[0023] In combination with the first aspect, in an alternative implementation manner of the embodiment of the present application, the physical and mental portrait includes at least one of an emotional state, a stress level, and a fatigue degree;

[0024] The device determination unit is configured to determine that an abnormality appears in the physical and mental portrait of the person when the emotional state of the person belongs to a preset negative emotional state and / or the stress level exceeds a preset stress threshold and / or the fatigue degree exceeds a preset fatigue threshold.

[0025] By adopting this implementation manner, through the monitoring of at least one of the emotional state, the stress level, and the fatigue degree, the monitoring of the abnormality of the physical and mental portrait is realized, and the monitoring accuracy is improved.

[0026] In combination with the first aspect, in an alternative implementation manner of the embodiment of the present application, the person profiling module is further configured to generate an operation habit portrait and a behavior pattern portrait of the person according to the historical operation data of the person;

[0027] The monitoring module is further configured to, when the operation data associated with the person indicates that the operation habit of the person does not match the operation habit portrait and / or the behavior pattern does not match the behavior pattern portrait, perform at least one of the following processes:

[0028] Generate a person monitoring warning for the person;

[0029] Generate a device monitoring warning for the device operated by the person.

[0030] By adopting this implementation manner, in addition to monitoring through the psychological state of the person, the person and / or the device can also be monitored through the operation habit portrait and the behavior pattern portrait, which improves the monitoring intelligence and accuracy of the monitoring system.

[0031] In combination with the first aspect, in an alternative implementation manner of the embodiment of the present application, the person data further includes the location data of the person;

[0032] The monitoring module includes an anomaly monitoring unit, which is used to monitor data anomalies of a person based on the position data of the person and the operation data associated with the person.

[0033] In this implementation manner, the operation data belongs to the digital space, the psychological data belongs to the psychological space, and the position data belongs to the physical space, enabling the monitoring system to monitor devices and / or persons by integrating three-dimensional spaces, thereby improving the monitoring accuracy of the monitoring system.

[0034] Combined with the first aspect, in an alternative implementation manner of the embodiments of the present application, the anomaly monitoring unit is used to generate a monitoring result of data anomalies of a person when the workload characterized by the operation data associated with the person does not match the activity amount characterized by the person's data.

[0035] In this implementation manner, anomalies of the data are also monitored to ensure the accuracy of the person's data, thereby ensuring the accuracy of the monitoring result obtained using the person's data.

[0036] According to the second aspect of the embodiments of the present application, a monitoring method is provided, and the method includes:

[0037] Obtain digital space data, physical space data, and physical and mental space data;

[0038] Use a preset multi-dimensional space model to process the digital space data, physical space data, and physical and mental space data to obtain a monitoring result for monitoring anomalies of devices and / or persons.

[0039] In this implementation manner, a multi-dimensional space model is used to process multi-dimensional data to obtain a monitoring result, such that the monitoring result is affected by the digital space data, physical space data, and physical and mental space data, thereby improving the accuracy of the monitoring result.

[0040] Combined with the second aspect, in an alternative implementation manner of the embodiments of the present application, the digital space data includes operation data of a device; the physical space data includes position data of a person; the physical and mental space data includes physical and mental data representing the physical and mental conditions of a person;

[0041] The step of using a preset multi-dimensional space model to process the digital space data, physical space data, and physical and mental space data to obtain a monitoring result for monitoring anomalies of devices and / or persons includes:

[0042] Use the multi-dimensional space model to identify data anomalies in the operation data and position data to obtain a data identification result regarding whether the physical and mental data of the person is abnormal;

[0043] Using the multi-dimensional space model to perform portrait processing on the physical and mental data to obtain the physical and mental portrait of the person;

[0044] Using the multi-dimensional space model to perform anomaly recognition on the operation data and the physical and mental portrait to obtain an anomaly recognition result regarding whether the device and / or the person is abnormal;

[0045] Wherein, the monitoring result includes the data recognition result and the anomaly recognition result.

[0046] Combined with the first aspect, in an optional implementation manner of the embodiments of the present application, the multi-dimensional space model includes a first processing logic for performing the following processing:

[0047] Determine whether the workload characterized by the operation data associated with the person matches the activity amount characterized by the location data;

[0048] If not, output a data recognition result indicating that the physical and mental data of the person is abnormal.

[0049] Combined with the first aspect, in an optional implementation manner of the embodiments of the present application, the multi-dimensional space model includes a second processing logic for performing the following processing:

[0050] Determine the target person to be detected according to the operation data, and generate a first recognition result for the target person based on the physical and mental portrait of the target person;

[0051] And / or, determine the target device to be detected according to the physical and mental portrait of the person, and generate a second recognition result for the target device based on the operation data of the target device.

[0052] Combined with the first aspect, in an optional implementation manner of the embodiments of the present application, the determining the target person to be detected according to the operation data and generating a first recognition result for the target person based on the physical and mental portrait of the target person includes:

[0053] Determine the warning device and the warning time period based on the operation data, determine the target person according to the warning device and the warning time period, and generate the first recognition result according to the first comparison result between the physical and mental portrait of the target person during the warning time period and the physical and mental portrait before the warning time period.

[0054] Combined with the first aspect, in an optional implementation manner of the embodiments of the present application, the physical and mental portrait includes at least one of heart rate, activity amount, and emotional state;

[0055] The generating the first recognition result according to the first comparison result between the physical and mental portrait of the target person during the warning time period and the physical and mental portrait before the warning time period includes:

[0056] When the first comparison result indicates that the increase in the heart rate of the target person exceeds a preset heart rate threshold and / or the decrease in the activity level exceeds a preset activity level threshold and / or the emotional state changes to a preset negative emotional state, generate the first recognition result of the abnormal person.

[0057] Combined with the first aspect, in an optional implementation manner of the embodiment of the present application, the determining the target device to be detected according to the physical and mental portrait of the person and generating a second recognition result for the target device based on the operation data of the target device includes:

[0058] Obtain retrospective space data, where the retrospective space data includes historical work order information of the target device;

[0059] When the physical and mental portrait of the person is abnormal, use the device operated by the person as the target device, retrieve the work order information participated by the person from the operation data of the target device, and generate the second recognition result indicating whether the target device is abnormal according to the second comparison result between the work order information and the corresponding historical work order information.

[0060] Combined with the first aspect, in an optional implementation manner of the embodiment of the present application, the physical and mental portrait includes at least one of an emotional state, a stress level, and a fatigue degree;

[0061] The method further includes:

[0062] When the emotional state of the person belongs to a preset negative emotional state and / or the stress level exceeds a preset stress threshold and / or the fatigue degree exceeds a preset fatigue threshold, determine that the physical and mental portrait of the person is abnormal.

[0063] Combined with the first aspect, in an optional implementation manner of the embodiment of the present application, the multi-dimensional space model includes a third processing logic for performing the following processing:

[0064] Generate an operation habit portrait and a behavior pattern portrait of the person according to the historical operation data of the person, and when the operation data associated with the person indicates that the operation habit of the person does not match the operation habit portrait and / or the behavior pattern does not match the behavior pattern portrait, generate a personnel monitoring warning for the person and / or a device monitoring warning for the device operated by the person.

[0065] The technical effects produced by the technical solutions in the second aspect are similar to those produced by the first aspect, and will not be elaborated here. Description of the Drawings

[0066] Figure 1It is a structural block diagram of a monitoring system provided by an embodiment of the present application. Detailed implementation manners

[0067] In order to enable those skilled in the art to better understand the solutions of the present application, the technical solutions in the embodiments of the present application will be clearly and completely described below in conjunction with the accompanying drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present application.

[0068] It should be understood that the "multiple" mentioned herein refers to two or more. In the description of the embodiments of the present application, unless otherwise stated, " / " means "or". For example, A / B may mean A or B; the "and / or" herein is only a description of the association relationship of the associated objects, indicating that there can be three relationships. For example, A and / or B may mean: A exists alone, A and B exist simultaneously, and B exists alone. In addition, in order to clearly describe the technical solutions of the embodiments of the present application, in the embodiments of the present application, terms such as "first" and "second" are used to distinguish the same items or similar items with basically the same functions and effects. Those skilled in the art can understand that the terms "first", "second", etc. do not limit the quantity and execution order, and the terms "first", "second", etc. do not necessarily limit to be different

[0069] In addition, the terms "include" and "have" and any of their deformations are intended to cover non-exclusive inclusions. For example, a process, method, system, product or device including a series of steps or units does not necessarily limit to those clearly listed steps or units, but may include other steps or units not clearly listed or inherent to these processes, methods, products or devices.

[0070] The current monitoring systems usually only focus on the technical level of operation and maintenance, while ignoring the impact of the physical and mental states of operation and maintenance personnel on operation and maintenance safety and efficiency, resulting in at least one of the following defects in the existing monitoring systems:

[0071] 1. It is impossible to comprehensively monitor the safety status of operation and maintenance personnel, resulting in frequent safety accidents;

[0072] 2. Lack of real-time performance and accuracy, and it is impossible to understand the progress of fault handling and service quality in real time;

[0073] 3. Lack of monitoring of the physical and mental states of operation and maintenance personnel, and it is impossible to effectively prevent safety accidents caused by human factors;

[0074] 4. Lack of comprehensive analysis and application of operation and maintenance data, and it is impossible to achieve comprehensive optimization of the operation and maintenance process.

[0075] The monitoring system provided in this embodiment relates to the technical field of intelligent operation and maintenance management, and particularly focuses on the high-precision monitoring of the safety and work efficiency of operation and maintenance personnel. By collecting the physiological and psychological state data of operation and maintenance personnel in real time through intelligent wearable devices, and combining the work information in the existing operation and maintenance system, a multi-dimensional space model is constructed to achieve real-time monitoring and precise management of operation and maintenance personnel. The system aims to improve the work efficiency and safety of operation and maintenance personnel through intelligent means, while reducing the safety risks caused by human factors. That is to say, the monitoring system provided in this embodiment constructs a four-dimensional space model including a digital space, a physical space, a psychological space, and a time and space traceback by integrating intelligent wearable devices and data analysis technologies. The system can monitor the safety status, service quality, and decision-making support of operation and maintenance personnel in real time, while optimizing operation and maintenance efficiency and personnel health management. Through the physiological and psychological data collected by intelligent wearable devices, combined with the location tracking in the physical space and the operation and maintenance data in the digital space, this system can warn of potential risks, intervene precisely, and continuously optimize, so as to comprehensively ensure operation and maintenance safety and reduce the occurrence probability of human errors and safety accidents. The innovation of this technical solution lies in its real-time monitoring of the psychological state of operation and maintenance personnel and the comprehensive analysis of operation and maintenance data, realizing the intelligence and personalization of operation and maintenance management.

[0076] Specifically, the embodiment of the present application provides a monitoring system. Referring to Figure 1 the structural block diagram of the monitoring system shown, the detection system includes the following.

[0077] A data acquisition module, configured to acquire the operation data of the device and the personnel data of the personnel, where the personnel data includes physical and mental data representing the physiological and psychological conditions of the personnel;

[0078] A personnel profiling module, configured to dynamically generate a physical and mental portrait according to the personnel data;

[0079] A monitoring module, configured to monitor the anomalies of the device and / or the personnel according to the physical and mental portrait and the operation data, and obtain a monitoring result.

[0080] In one embodiment, the operation data includes operation data when the device is operated by a person, calculation data performed due to the person's operation, and result data brought about by the operation. At the same time, it also includes data such as operation time, calculation time, and result generation time. The person data can include the location data of the person in addition to the physical and mental data. Specifically, the physical and mental data includes physiological data and psychological data. Physiological data such as heart rate, blood pressure, etc., and location data such as the GPS positioning or Beidou positioning of the person. In addition, the location data can also be a movement trajectory with time nodes, and through the movement trajectory, it is possible to know the location of the person at a certain time point. Psychological data such as emotional state, stress level, fatigue degree, etc. Among them, the physiological data can be obtained through the smart bracelet worn by the person, and the psychological data can also be obtained through the smart bracelet worn by the person, or can be calculated based on the physiological data. This embodiment does not limit the specific calculation process. For the sake of understanding, the emotional state can include low mood, stable mood, and high mood; the stress level can be a specific stress value or a preset stress level; the fatigue degree can be a specific fatigue value or a preset fatigue level.

[0081] It should be noted that the physical and mental portrait is a portrait containing person data, and the corresponding person can be found through the physical and mental portrait. Since the person data is updated in real time, the physical and mental portrait is also dynamically updated. In one embodiment, the physical and mental portraits of each person are updated using the newly obtained person data continuously to obtain dynamic physical and mental portraits. In addition, the physical and mental portraits at each time node will be retained to facilitate comparing the physical and mental portraits at different time nodes to obtain the change result of the person's psychological condition.

[0082] Since the physical and mental portrait is generated based on the person data, the psychological condition of the person can be obtained according to the physical and mental portrait. When the psychological condition is poor, the device operated by the person can be found according to the operation data, that is, the work order or task operated by the person in the device can be found, so as to monitor the device, work order or task to obtain the monitoring result.

[0083] In one embodiment, the monitoring result is used to characterize whether there is an abnormality in the device, the person, and the work order / task in the device. Specifically, the monitoring result can include having an abnormality and no abnormality.

[0084] By adopting this embodiment, operation data and personnel data can be collected, and the personnel data includes physical and mental data that can characterize the physical and mental conditions of personnel. Then, the physical and mental portrait formed by the personnel data is combined with the operation data to monitor the equipment and / or personnel. Since it involves the physical and mental data of personnel, when monitoring the equipment and / or personnel, the mental condition of personnel is taken into account, so that the root cause of the abnormality of the monitoring system can be determined more accurately, and the accuracy of monitoring is improved. In addition, the operation data and the physical and mental data realize the integration of the digital space and the mental space, improving the monitoring intelligence and monitoring accuracy of the monitoring system.

[0085] Optionally, in an implementation manner of this embodiment, the monitoring module includes a personnel monitoring unit and / or an equipment monitoring unit;

[0086] The personnel monitoring unit is used to determine the target personnel to be detected according to the operation data, and generate a first monitoring result for the target personnel based on the physical and mental portrait of the target personnel;

[0087] The equipment monitoring unit is used to determine the target equipment to be detected according to the physical and mental portrait of the personnel, and generate a second monitoring result for the target equipment based on the operation data of the target equipment.

[0088] In one embodiment, when the monitoring system issues a warning, the target personnel to be detected is determined according to the operation data, and a first monitoring result for the target personnel is generated based on the physical and mental portrait of the target personnel. The warning of the monitoring system comes from the abnormality of the equipment, the abnormality of the work order or task in the equipment, and the abnormality of the personnel. For example, when the equipment alarms, it is regarded as the monitoring system issuing a warning. It should be noted here that the monitoring system can be a system containing a real operating system, that is to say, the system where the personnel work is part of the monitoring system. When the system where the personnel work issues a warning, it is regarded as the monitoring system issuing a warning. In another embodiment, the system where the personnel work and the monitoring system are two independent systems, and the monitoring system is used to monitor the system where the personnel work. When the system where the personnel work issues a warning, the monitoring system will receive this warning, and at this time, it is understood that the monitoring system issues a warning. The system where the personnel work is, for example, a banking system, a production system of a certain product, etc.

[0089] In one embodiment, after a warning occurs, the relevant personnel can be found according to the operation data, and this personnel can be determined as the target personnel.

[0090] By adopting this implementation manner, when monitoring personnel, the physical and mental portrait is utilized, so that the first monitoring result involves the mental condition of the personnel, which is easy to improve the accuracy of personnel monitoring. At the same time, when monitoring the equipment, the physical and mental portrait is also utilized, which is easy to analyze the correlation between the equipment abnormality and the personnel, and improves the accuracy of equipment monitoring.

[0091] Optionally, in an implementation of this embodiment, the personnel monitoring unit includes a target personnel determination unit, which is configured to determine an early warning device and an early warning time period based on operation data, and determine target personnel according to the early warning device and the early warning time period;

[0092] A first monitoring unit, which is configured to generate a first monitoring result according to a first comparison result between the physical and mental portrait of the target personnel during the early warning time period and the physical and mental portrait before the early warning time period.

[0093] For ease of understanding, in one embodiment, the physical and mental portrait includes the physiological data and psychological data of the target personnel. By comparing the physical and mental portraits at different time nodes, it is possible to determine the changes in the physiological condition and / or psychological condition of the target personnel, thereby obtaining the first comparison result. Taking the psychological condition as an example, the stress level A of the target personnel can be determined from the physical and mental portrait during the early warning time period, and the stress level B of the same target personnel can be obtained from the physical and mental portrait before the early warning time period. Then, the first comparison result is generated according to the fluctuation of the stress level A and the stress level B. Preferably, the first comparison result is the degree of stress fluctuation.

[0094] In another embodiment, according to the early warning event occurred by the early warning device, search for the physical and mental portrait i when the target personnel successfully solved or completed the same type of early warning event before the early warning time period, and compare the physical and mental portrait k during the early warning time period with the physical and mental portrait i to obtain the first comparison result. Among them, the comparison can be to compare the volatility or the degree of volatility of the physical and mental portraits k and i.

[0095] In other embodiments, the methods for generating the first comparison result in the above two embodiments can be combined to obtain two first comparison results A and B. If any one of the first comparison results A and B does not meet the requirements, an abnormal first monitoring result is generated according to the first comparison result. Or, according to the severity of the early warning event in the early warning device, when the early warning event is severe, if one of the two first comparison results does not meet the requirements, an abnormal first monitoring result is generated. When the early warning event is not severe, if both of the two first comparison results do not meet the requirements, an abnormal first monitoring result is generated. Among them, the judgment conditions for whether the early warning event is severe can be set according to actual needs, and this embodiment does not make specific limitations on this.

[0096] Adopting this implementation method, when an early warning appears in the operation data, the early warning device and the early warning time period can be determined according to the operation data, and then the target personnel can be further determined, improving the accuracy of the personnel to be monitored. Then, the first monitoring result is generated according to the physical and mental portrait of the target personnel, which is conducive to accurately reflecting whether the reason for the early warning is related to the change in the psychological condition of the personnel, improving the accuracy and fineness of the monitoring.

[0097] Optionally, in an implementation of this embodiment, the physical and mental portrait includes at least one of heart rate, activity level, and emotional state;

[0098] The first monitoring unit is configured to generate a first monitoring result indicating an abnormality of a person when the first comparison result indicates that the increase in the heart rate of the target person exceeds a preset heart rate threshold and / or the decrease in the activity level exceeds a preset activity level threshold and / or the emotional state changes to a preset negative emotional state.

[0099] In one embodiment, the physical and mental portrait includes multiple dimensions, such as a physiological dimension, a psychological dimension, and a location dimension, where the location dimension refers to the location of the person in real life. The first monitoring unit can integrate the data corresponding to the multiple dimensions to obtain a comprehensive result, and generate the first monitoring result based on the comprehensive result. For example, calculate the deviation value of the data corresponding to each dimension from the preset standard data, and then integrate the deviation values of all dimensions to obtain a comprehensive result. If the comprehensive result is greater than the preset deviation threshold, the first monitoring result is abnormal.

[0100] It should be noted that, in addition to using at least one of the heart rate, activity level, and emotional state to generate the first monitoring result, at least one of the emotional state, stress level, and fatigue degree can also be used to generate the first monitoring result.

[0101] Adopting this implementation method to generate the first monitoring result from at least one of the heart rate, activity level, and emotional state is conducive to accurately reflecting whether the reason for the early warning is related to the change in the psychological condition of the person, and improves the accuracy and fineness of the monitoring.

[0102] Optionally, in one implementation manner of this embodiment, the device monitoring unit includes a device determination unit, which is configured to use the device operated by the person as the target device when the physical and mental portrait of the person is abnormal;

[0103] A second monitoring unit, which is configured to retrieve the work order information participated by the person from the operation data of the target device, and generate a second monitoring result indicating whether the target device is abnormal according to the second comparison result between the work order information and the corresponding historical work order information.

[0104] In one embodiment, the second comparison result can be the comparison result of the similarity between the work order information and the historical work order information, or the comparison result of the completion degree and the work order score. Since there are differences in different types of work orders, the specific comparison process of the work order information and the historical work order information can be configured according to the actual situation, so as to generate the corresponding second comparison result, and this embodiment does not make specific limitations on this. For the sake of understanding, for example, compare whether the mandatory items in the work order information are filled in correctly. If the mandatory items in the work order information are different from the corresponding historical work order information, a mismatched second comparison result can be generated, thereby generating a second monitoring result indicating that the device is abnormal.

[0105] With this implementation method, when an abnormality in the physical and mental portrait is detected, the target device is first determined, and then a second monitoring result is generated based on the operation data of the target device, which helps to improve the monitoring accuracy of the device.

[0106] Optionally, in an implementation of this embodiment, the physical and mental portrait includes at least one of an emotional state, a stress level, and a fatigue degree;

[0107] The device determination unit is used to determine that the physical and mental portrait of a person is abnormal when the emotional state of the person belongs to a preset negative emotional state and / or the stress level exceeds a preset stress threshold and / or the fatigue degree exceeds a preset fatigue threshold.

[0108] In one embodiment, the physical and mental portrait includes multiple dimensions, such as a physiological dimension, a psychological dimension, and a location dimension. Among them, the location dimension refers to the location of a person in real life. The device determination unit can integrate the data corresponding to multiple dimensions to obtain a comprehensive result, and determine whether the physical and mental portrait of the person is abnormal depending on the comprehensive result. For example, calculate the deviation value of the data corresponding to each dimension (such as the emotional state, stress level, and fatigue degree in the psychological dimension) from the preset standard data, and then integrate the deviation values of all dimensions to obtain a comprehensive result. If the comprehensive result is greater than the preset deviation threshold, the physical and mental portrait is abnormal.

[0109] It should be noted that in addition to using at least one of the emotional state, stress level, and fatigue degree to determine whether the physical and mental portrait of a person is abnormal, at least one of the heart rate, activity level, and emotional state can also be used to determine whether the physical and mental portrait of a person is abnormal.

[0110] With this implementation method, by monitoring at least one of the emotional state, stress level, and fatigue degree, the monitoring of the abnormality of the physical and mental portrait is realized, and the monitoring accuracy is improved.

[0111] Optionally, in an implementation of this embodiment, the person profiling module is further used to generate a person's operation habit portrait and behavior pattern portrait according to the person's historical operation data;

[0112] The monitoring module is further used to perform at least one of the following processes when the operation data associated with the person indicates that the person's operation habit does not match the operation habit portrait and / or the behavior pattern does not match the behavior pattern portrait:

[0113] Generate a person monitoring warning for this person;

[0114] Generate a device monitoring warning for the device operated by this person.

[0115] By adopting this implementation method, in addition to monitoring through the psychological state of personnel, it is also possible to monitor personnel and / or equipment through the operation habit portrait and behavior pattern portrait, improving the monitoring intelligence and accuracy of the monitoring system.

[0116] Optionally, in an implementation manner of this embodiment, the monitoring module includes a psychological fluctuation monitoring unit, which is used to generate a monitoring result of personnel psychological fluctuation according to the changes in the physical and mental data of personnel when major operation and maintenance events occur in the monitoring system.

[0117] The major operation and maintenance events include at least one of the following situations:

[0118] The event with a warning belongs to a preset target key device.

[0119] The event with a warning belongs to a preset target key service.

[0120] The number of users involved in the event with a warning exceeds a preset user quantity threshold.

[0121] The event with a warning belongs to a preset target emergency event.

[0122] It is possible to monitor the psychological fluctuations of personnel by using major operation and maintenance events, and thus understand the stress resistance of each personnel according to the monitoring results of personnel psychological fluctuations.

[0123] Optionally, in an implementation manner of this embodiment, the personnel data includes the location data of personnel.

[0124] The monitoring module includes an anomaly monitoring unit, which is used to monitor the data anomalies of personnel according to the personnel data of personnel and the operation data associated with the personnel.

[0125] In one embodiment, the detection module is used to monitor personnel according to the data in four dimensions: location data, operation data, and personnel data. Specifically, for example, the action trajectory of personnel is formed through the location data. If the action trajectory does not match the trajectory of manual work, the behavior of the personnel is observed through the monitoring device. If the behavior of the personnel belongs to a preset illegal behavior, a monitoring result of abnormal personnel behavior is generated. For example, according to the action trajectory, it is monitored that a person enters the computer room, but the computer room does not belong to the work location of this person. At this time, the monitoring in the computer room is retrieved, and it is seen that the person is smoking or making a phone call, then a monitoring result of abnormal behavior of this person is generated.

[0126] Specifically, for the convenience of understanding the application of location data in monitoring, in a specific application scenario, taking the monitoring of operation and maintenance personnel as an example, the monitoring target of the physical space (detection of abnormal behavior in the computer room) of operation and maintenance personnel:

[0127] 1) Record the action trajectory of operation and maintenance personnel at the customer site.

[0128] 2) Identification of abnormal behaviors of operation and maintenance personnel in the computer room area.

[0129] I. Implementation methods for the behavior trajectories of operation and maintenance personnel

[0130] 1. When operation and maintenance personnel enter the customer site, images are collected through the access control face integrated machine.

[0131] 2. Through video analysis of the cameras in the park, the face images in the video are compared with the faces of external personnel, and the action trajectories of external personnel are identified through time series.

[0132] 3. When non-core operation and maintenance personnel enter the internal sensitive area, an alarm is issued.

[0133] II. Line-of-sight methods for identifying abnormal behaviors in the computer room area

[0134] 1. Connect to the unified operation and maintenance system to pull the images of operation and maintenance personnel.

[0135] 2. Through the SenseTime video analysis AIE box (hardware), video image feature analysis is carried out to detect abnormal behaviors and issue alarms.

[0136] 3. If there are new requirements for identifying abnormal behaviors, it is necessary to select feature maps for marking and training.

[0137] 4. The project focuses on the abnormal behavior characteristics of the computer room, including tailing into the computer room, carrying suitcases into the computer room, smoking, and making phone calls.

[0138] The images and videos output by the access control face integrated machine and the cameras mentioned above all belong to operation data.

[0139] Adopting this implementation method, the operation data belongs to the digital space, the psychological data belongs to the psychological space, and the location data belongs to the physical space, enabling the monitoring system to monitor equipment and / or personnel by integrating the three aspects of space, thereby improving the monitoring accuracy of the monitoring system.

[0140] Optionally, in an implementation manner of this embodiment, the abnormal monitoring unit is used to generate a monitoring result of abnormal personnel data when the workload characterized by the operation data associated with the personnel does not match the activity amount characterized by the personnel data.

[0141] Adopting this implementation method, the abnormality of the data will also be monitored to ensure the accuracy of the personnel data, thereby ensuring the accuracy of the monitoring results obtained from the personnel data.

[0142] This application embodiment also provides a monitoring method, and the method includes:

[0143] Obtain digital space data, physical space data, and physical and mental space data;

[0144] Process the digital space data, physical space data, and physical and mental space data using a preset multi-dimensional space model to obtain a monitoring result for monitoring anomalies of the device and / or personnel.

[0145] With this implementation method, a multi-dimensional space model is used to process multi-dimensional data to obtain a monitoring result, making the monitoring result affected by the digital space data, physical space data, and physical and mental space data, and improving the accuracy of the monitoring result.

[0146] Optionally, in an implementation of this embodiment, the digital space data includes the operation data of the device; the physical space data includes the location data of the personnel; the physical and mental space data includes the physical and mental data representing the physiological and psychological conditions of the personnel;

[0147] The process of using a preset multi-dimensional space model to process the digital space data, physical space data, and physical and mental space data to obtain a monitoring result for monitoring anomalies of the device and / or personnel includes:

[0148] Use the multi-dimensional space model to identify data anomalies in the operation data and location data to obtain a data identification result on whether the physical and mental data of the personnel is abnormal;

[0149] Use the multi-dimensional space model to perform portrait processing on the physical and mental data to obtain the physical and mental portrait of the personnel;

[0150] Use the multi-dimensional space model to identify anomalies in the operation data and physical and mental portrait to obtain an anomaly identification result on whether the device and / or personnel is abnormal;

[0151] Among them, the monitoring result includes the data identification result and the anomaly identification result.

[0152] In one embodiment, the operation data includes operation data when the device is operated by a person, calculation data performed due to the person's operation, and result data brought about by the operation. At the same time, it also includes data such as operation time, calculation time, and result generation time. The person data can include the position data of the person in addition to the physical and mental data. Specifically, the physical and mental data includes physiological data and psychological data. Physiological data such as heart rate, blood pressure, etc., and position data such as the GPS positioning or Beidou positioning of the person. In addition, the position data can also be a movement trajectory with time nodes, and through the movement trajectory, it is possible to know the position of the person at a certain time point. Psychological data such as emotional state, stress level, fatigue degree, etc. Among them, the physiological data can be obtained through the smart bracelet worn by the person, and the psychological data can also be obtained through the smart bracelet worn by the person, or can be calculated based on the physiological data. The specific calculation process is not limited in this embodiment. For the sake of understanding, the emotional state can include low mood, stable mood, and high mood; the stress level can be a specific stress value or a preset stress level; the fatigue degree can be a specific fatigue value or a preset fatigue level.

[0153] It should be noted that the physical and mental portrait is a portrait containing person data, and the corresponding person can be found through the physical and mental portrait. Since the person data is updated in real time, the physical and mental portrait is also dynamically updated. In one embodiment, the physical and mental portraits of each person are updated using the continuously newly obtained person data to obtain dynamic physical and mental portraits. In addition, the physical and mental portraits at each time node will be retained to facilitate comparing the physical and mental portraits at different time nodes to obtain the change result of the person's psychological condition.

[0154] Since the physical and mental portrait is generated based on the person data, the psychological condition of the person can be obtained according to the physical and mental portrait. When the psychological condition is poor, the device operated by the person can be found according to the operation data, or the work order or task operated by the person in the device can be found, so as to monitor the device, work order or task to obtain the monitoring result.

[0155] In one embodiment, the monitoring result is used to characterize whether there is an abnormality in the device, the person, and the work order / task in the device. Specifically, the monitoring result can include having an abnormality and no abnormality.

[0156] Optionally, in one implementation manner of this embodiment, the multi-dimensional space model includes a first processing logic for performing the following processing:

[0157] Judge whether the workload represented by the operation data associated with the person matches the activity amount represented by the position data;

[0158] If not, output a data recognition result indicating that the physical and mental data of the person is abnormal.

[0159] In one embodiment, the first processing logic, the second processing logic, the third processing logic, or a combination of the processing logics may be preset manually or obtained based on a neural network model.

[0160] Optionally, in an implementation manner of this embodiment, the multi-dimensional space model includes a second processing logic for performing the following processing:

[0161] Determine a target person to be detected according to the operation data, and generate a first recognition result for the target person based on the physical and mental portrait of the target person;

[0162] And / or, determine a target device to be detected according to the physical and mental portrait of a person, and generate a second recognition result for the target device based on the operation data of the target device.

[0163] Optionally, in an implementation manner of this embodiment, the determining a target person to be detected according to the operation data and generating a first recognition result for the target person based on the physical and mental portrait of the target person includes:

[0164] Determine a warning device and a warning time period based on the operation data, determine the target person according to the warning device and the warning time period, and generate the first recognition result according to a first comparison result between the physical and mental portrait of the target person during the warning time period and the physical and mental portrait before the warning time period.

[0165] Optionally, in an implementation manner of this embodiment, the physical and mental portrait includes at least one of heart rate, activity level, and emotional state;

[0166] The generating the first recognition result according to a first comparison result between the physical and mental portrait of the target person during the warning time period and the physical and mental portrait before the warning time period includes:

[0167] When the first comparison result indicates that the increase amplitude of the heart rate of the target person exceeds a preset heart rate threshold and / or the decrease amplitude of the activity level exceeds a preset activity level threshold and / or the emotional state changes to a preset negative emotional state, generate the first recognition result of the person being abnormal.

[0168] Optionally, in an implementation manner of this embodiment, the determining a target device to be detected according to the physical and mental portrait of a person and generating a second recognition result for the target device based on the operation data of the target device includes:

[0169] Obtain retrospective space data, where the retrospective space data includes historical work order information of the target device;

[0170] When the physical and mental portrait of a person appears abnormal, the device operated by the person is taken as the target device, the work order information participated by the person is retrieved from the operation data of the target device, and the second recognition result indicating whether the target device is abnormal is generated according to the second comparison result between the work order information and the corresponding historical work order information.

[0171] Optionally, in an implementation manner of this embodiment, the physical and mental portrait includes at least one of an emotional state, a stress level, and a fatigue degree;

[0172] The method further includes:

[0173] When the emotional state of the person belongs to a preset negative emotional state and / or the stress level exceeds a preset stress threshold and / or the fatigue degree exceeds a preset fatigue threshold, it is determined that the physical and mental portrait of the person appears abnormal.

[0174] Optionally, in an implementation manner of this embodiment, the multi-dimensional space model includes a third processing logic for performing the following processing:

[0175] Generate an operation habit portrait and a behavior pattern portrait of a person according to the historical operation data of the person, and when the operation data associated with the person indicates that the operation habit of the person does not match the operation habit portrait and / or the behavior pattern does not match the behavior pattern portrait, generate a personnel monitoring warning for the person and / or a device monitoring warning for the device operated by the person.

[0176] In a specific implementation of the embodiment of the present application, it includes the following three parts.

[0177] (1) Construct a data multi-dimensional space model

[0178] The present invention integrates the following data dimensions through intelligent wearable devices to construct a comprehensive multi-dimensional space model:

[0179] 1. Comprehensive data baseline: By wearing a data collection bracelet for a long time, a personalized baseline is established, including a physiological baseline and a psychological baseline. The physiological baseline involves physiological indicators such as heart rate, blood pressure, and activity level; the psychological baseline involves psychological indicators such as emotional state and stress level, and various indicators are collected by the bracelet.

[0180] 2. Multidimensional Personnel Profiling: It is a comprehensive analysis model designed to comprehensively evaluate the physical and mental states, operation behavior patterns, and changes in psychophysiological states of operation and maintenance personnel through multi-dimensional analysis of their physiological and psychological data. The model is divided into two parts: Comprehensive Evaluation of Personnel's Physical and Mental Health, which comprehensively evaluates the physical and mental health status of operation and maintenance personnel by analyzing their physiological indicators (such as heart rate, blood pressure, sleep quality, etc.) and psychological indicators (such as emotional state, stress level, fatigue degree, etc.); Operation Mode Recognition: By analyzing the historical operation data of operation and maintenance personnel (such as operation time, operation frequency, operation type, etc.), it identifies the operation habits and behavior patterns of operation and maintenance personnel. The multidimensional personnel profiling model can comprehensively and dynamically evaluate the physical and mental states and work performance of operation and maintenance personnel, providing comprehensive data support for system risk warning, decision-making support, and health management.

[0181] 3. Special Tagging: Special tags are assigned to personnel characteristics, work areas, time periods, alarm status, etc., so as to quickly locate and identify key factors during data analysis.

[0182] 4. Psychological Fluctuation Comparison: During the operation and maintenance process, major operation and maintenance events refer to those events that may have a significant impact on system operation, data security, or business continuity, such as critical system failures, data leaks, major configuration changes, etc. These events usually require emergency response and may cause great pressure on the psychological state of operation and maintenance personnel. To evaluate the impact of major operation and maintenance events on the psychological state of operation and maintenance personnel, the present invention analyzes by comparing the changes in the psychological indicators (such as emotional state, stress level, fatigue degree, etc.) of operation and maintenance personnel before and after the event. The specific judgment criteria include:

[0183] Event Impact Scope: Whether the event affects critical business systems or a large number of users;

[0184] Event Urgency: Whether the event needs to be responded to and processed within a short time;

[0185] Psychological Indicator Changes: Whether there are significant fluctuations in the psychological indicators of operation and maintenance personnel before and after the event;

[0186] Historical Event Comparison: The similarity between the current event and historical major operation and maintenance events.

[0187] 5. Fraud Detection: To ensure the authenticity and reliability of the data collected by smart wearable devices, the present invention designs a fraud detection mechanism. This mechanism monitors the wearing behavior of smart wearable devices, identifies abnormal wearing behaviors, and sets up real-time alarm and intervention mechanisms to prevent data falsification or device abuse. For example, if the system detects that the smart wearable device has been stationary for a period of time, but the work record of the operation and maintenance personnel shows that they are performing high-intensity operation and maintenance operations, or the device is worn during non-working hours and the location changes frequently, these situations may be regarded as abnormal wearing behaviors. The specific detection methods include:

[0188] Activity Data Monitoring: Compare the activity amount recorded by the device (such as steps, movement trajectory) with the work task record of the operation and maintenance personnel. If the task record shows high-intensity operation but the activity amount is extremely low, it may indicate that the device is not worn correctly;

[0189] Location Data Monitoring: Monitor the location change of the device through the GPS or location sensor of the smart wearable device. If the device moves frequently during non-working hours or in non-working areas, it may indicate that the device is being abused;

[0190] Physiological Data Monitoring: Analyze the rationality of physiological data such as heart rate and blood pressure. If the physiological data remains abnormal (such as too low or too high heart rate) during normal working hours, it may indicate that the device is not worn correctly or the data has been tampered with.

[0191] (2) Data Collection and Application Scenarios

[0192] Data Collection of the Present Invention:

[0193] 1. Operation and Maintenance Data Collection: Collect the operation logs of hardware devices and application software through a unified operation and maintenance system to monitor system performance and identify potential technical problems.

[0194] 2. Emotional Data Collection: Collect physiological data through smart wearable devices (such as smart bracelets) and convert it into psychological data through algorithms to monitor the emotional state of operation and maintenance personnel.

[0195] 3. Physical Data Collection: Collect spatial data of personnel activities through surveillance cameras, including location tracking, area management, and trajectory analysis.

[0196] (3) Application Scenarios

[0197] 1. Correlate Device / Application Abnormalities Based on Abnormalities in Personnel Psychology:

[0198] Emotion Detection: Detect psychological abnormalities such as low mood, high stress, and fatigue of operation and maintenance personnel through smart wearable devices.

[0199] Involvement in Work: Check the work orders recently participated in by the operation and maintenance personnel to evaluate their work load and efficiency.

[0200] Application anomaly recognition: By comparing historical work orders, it is found that there are still alarms in the applications processed in the last few work orders handled by this member.

[0201] Equipment troubleshooting: According to the application system, it is traced that the equipment logged in by the operation and maintenance personnel also has alarms.

[0202] Risk assessment: By setting a comprehensive data baseline through the close correlation between personnel emotions and work quality, potential equipment problems are discovered and solved.

[0203] 2. Screening the risk of psychological abnormal personnel errors from equipment alarms or emergency events:

[0204] System warning: According to the warning, the operation and maintenance team checks the logs and finds that the abnormal traffic originates from a specific server group.

[0205] Narrowing down the scope: Further analysis shows that the abnormality occurred during the night maintenance period.

[0206] Personnel troubleshooting: Check the work orders during the night maintenance period, determine the on-duty personnel through the work orders, and retrieve the data of intelligent wearable devices through the workbench.

[0207] Abnormality discovery: It is found that the heart rate of the operation and maintenance engineer increased abnormally before the operation, and the activity level suddenly decreased. Checking the emotion index, it is found that the employee is in a depressive alarm state.

[0208] Cause analysis: After interviewing the engineer, it is found that the engineer was in a poor mental state due to night shift duty and made mistakes during the configuration update.

[0209] Through the above technical implementation path, the present invention can realize real-time monitoring and analysis of multi-dimensional data in the operation and maintenance process, thereby improving the security, efficiency and personnel health level of operation and maintenance.

[0210] The detection system provided in this embodiment at least includes the following one feature:

[0211] 1. Construction of a multi-dimensional space model, including the integration of digital space, physical space and psychological space;

[0212] 2. Application of intelligent wearable devices in the operation and maintenance process to realize real-time monitoring of the physiological and psychological states of operation and maintenance personnel;

[0213] 3. Innovation of data collection and application scenarios, including operation and maintenance data collection, emotion data collection and physical data collection.

[0214] The detection system provided in this embodiment at least includes the following one effect:

[0215] 1. The comprehensive upgrade of operation and maintenance security management is realized, and the real-time performance and accuracy of security monitoring are improved through the multi-dimensional space model;

[0216] 2. The operation and maintenance efficiency is improved. Through intelligent wearable devices and data analysis technologies, the human resource allocation and work processes are optimized;

[0217] 3. The attention to the health management of operation and maintenance personnel is strengthened. By real-time monitoring of physiological and psychological states, the work safety and satisfaction of operation and maintenance personnel are improved;

[0218] 4. The comprehensive analysis and application of operation and maintenance data are realized. Through the space-time backtracking technology, the all-dimensional insight ability into operation and maintenance anomalies is improved.

[0219] Through the above technical solutions, the present invention not only improves the operation and maintenance security management level, but also optimizes the operation and maintenance efficiency, and ensures the health of operation and maintenance personnel, having significant technical advantages and application values.

[0220] The above has given an illustrative example of the method embodiments according to the present application.

[0221] The serial numbers of the embodiments of the present application or the order of introduction are only for description, and do not represent the advantages or disadvantages of the embodiments.

[0222] In several embodiments provided by the present application, it should be understood that the disclosed technical content can be implemented in other ways. Among them, the device embodiments described above are only illustrative. For example, the division of the units can be a logical function division. In actual implementation, there can be other division methods. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point, the displayed or discussed couplings or direct couplings or communication connections to each other can be through some interfaces. The indirect couplings or communication connections of the units or modules can be in electrical or other forms.

[0223] In addition, in each embodiment of the present application, the functional units can be integrated in a processing unit, or each unit can exist physically alone, or two or more units can be integrated in one unit. The above integrated units can be implemented in the form of hardware or in the form of software functional units.

[0224] In the above embodiments, it can be implemented in whole or in part by software, hardware, firmware, or any combination thereof. When implemented using software, it can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions. When the computer instructions are loaded and executed on a computer, the processes or functions described in the embodiments of the present application are generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable devices. The computer instructions can be stored in a computer-readable storage medium, or transmitted from one computer-readable storage medium to another. For example, the computer instructions can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center via wired (such as coaxial cable, fiber optic, digital subscriber line (DSL)) or wireless (such as infrared, wireless, microwave, etc.) means. The computer-readable storage medium can be any available medium that can be accessed by a computer, or a data storage device such as a server or data center that includes one or more available media integrated. The available medium can be a magnetic medium (such as a floppy disk, hard disk, magnetic tape), an optical medium (such as a digital versatile disc (DVD)), or a semiconductor medium (such as a solid state disk (SSD)), etc. It should be noted that the computer-readable storage medium mentioned in the embodiments of the present application can be a non-volatile storage medium, in other words, a non-transitory storage medium.

[0225] It should be noted that the information (including but not limited to user equipment information, user personal information, etc.), data (including but not limited to data for analysis, stored data, displayed data, etc.), and signals involved in the embodiments of the present application are all authorized by the user or fully authorized by all parties, and the collection, use, and processing of relevant data need to comply with the relevant laws, regulations, and standards of relevant countries and regions. For example, the scene data of the current frame in the three-dimensional virtual scene, the device information of the client, and the scene interaction information involved in the embodiments of the present application are all obtained under full authorization.

[0226] The above are only the preferred embodiments of the present application. It should be noted that for those of ordinary skill in the art, without departing from the principle of the present application, several improvements and refinements can be made, and these improvements and refinements should also be regarded as the protection scope of the present application.

Claims

1. A monitoring system, characterized in that: The monitoring system comprises: A data acquisition module, used to acquire operation data of the equipment and personnel data of personnel, wherein the personnel data includes physical and mental data representing the physiological and psychological conditions of the personnel; A personnel profiling module, for dynamically generating a physical and mental portrait based on the personnel data; The monitoring module is used to monitor abnormalities of equipment and / or personnel based on the physical and mental portraits and the operating data to obtain monitoring results.

2. The monitoring system according to claim 1, characterized in that: The monitoring module includes a personnel monitoring unit and / or an equipment monitoring unit; The personnel monitoring unit is used to determine a target person to be detected according to the operation data, and generate a first monitoring result for the target person based on the physical and mental portrait of the target person; The device monitoring unit is used to determine the target device that needs to be detected according to the physical and mental portrait of the person, and generate a second monitoring result for the target device based on the operating data of the target device.

3. The monitoring system according to claim 2, characterized in that: The personnel monitoring unit includes a target personnel determination unit, which is used to determine the early warning device and the early warning period based on the operation data, and determine the target personnel according to the early warning device and the early warning period; The first monitoring unit is used to generate the first monitoring result according to a first comparison result of the physical and mental portrait of the target person in the warning period and the physical and mental portrait before the warning period.

4. The monitoring system according to claim 3, characterized in that: The physical and mental portrait includes at least one of heart rate, activity level and emotional state; The first monitoring unit is used to generate the first monitoring result of personnel abnormality when the first comparison result indicates that the target person's heart rate increase exceeds a preset heart rate threshold and / or the activity decrease exceeds a preset activity threshold and / or the emotional state changes to a preset negative emotional state.

5. The monitoring system according to claim 2, characterized in that: The device monitoring unit includes a device determining unit for determining the device operated by the person as the target device when the person's physical and mental portrait is abnormal; The second monitoring unit is used to retrieve the work order information in which the person participated from the operation data of the target device, and generate the second monitoring result indicating whether the target device is abnormal according to a second comparison result between the work order information and corresponding historical work order information.

6. The monitoring system according to claim 5, characterized in that: The mind-body portrait includes at least one of an emotional state, a stress level, and a fatigue level; The device determination unit is used to determine that the physical and mental portrait of the person is abnormal when the emotional state of the person belongs to a preset negative emotional state and / or the stress level exceeds a preset stress threshold and / or the fatigue level exceeds a preset fatigue threshold.

7. The monitoring system according to claim 1, characterized in that: The personnel profiling module is also used to generate a personnel operation habit portrait and a behavior pattern portrait based on the personnel's historical operation data; The monitoring module is further configured to perform at least one of the following processes when the operation data associated with the personnel indicates that the operating habits of the personnel do not match the operating habit portrait and / or the behavior pattern does not match the behavior pattern portrait: Generate personnel monitoring warning for the personnel; Generate equipment monitoring warnings for the equipment operated by the person.

8. The monitoring system according to claim 1, characterized in that: The personnel data also includes the personnel's location data; The monitoring module includes an abnormality monitoring unit, which is used to monitor data abnormalities of personnel based on location data of the personnel and the operation data associated with the personnel.

9. The monitoring system according to claim 8, characterized in that: The abnormality monitoring unit is used to generate a monitoring result of personnel data abnormality when the workload represented by the operation data associated with the personnel does not match the activity represented by the personnel data.

10. A monitoring method, characterized in that: The method comprises: Obtain data on digital space, physical space, and physical and mental space; The digital space data, physical space data and physical and mental space data are processed using a preset multi-dimensional space model to obtain monitoring results for abnormalities of equipment and / or personnel.

11. The monitoring method according to claim 10, characterized in that: The digital space data includes the operation data of the equipment; the physical space data includes the location data of the personnel; the physical and mental space data includes the physical and mental data representing the physiological and psychological conditions of the personnel; The digital space data, physical space data and physical and mental space data are processed by using a preset multi-dimensional space model to obtain monitoring results for abnormalities of equipment and / or personnel, including: Using the multidimensional space model to identify data anomalies in the operation data and location data, and obtaining a data identification result of whether the physical and mental data of the person are abnormal; Using the multidimensional space model to process the physical and mental data, and obtain a physical and mental portrait of the person; Using the multidimensional space model to identify abnormalities in the operating data and the physical and mental portraits, and obtaining abnormality identification results on whether the equipment and / or personnel are abnormal; The monitoring results include the data identification results and the abnormality identification results.

12. The monitoring method according to claim 11, characterized in that: The multidimensional space model includes a first processing logic for performing the following processing: Determining whether the workload represented by the operation data associated with the person matches the activity represented by the location data; If there is no match, the data recognition result representing the abnormality of the person's physical and mental data is output.

13. The monitoring method according to claim 11, characterized in that: The multidimensional space model includes a second processing logic for performing the following processing: Determining a target person to be detected according to the operation data, and generating a first recognition result for the target person based on the physical and mental portrait of the target person; And / or, determining a target device that needs to be detected according to the physical and mental portrait of the person, and generating a second recognition result for the target device based on the operating data of the target device.

14. The monitoring method according to claim 13, characterized in that: The step of determining a target person to be detected according to the operation data, and generating a first recognition result for the target person based on the physical and mental portrait of the target person, includes: The warning device and the warning period are determined based on the operating data, the target person is determined according to the warning device and the warning period, and the first recognition result is generated according to a first comparison result between the physical and mental portrait of the target person during the warning period and the physical and mental portrait before the warning period.

15. The monitoring method according to claim 14, characterized in that: The physical and mental portrait includes at least one of heart rate, activity level and emotional state; The generating the first recognition result according to a first comparison result of the physical and mental portrait of the target person in the warning period and the physical and mental portrait before the warning period includes: When the first comparison result indicates that the target person's heart rate increase exceeds a preset heart rate threshold and / or the activity decrease exceeds a preset activity threshold and / or the emotional state changes to a preset negative emotional state, the first identification result of person abnormality is generated.

16. The monitoring method according to claim 13, characterized in that: The step of determining the target device to be detected according to the physical and mental portrait of the person, and generating a second recognition result for the target device based on the operation data of the target device includes: Acquire retrospective space data, wherein the retrospective space data includes historical work order information of the target device; When an abnormality appears in the physical and mental portrait of a person, the device operated by the person is taken as the target device, and the work order information in which the person participated is retrieved from the operating data of the target device. The second recognition result indicating whether the target device is abnormal is generated based on a second comparison result of the work order information and the corresponding historical work order information.

17. The monitoring method according to claim 16, characterized in that: The mind-body portrait includes at least one of an emotional state, a stress level, and a fatigue level; The method further comprises: When the emotional state of the person belongs to a preset negative emotional state and / or the stress level exceeds a preset stress threshold and / or the fatigue level exceeds a preset fatigue threshold, it is determined that the physical and mental portrait of the person is abnormal.

18. The monitoring method according to claim 16, characterized in that: The multidimensional space model includes a third processing logic for performing the following processing: Generate a personnel's operating habit portrait and behavior pattern portrait based on the personnel's historical operating data, and when the operating data associated with the personnel represents that the personnel's operating habits do not match the operating habit portrait and / or the behavior pattern does not match the behavior pattern portrait, generate a personnel monitoring warning for the personnel and / or generate an equipment monitoring warning for the equipment operated by the personnel.

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