CN116307674A

CN116307674A - Security supervision method, device, system, equipment, medium and product

Info

Publication number: CN116307674A
Application number: CN202211103103.1A
Authority: CN
Inventors: 孙利臣; 陈智慧; 连静静; 吴寒峰; 王晓岸
Original assignee: Beijing Brain Up Technology Co ltd
Current assignee: Beijing Brain Up Technology Co ltd
Priority date: 2022-09-09
Filing date: 2022-09-09
Publication date: 2023-06-23

Abstract

The invention discloses a safety supervision method, a device, a system, equipment, a medium and a product, wherein the method comprises the following steps: acquiring mental state data and physiological state data of a target object in at least one target supervision project and preset operation environment parameters corresponding to the at least one target supervision project; determining a risk early warning item in at least one target supervision item according to the mental state data, the physiological state data and the preset operation environment parameters; determining a project risk value of at least one target supervision project according to the risk early warning project; and determining the regional risk level corresponding to the region to which each target supervision project belongs according to the project risk value of at least one target supervision project. The technical scheme of the embodiment of the invention solves the problem of incomplete supervision projects of the target safety supervision scene, realizes safety supervision and risk early warning of the target safety supervision scene from individual operators to an integral operation area, and reduces the accident rate.

Description

Security supervision method, device, system, equipment, medium and product

Technical Field

The present invention relates to the field of security management technologies, and in particular, to a security supervision method, device, system, apparatus, medium, and product.

Background

In order to ensure smooth operation of construction projects and safety of operators, engineering operation environments are generally subjected to safety supervision, and when dangerous factors occur, risk early warning is performed to prompt the operators to pay attention to safety. The current safety supervision method is mostly implemented for a single operator, and under the conditions that a plurality of operators exist in an operation area and risk factors are complex, effective risk early warning is difficult to provide for the whole area.

Disclosure of Invention

The embodiment of the invention provides a safety supervision method, a device, a system, equipment, a medium and a product, which can analyze and monitor the operation risk condition from a person to an operation area in a complex operation area environment and ensure the operation safety.

In a first aspect, an embodiment of the present invention provides a security supervision method, where the method includes:

acquiring mental state data and physiological state data of a target object in at least one target supervision project and preset operation environment parameters corresponding to the at least one target supervision project;

determining a risk early warning item in the at least one target supervision item according to the mental state data, the physiological state data and the preset operation environment parameters;

Determining a project risk value of the at least one target supervision project according to the risk early warning project;

and determining the regional risk level corresponding to the region to which each target supervision project belongs according to the project risk value of the at least one target supervision project.

In a second aspect, an embodiment of the present invention further provides a security supervision apparatus, including:

the monitoring data acquisition module is used for acquiring mental state data and physiological state data of a target object in at least one target supervision project and preset operation environment parameters corresponding to the at least one target supervision project;

the risk early warning item determining module is used for determining a risk early warning item in the at least one target supervision item according to the mental state data, the physiological state data and the preset operation environment parameters;

the project risk assessment module is used for determining a project risk value of the at least one target supervision project according to the risk early warning item;

and the regional risk supervision module is used for determining the regional risk grade corresponding to the region to which each target supervision item belongs according to the item risk value of the at least one target supervision item.

In a third aspect, embodiments of the present invention further provide a security supervision system, the system comprising:

The brain electricity analysis system comprises an electroencephalogram analysis result acquisition unit, a physiological state data acquisition unit, a preset operation environment parameter acquisition unit and an early warning processing unit;

the electroencephalogram analysis result acquisition unit is used for acquiring mental state data of a target object in at least one target supervision project;

the physiological state data acquisition unit is used for acquiring physiological state data of a target object in the at least one target supervision project;

the preset operation environment parameter acquisition unit is used for acquiring preset operation environment parameters corresponding to the at least one target supervision item;

the early warning processing unit is used for determining a project risk value of the at least one target supervision project according to one or more risk early warning items in the mental state data, the physiological state data and the preset operation environment parameters, and determining a region risk level corresponding to a region to which each target supervision project belongs according to the project risk value of the at least one target supervision project.

In a fourth aspect, an embodiment of the present invention further provides an electronic device, including:

one or more processors;

storage means for storing one or more programs,

The one or more programs, when executed by the one or more processors, cause the one or more processors to implement the security supervision method provided by any embodiment of the invention.

In a fifth aspect, embodiments of the present invention further provide a computer readable storage medium having stored thereon a computer program which, when executed by a processor, implements the security supervision method provided by any of the embodiments of the present invention.

In a sixth aspect, embodiments of the present invention also provide a computer program product comprising a computer program which, when executed by a processor, implements a security supervision method according to any one of the embodiments of the present invention.

According to the technical scheme, mental state data and physiological state data of a target object in at least one target supervision project and preset operation environment parameters corresponding to the at least one target supervision project are obtained; determining a risk early warning item in the at least one target supervision item according to the mental state data, the physiological state data and the preset operation environment parameters; determining a project risk value of the at least one target supervision project according to the risk early warning project; and determining the regional risk level corresponding to the region to which each target supervision project belongs according to the project risk value of the at least one target supervision project. The technical scheme of the embodiment of the invention solves the problems that in the operation project requiring safety supervision, safety supervision is only carried out aiming at individuals, risk factors of the operation region cannot be comprehensively analyzed, and safety supervision is carried out on the whole region, and the like, realizes that the safety supervision and risk early warning are carried out on the whole operation region of a plurality of operation projects in multiple directions based on the angles of physiological states and mental states of operators to the environment of the operation project, and reduces the accident rate.

The technical scheme of the invention is further described in detail through the drawings and the embodiments.

Drawings

In order to more clearly illustrate the technical solution of the exemplary embodiments of the present invention, a brief description is given below of the drawings required for describing the embodiments. It is obvious that the drawings presented are only drawings of some of the embodiments of the invention to be described, and not all the drawings, and that other drawings can be made according to these drawings without inventive effort for a person skilled in the art. Wherein:

FIG. 1 is a flow chart of a security supervision method according to an embodiment of the present invention;

FIG. 2 is a schematic diagram of a risk indicator hierarchical management according to an embodiment of the present invention;

FIG. 3 is a diagram showing a fatigue alarm risk alarm index configuration according to an embodiment of the present invention;

FIG. 4 is a diagram showing a fatigue alarm risk alarm index configuration according to an embodiment of the present invention;

fig. 5 is a schematic structural diagram of a security supervision apparatus according to an embodiment of the present invention;

fig. 6 is a schematic structural diagram of a security supervision system according to an embodiment of the present invention;

FIG. 7 is a schematic diagram of another security supervision system according to an embodiment of the present invention;

Fig. 8 is a schematic diagram of a visual display of risk alarm data according to an embodiment of the present invention;

FIG. 9 is a schematic diagram of another visual presentation of risk alert data according to an embodiment of the present invention;

fig. 10 is a schematic structural diagram of an electronic device according to an embodiment of the present invention.

Detailed Description

Various exemplary embodiments of the present invention will now be described in detail with reference to the accompanying drawings. It should be noted that: the relative arrangement of the components and steps, numerical expressions and numerical values set forth in these embodiments do not limit the scope of the present invention unless it is specifically stated otherwise.

Meanwhile, it should be understood that the sizes of the respective parts shown in the drawings are not drawn in actual scale for convenience of description.

The following description of at least one exemplary embodiment is merely exemplary in nature and is in no way intended to limit the invention, its application, or uses. Techniques, methods, and apparatus known to one of ordinary skill in the relevant art may not be discussed in detail, but are intended to be part of the specification where appropriate.

It should be noted that: like reference numerals and letters denote like items in the following figures, and thus once an item is defined in one figure, no further discussion thereof is necessary in subsequent figures.

It can be appreciated that before using the technical solutions disclosed in the embodiments of the present invention, the user should be informed and authorized of the type, the usage range, the usage scenario, etc. of the personal information related to the present invention in an appropriate manner according to the relevant laws and regulations.

Fig. 1 is a schematic flow chart of a security supervision method according to an embodiment of the present invention, where the embodiment is applicable to a scenario of performing security supervision on a working area with possibility of accident, especially a service scenario of manual operation, and the method may be performed by a security supervision device, which may be implemented by software and/or hardware, and may be configured in a terminal and/or a server to implement the security supervision method according to the embodiment of the present invention.

As shown in fig. 1, the security supervision method of the present embodiment may specifically include:

s110, acquiring mental state data and physiological state data of a target object in at least one target supervision project and preset operation environment parameters corresponding to the at least one target supervision project.

The target supervision project may be any one of the work projects in the work area where the safety work supervision is required, and is a work project where the safety supervision is required for the operators and the work environment, such as each project of the infrastructure. The number of the target supervision items may be one or more, and may be determined according to the target supervision items set by the user of the security supervision system.

The target object is a person who performs an actual operation in each target supervision project. In this embodiment, each item of monitoring data of the target object is obtained by obtaining monitoring data capable of reflecting the operation condition, the safety state and the operation environment of the target object from the corresponding data source terminal through a preset data acquisition communication interface.

For example, aiming at mental state data of a target object, connecting a preset electroencephalogram signal analysis server through a preset data acquisition interface to acquire mental state data; the mental state data comprise at least one of fatigue state evaluation data, attention state evaluation data and visual dizziness state evaluation data which are determined by analyzing an electroencephalogram signal of a target object in the working process. Specifically, the complete acquisition process of the mental state data about the target object may be to wear the intelligent wearable device by the target object in the working process, so as to realize the acquisition of the monitoring data. In one possible implementation mode, the electroencephalogram signal acquisition device is arranged on a safety helmet worn by a target object in the working process so as to acquire the electroencephalogram signal of the target object in the working process. And the electroencephalogram signal acquisition device can upload the acquired electroencephalogram signal to a preset electroencephalogram signal analysis server, and the server analyzes the acquired electroencephalogram signal to determine mental state data of the target object. If the analyzed electroencephalogram data is an electroencephalogram with a plurality of data fragments identified as fatigue, one data fragment corresponds to one fatigue state alarm prompt. Similarly, the attention state and the visual dizziness state of the target object can be determined by a preset electroencephalogram analysis algorithm. And then, each result of the electroencephalogram signal analysis is sent to a safety supervision and risk early warning system through a preset data acquisition interface by a preset electroencephalogram signal server, so that corresponding monitoring data can be obtained in real time.

The physiological status data of the target object may also be real-time data collected by the intelligent wearable device, including at least one data of body temperature, blood pressure, blood oxygen saturation and heart rate. The data transmission interface of the corresponding intelligent wearable device can be directly connected through the preset data acquisition interface, and the corresponding physiological state detection data can be obtained through connecting the preset physiological state parameter detection server. In addition, the operation duration can be determined by the duration of wearing the intelligent wearable equipment so as to assist in judging the conditions such as fatigue operation.

The preset operation environment parameters corresponding to each target supervision project are different according to different specific operation contents, such as the temperature, humidity, depth, brightness of the operation environment of the target supervision project, the height of the overhead operation, the configuration of safety protection equipment and other environment parameters.

S120, determining a risk early warning item in the at least one target supervision item according to the mental state data, the physiological state data and the preset operation environment parameters.

Generally, when the indexes of each monitoring data are all in the safety value range, the operation area is relatively safe, and risk early warning is not generated. When one or more data of mental state data, physiological state data and preset operation environment parameters exceeds a preset safety value range and reaches a corresponding preset early warning threshold value, the corresponding data item is the required risk early warning item. By setting a reasonable early warning threshold value, each risk factor which possibly causes operation accidents in the target supervision project can be timely found. Therefore, the risk early warning item can be further analyzed to determine the item risk level of the target supervision item.

S130, determining the project risk value of the at least one target supervision project according to the risk early warning project.

Different risk early warning items can be divided into three-level risk index items according to attribute categories, wherein the three-level risk index items comprise a first-level index, a second-level index and a third-level index, and the classification relation can refer to the content shown in fig. 2. The first-level index represents an index library, is the highest-level class, and covers a plurality of factors influencing the risk of the project, such as project factors, risk alarms, supervision information and the like; the specific index items represented by the secondary indexes are the second classification of the primary index items, and the secondary index items are classified in the major class of the primary index library, for example, the risk alarm primary indexes are classified into electroencephalogram alarm, equipment alarm, overrun alarm, personnel positioning alarm and the like; the third-level index represents a specific index factor item, is a third classification of the second-level index subdivision, and respectively sets configuration information such as index names, index risk grades, calculation rules, collected data sources, weights, risk research and judgment results, treatment suggestions, index descriptions, index codes, index types and the like of various indexes in the level according to the specific index factor item.

Specifically, in the process of determining the risk level of the item, analysis and determination are gradually performed for each risk early-warning item classified in three levels. Determining the factor weight of the risk early warning item according to the alarm times of the corresponding risk early warning item and the corresponding preset risk level strategy; and determining the project risk value of the target supervision project corresponding to the risk early warning project according to the factor weight and the corresponding index weight of the risk early warning project. And finally, determining the risk level of the target supervision project based on the risk level interval corresponding to the project risk value. Corresponding factor weights and index weights are set for different risk early-warning items, and the influence degree of the different risk early-warning items on the item risks can be understood to be different. Therefore, the accuracy of judging the risk level of the project can be improved to a certain extent, and the situation of misjudgment of risks is reduced.

By way of example, fatigue alarms in mental state data are described. The specific index name, index risk level, calculation rule, collected data source, weight, risk study and judgment result, treatment suggestion, index description, index code, index type and other configuration information of the fatigue alarm index item are shown in the tables in fig. 3 and 4. The data source is a dynamic data source, and the data is indicated to be the monitoring data or the analysis result of the monitoring data obtained in real time by connecting the data with the corresponding data source through a preset data acquisition interface.

The fatigue alarm data are dynamically acquired data from a preset electroencephalogram signal analysis server, and can determine how many times (corresponding to the condition rule n) the electroencephalogram signal prompts fatigue alarm information in the acquisition period. The risk level of the fatigue alarm indicator term, and the factor weight corresponding to the level, may then be further determined from n. Assuming that in a fatigue alarm event, there are 10 electroencephalogram fatigue prompts, the corresponding grade is red, etc., the weight factor of the alarm event is 0.4, if the target supervision item has no other alarm item, the risk score of the target supervision direction is (weight factor 0.4 is index weight 0.5) 100=20. And carrying out risk level matching on the corresponding project sharing level according to the table 1, and determining the corresponding project sharing level as a yellow level.

Table 1 risk value and risk level matching table

And carrying out corresponding early warning prompt according to the early warning strategy of the corresponding project risk level. For example, in the target supervision project, the fatigue state of the operator is prompted, the safety operation prompt of the operator is noted to be enhanced, safety protection is performed for the operator, the scheduling rules of the operator are optimized, and the like, so that the safety of the operator in the operation process is improved.

And S140, determining the regional risk level corresponding to the region to which each target supervision project belongs according to the project risk value of the at least one target supervision project.

Furthermore, on the basis of the safety supervision data and the environmental data acquisition aiming at each target object, the regional risk condition of the region where each target supervision project is located can be further analyzed. The risk level of the area corresponding to the area to which each target supervision item belongs may be determined according to the risk level of at least one target supervision item including the risk early warning item. And matching corresponding regional risk early warning strategies according to the regional risk grades, and carrying out regional risk early warning prompt.

For example, in a large area including a plurality of target supervision items, each wind item index item in the plurality of target supervision items may be monitored at the same time, risk early warning items are determined according to the monitoring result, risk values of each index item are determined according to risk levels, factor weights, index weights and the like of each risk early warning item, risk values of each target supervision item and corresponding risk levels are determined step by step according to a preset recursive algorithm.

Suppose a ₀ Represents the risk level of a three-level index item (corresponding to one of red, orange, yellow or blue), a _n Representing the risk value of an index item, a _n Can be expressed as f ₁ (a ₀ )，f ₁ The function is the operation rule of the index item and can be a ₀ The corresponding factor weights are 100. Suppose a _n+1 Representing the risk value of the item, which can be expressed as f ₂ (a _n )，f ₂ The function is an item risk level operation rule, and may be a weighted sum of risk values of a plurality of index items according to index weights. Can be according to a _n+1 A risk level of the item is determined. Let am = regional risk level (regional item risk value), which can be expressed as f ₃ (a _n+1 ) The risk level rule (as in table 1). It will be appreciated that f for users of different security supervision and risk early warning systems ₁ 、f ₂ And f ₃ The method can be set in a self-defined way, and the calculation rule which is suitable for the own target supervision project is set.

Assuming the target supervision item a, there is a fatigue alarm event, the index weight is 0.5, it is red (a ₀ =red), the risk level of the alarm event is 0.4. Assuming that the early warning item of the whole item A is triggered by a fatigue warning event with high risk (red grade) after no other warning triggers at the moment, the corresponding risk value is (0.4 x 0.5) x 100=20, and the risk grade rule judges that the risk value of the item A is 10 less than or equal to n less than or equal to 20, the overall risk rating for item a is a yellow rating, with a score of 20 x 0.2=4. In addition, there are two risk alarm triggers in the target supervision item B, namely fatigue alarm (index weight is 0.5) and attention alarm (index weight is 0.4), and the risk value of the target supervision item B is: (0.4 x 0.5+0.2 x 0.4) x 100=28. It is apparent that 20<B<The risk rating for item B is yellow and the score is 28 x 0.2=5.6 points 68. The risk value of the area where the target supervision item a and the target supervision item B are located is 4+5.6=9.6 minutes and less than 10, so the risk level of the area is blue.

Fig. 5 is a schematic structural diagram of a security supervision apparatus according to an embodiment of the present invention. The safety supervision device provided by the embodiment is suitable for a scene of safety supervision on a working area with possibility of accident, in particular for a business scene of manual work of a plurality of items. The apparatus may be implemented in software and/or hardware, and the apparatus may be configured in an electronic device, for example, in a mobile terminal or server device.

As shown in fig. 5, the security supervision apparatus includes: a monitoring data acquisition module 210, a risk early warning item determination module 220, an item risk assessment module 230, and a regional risk supervision module 240.

The monitoring data obtaining module 210 is configured to obtain mental state data, physiological state data, and preset operation environment parameters corresponding to at least one target supervision item of a target object in the at least one target supervision item; a risk early warning item determining module 220, configured to determine a risk early warning item in the at least one target supervision item according to the mental state data, the physiological state data, and the preset operation environment parameter; an item risk assessment module 230 for determining an item risk value of the at least one target supervision item from the risk early warning item; the regional risk supervision module 240 is configured to determine a regional risk level corresponding to a region to which each of the target supervision items belongs according to the item risk value of the at least one target supervision item.

In an alternative embodiment, the risk early warning item determining module 220 is specifically configured to:

And determining any data item of which any numerical value of the mental state data, the physiological state data and the preset operation environment parameter is larger than a corresponding preset risk early warning threshold value as a risk early warning item.

In an alternative embodiment, the project risk assessment module 230 is specifically configured to:

determining factor weights of the risk early-warning items according to the alarm times of the risk early-warning items based on a preset risk level strategy;

and determining the project risk value of the target supervision project corresponding to the risk early warning project according to the factor weight and the corresponding index weight of the risk early warning project.

In an alternative embodiment, the item risk assessment module 230 is further configured to:

determining the risk score of the corresponding risk early warning item according to the factor weight and the corresponding index weight of the risk early warning item;

determining the sum of the risk scores of all the risk early warning items in each target supervision item as the item risk value of each target supervision item;

and determining the risk level of each target supervision project based on the risk level score interval of the project risk value.

In an alternative embodiment, the regional risk supervision module 240 is specifically configured to:

Determining the sum of the project risk values of the at least one target supervision project as a region risk value of a region to which each target supervision project belongs;

and determining the regional risk grade of the region of each target supervision project according to the risk grade score interval corresponding to the regional risk value.

In an alternative embodiment, the monitoring data acquisition module 210 is specifically configured to:

connecting a preset electroencephalogram signal analysis server through a preset data acquisition interface to acquire the mental state data;

the mental state data comprise at least one of fatigue state evaluation data, attention state evaluation data and visual dizziness state evaluation data which are determined by analyzing an electroencephalogram signal of the target object in the working process.

In an alternative embodiment, the safety supervision apparatus further comprises:

and the risk early warning module is used for determining a corresponding risk early warning strategy according to the regional risk grade and carrying out risk early warning.

The safety supervision device provided by the embodiment of the invention can execute the safety supervision method provided by any embodiment of the invention, and has the corresponding functional modules and beneficial effects of the execution method.

Fig. 6 is a schematic structural diagram of a security supervision system according to an embodiment of the present invention. The safety supervision and risk early warning system provided by the embodiment is suitable for the scene of safety supervision on the operation area with possibility of accident, in particular for the business scene of manual operation.

As shown in fig. 6, the security supervision system includes:

the brain electricity analysis system comprises an electroencephalogram analysis result acquisition unit, a physiological state data acquisition unit, a preset operation environment parameter acquisition unit and an early warning processing unit.

The electroencephalogram analysis result acquisition unit is used for connecting a preset electroencephalogram analysis server through a preset data acquisition interface to acquire mental state data of a target object in at least one target supervision project. The target object is a person who performs an actual job in each target supervision item. The mental state data comprises at least one of fatigue state evaluation data, attention state evaluation data and visual dizziness state evaluation data which are determined by analyzing an electroencephalogram signal of a target object in the working process.

And the physiological state data acquisition unit is used for acquiring physiological state data of a target object in at least one target supervision project. Specifically, the physiological state data acquisition unit may acquire real-time physiological state data including at least one data of body temperature, blood pressure, blood oxygen saturation and heart rate by connecting the intelligent wearing device; the intelligent wearing equipment can be connected with the preset physiological state parameter detection service end to acquire real-time physiological state detection data.

The preset operation environment parameter acquisition unit is used for acquiring preset operation environment parameters corresponding to at least one target supervision project. The preset operation environment parameters may be different according to the specific operation content, such as the temperature, humidity, depth, brightness, etc. of the target supervision project operation environment.

The early warning processing unit is used for determining a project risk value of at least one target supervision project according to one or more risk early warning items in the mental state data, the physiological state data and the preset operation environment parameters, and determining a region risk grade corresponding to a region to which each target supervision project belongs according to the project risk value of the at least one target supervision project.

Through the functional units, safety supervision is performed in all directions from a person in an area containing a target supervision project to the whole area, so that the operation safety index in the whole area is improved, and the operation accident rate is correspondingly reduced.

Specifically, in this embodiment, during the process of performing risk early warning analysis processing, the early warning processing unit may adopt an early warning rule of a multi-level structure, for example, first calculate a weight score of each factor according to the latest variation analysis of multiple risk factors, and determine a risk level of a corresponding target supervision item; then, determining the regional risk level corresponding to the region to which each target supervision item belongs according to the risk level of at least one target supervision item containing the early warning item, matching the corresponding regional risk early warning strategy according to the regional risk level, and carrying out regional risk early warning prompt, namely gathering the item risk supervision information up to the last level, and determining the risk level in the regional range based on a plurality of target supervision items; the early warning result of the group monitoring the multiple areas can be further calculated, and a favorable tool is provided for a decision maker to discover risks in advance. It can be appreciated that in the actual target project supervision process, the early warning rules can be personalized to formulate corresponding rules according to specific project contents and requirements of system users on project supervision.

In one embodiment, further as shown in fig. 7, the safety supervision system further includes other functional modules, such as an alarm processing unit and a risk alarm result display unit.

And the alarm processing unit is used for carrying out risk alarm according to the project risk level and/or the regional risk level. For example, if the project risk level or the regional risk level reaches the red level, an alarm message is sent to prompt the relevant manager or operator to pay attention to the risk hidden danger and solve the corresponding risk problem.

And the risk alarm result display unit is used for displaying the project risk data and the corresponding regional risk data of the target supervision project according to at least one preset information display dimension. The preset information presentation dimension may include one or more of area information, alarm items, alarm times, alarm levels, number of operators, alarm handling conditions, and alarm statistics. The alarm information visual display interface can be specifically referred to as shown in fig. 8 and 9. The physiological monitoring information and the electroencephalogram signals of each target object are collected through intelligent wearing equipment, such as intelligent safety helmets, and each safety helmet corresponds to one target object one by one, so that accurate matching of the information and the target object can be ensured. If the safety helmet is taken off, information cannot be continuously collected, the safety helmet can be detected, and a corresponding cap-off alarm can be initiated. SOS refers to help seeking alarm actively sent by a target object, and can carry out alarm help seeking when an emergency occurs.

In addition, the safety supervision system may further include one or more units of a target object management unit, a job recording unit of a target supervision project, a target object positioning information management unit, a target object attendance management unit, and a job equipment management unit of a target object. The target object management unit is used for managing the archive information of the target object, judging whether conditions such as physical conditions of the target object can be qualified for the task of the target supervision project based on the archive information, matching proper tasks for the target object, and reducing the task risk caused by discomfort. And the job recording unit of the target supervision project is used for recording the job content and the job progress of the target supervision project. The target object positioning information management unit is used for acquiring the position information of the target object in the target supervision project operation area; when the position information of the target object deviates from the normal operation area range, a corresponding alarm prompt is sent. The target object attendance management unit is used for managing the work attendance information of the target object in the target supervision project; when the attendance time of a single operation is too long, potential safety hazards can also exist. And the working equipment management unit is used for matching the target object with corresponding working equipment, wherein the working equipment can comprise working equipment such as a safety helmet and the like.

Correspondingly, the early warning processing unit can also be used for carrying out risk early warning processing according to information provided by the target object management unit, the job recording unit of the target supervision project, the target object positioning information management unit and/or the target object attendance management unit and preset risk early warning rules. If the target object is too long, or the target object is not suitable for the current operation content, etc.

Further, the safety supervision system may further comprise a data query unit for matching the risk index item data associated with the data query instruction and/or the historical risk early warning data of the target supervision item in response to the data query instruction of the user. The user may refer to a manager of the target supervision project and related personnel. The user can inquire any monitoring information in the process of carrying out the target supervision project and contents such as worker information and the like through the inquiry unit.

It can be understood that different users can self-define the monitoring data items, the early warning rules and the like in the safety supervision and risk early warning system so as to better match the service of the users.

According to the technical scheme, a safety supervision system comprising a plurality of functional units is constructed, so that the safety supervision process can be carried out on the working environment of at least one target supervision project and the working process of the working personnel, and mental state data, physiological state data and preset working environment parameters corresponding to the target object in the target supervision project can be obtained in the supervision process; when one or more data of mental state data, physiological state data and preset operation environment parameters reach corresponding preset early warning thresholds, the corresponding risk early warning items are called, and then item risk levels of corresponding target supervision items are calculated according to preset calculation rules according to index weight parameters of the corresponding risk early warning item data and the corresponding risk early warning items; therefore, the corresponding project risk early warning strategies can be matched based on the project risk grade of the target supervision project containing the early warning term, and project risk early warning prompt is carried out. The technical scheme of the embodiment of the invention solves the problems that in the operation project requiring safety supervision, safety supervision is only carried out aiming at individuals, risk factors of the operation region cannot be comprehensively analyzed, and safety supervision is carried out on the whole region, and the like, realizes that the safety supervision and risk early warning are carried out on the whole operation region of a plurality of operation projects in multiple directions based on the angles of physiological states and mental states of operators to the environment of the operation project, and reduces the accident rate.

Fig. 10 is a schematic structural diagram of an electronic device according to an embodiment of the present invention. Fig. 10 illustrates a block diagram of an exemplary electronic device 12 suitable for use in implementing embodiments of the present invention. The electronic device 12 shown in fig. 10 is merely an example and should not be construed as limiting the functionality and scope of use of embodiments of the present invention. Electronic device 12 may be any terminal device having computing capabilities, such as a personal computer system, server computer system, thin client, thick client, hand-held or laptop device, microprocessor-based system, set-top box, programmable consumer electronics, network personal computer, small computer system, mainframe computer system, and distributed cloud computing environment including any of the above, and the like.

As shown in fig. 10, the electronic device 12 is in the form of a general purpose computing device. Components of the electronic device 12 may include, but are not limited to: one or more processors or processing units 16, a system memory 28, a bus 18 that connects the various system components, including the system memory 28 and the processing units 16.

Bus 18 represents one or more of several types of bus structures, including a memory bus or memory controller, a peripheral bus, an accelerated graphics port, a processor, and a local bus using any of a variety of bus architectures. By way of example, and not limitation, such architectures include Industry Standard Architecture (ISA) bus, micro channel architecture (MAC) bus, enhanced ISA bus, video Electronics Standards Association (VESA) local bus, and Peripheral Component Interconnect (PCI) bus.

Electronic device 12 typically includes a variety of computer system readable media. Such media can be any available media that is accessible by electronic device 12 and includes both volatile and nonvolatile media, removable and non-removable media.

The system memory 28 may include computer system readable media in the form of volatile memory, such as Random Access Memory (RAM) 40 and/or cache memory 42. The electronic device 12 may further include other removable/non-removable, volatile/nonvolatile computer system storage media. By way of example only, storage system 44 may be used to read from and write to non-removable, nonvolatile magnetic media (not shown in FIG. 10, commonly referred to as a "hard disk drive"). Although not shown in fig. 10, a magnetic disk drive for reading from and writing to a removable non-volatile magnetic disk (e.g., a "floppy disk"), and an optical disk drive for reading from or writing to a removable non-volatile optical disk (e.g., a CD-ROM, DVD-ROM, or other optical media) may be provided. In such cases, each drive may be coupled to bus 18 through one or more data medium interfaces. The system memory 28 may include at least one program product having a set (e.g., at least one) of program modules configured to carry out the functions of the embodiments of the invention.

A program/utility 40 having a set (at least one) of program modules 42 may be stored in, for example, system memory 28, such program modules 42 including, but not limited to, an operating system, one or more application programs, other program modules, and program data, each or some combination of which may include an implementation of a network environment. Program modules 42 generally perform the functions and/or methods of the embodiments described herein.

The electronic device 12 may also communicate with one or more external devices 14 (e.g., keyboard, pointing device, display 24, etc.), one or more devices that enable a user to interact with the electronic device 12, and/or any devices (e.g., network card, modem, etc.) that enable the electronic device 12 to communicate with one or more other computing devices. Such communication may occur through an input/output (I/O) interface 22. Also, the electronic device 12 may communicate with one or more networks such as a Local Area Network (LAN), a Wide Area Network (WAN) and/or a public network, such as the Internet, through a network adapter 20. As shown, the network adapter 20 communicates with other modules of the electronic device 12 over the bus 18. It should be appreciated that although not shown in fig. 10, other hardware and/or software modules may be used in connection with electronic device 12, including, but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, data backup storage systems, and the like.

The processing unit 16 executes various functional applications and data processing by running programs stored in the system memory 28, for example, implementing the security supervision method provided by the present embodiment, the method includes:

The embodiment of the invention also provides a computer storage medium, on which a computer program is stored, which when executed by a processor, implements the security supervision method provided by the above embodiment.

The computer readable medium of the present invention may be a computer readable signal medium or a computer readable storage medium, or any combination of the two. The computer readable storage medium can be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or a combination of any of the foregoing. More specific examples of the computer-readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-Only Memory (ROM), an erasable programmable read-Only Memory (EPROM) or FLASH Memory (FLASH), an optical fiber, a portable compact disc read-Only Memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In the context of this document, a computer readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. In the present invention, however, the computer-readable signal medium may include a data signal propagated in baseband or as part of a carrier wave, with the computer-readable program code embodied therein. Such a propagated data signal may take any of a variety of forms, including, but not limited to, electro-magnetic, optical, or any suitable combination of the foregoing. A computer readable signal medium may also be any computer readable medium that is not a computer readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device. Program code embodied on a computer readable medium may be transmitted using any appropriate medium, including but not limited to: electrical wires, fiber optic cables, RF (radio frequency), and the like, or any suitable combination of the foregoing.

In some implementations, the clients, servers may communicate using any currently known or future developed network protocol, such as HTTP (HyperText Transfer Protocol ), and may be interconnected with any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include a local area network ("LAN"), a wide area network ("WAN"), the internet (e.g., the internet), and peer-to-peer networks (e.g., ad hoc peer-to-peer networks), as well as any currently known or future developed networks.

The computer readable medium may be contained in the electronic device; or may exist alone without being incorporated into the electronic device.

The computer readable medium carries one or more programs which, when executed by the electronic device, cause the electronic device to:

Computer program code for carrying out operations of the present invention may be written in one or more programming languages, including, but not limited to, an object oriented programming language such as Java, smalltalk, C ++ and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any kind of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or may be connected to an external computer (for example, through the Internet using an Internet service provider).

The flowcharts and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present invention. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.

The units involved in the embodiments of the present invention may be implemented in software or in hardware. The names of the units and modules do not limit the units and modules themselves in some cases, and the data generation module may be described as a "video data generation module", for example.

The functions described above herein may be performed, at least in part, by one or more hardware logic components. For example, without limitation, exemplary types of hardware logic components that may be used include: a field programmable gate array (Field Programmable Gate Array, FPGA), an application specific integrated circuit (Application Specific Integrated Circuit, ASIC), a special standard product (Application Specific Standard Parts, ASSP), a System On Chip (SOC), a Complex Programmable Logic Device (CPLD), and the like.

In the context of the present invention, a machine-readable medium may be a tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. The machine-readable medium may be a machine-readable signal medium or a machine-readable storage medium. The machine-readable medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any suitable combination of the foregoing. More specific examples of a machine-readable storage medium would include an electrical connection based on one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

It should be further noted that, in the present specification, each embodiment is described in a progressive manner, and each embodiment is mainly described as different from other embodiments, where the same or similar parts between the embodiments refer to each other. For the device embodiments, since they basically correspond to the method embodiments, the description is relatively simple, and the relevant points are referred to in the description of the method embodiments.

The method and apparatus of the present invention may be implemented in a number of ways. For example, the methods and apparatus of the present invention may be implemented by software, hardware, firmware, or any combination of software, hardware, firmware. The above-described sequence of steps for the method is for illustration only, and the steps of the method of the present invention are not limited to the sequence specifically described above unless specifically stated otherwise. Furthermore, in some embodiments, the present invention may also be embodied as programs recorded in a recording medium, the programs including machine-readable instructions for implementing the methods according to the present invention. Thus, the present invention also covers a recording medium storing a program for executing the method according to the present invention.

Embodiments of the present invention also provide a computer program product comprising a computer program which, when executed by a processor, implements a security supervision method as provided in any of the embodiments of the present application.

Computer program product in the implementation, the computer program code for carrying out operations of the present invention may be written in one or more programming languages, including an object oriented programming language such as Java, smalltalk, C ++ and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any kind of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or may be connected to an external computer (for example, through the Internet using an Internet service provider).

The description of the present invention has been presented for purposes of illustration and description, and is not intended to be exhaustive or limited to the invention in the form disclosed. Many modifications and variations will be apparent to those of ordinary skill in the art. The embodiments were chosen and described in order to best explain the principles of the invention and the practical application, and to enable others of ordinary skill in the art to understand the invention for various embodiments with various modifications as are suited to the particular use contemplated.

Claims

1. A method of security supervision, comprising:

2. The method of claim 1, wherein said determining a risk early warning item of said at least one target supervisory item from said mental state data, said physiological state data, and said preset operating environment parameters comprises:

3. The method of claim 1, wherein the determining the item risk value for the at least one target supervisory item from the risk early warning items comprises:

4. A method according to claim 3, wherein the determining the item risk value of the target supervision item corresponding to the risk early warning item according to the factor weight and the corresponding index weight of the risk early warning item comprises:

5. The method according to claim 1, wherein determining the regional risk level corresponding to the region to which each of the target supervisory items belongs according to the item risk value of the at least one target supervisory item comprises:

6. The method of claim 1, wherein the obtaining mental state data of a target subject in at least one target regulatory project comprises:

7. The method according to claim 1, wherein the method further comprises:

and determining a corresponding risk early warning strategy according to the regional risk grade, and carrying out risk early warning.

8. A security supervision apparatus, comprising:

9. A security supervision system, comprising:

10. The system of claim 9, wherein the system further comprises: the alarm processing unit and the risk alarm result display unit;

the alarm processing unit is used for carrying out risk alarm according to the project risk level and/or the regional risk level;

the risk alarm result display unit is used for displaying the project risk data and the corresponding regional risk data of the target supervision project according to at least one preset information display dimension.

11. The system of claim 9, wherein the system further comprises:

one or more units of a target object management unit, a job recording unit of a target supervision project, a target object positioning information management unit, a target object attendance management unit and a job equipment management unit of a target object;

The target object management unit is used for managing archive information of the target object;

the job recording unit of the target supervision project is used for recording the job content and the job progress of the target supervision project;

the target object positioning information management unit is used for acquiring the position information of the target object in the target supervision project operation area;

the target object attendance management unit is used for managing the work attendance information of the target object in the target supervision project;

and the operation equipment management unit of the target object is used for matching the target object with corresponding operation equipment.

12. The system according to claim 11, wherein the early warning processing unit is further configured to perform risk early warning processing according to a preset risk early warning rule according to information provided in the target object management unit, the job recording unit of the target supervision project, the target object positioning information management unit, and/or the target object attendance management unit.

13. The system of claim 9, wherein the system further comprises:

and the data query unit is used for responding to the data query instruction of the user and matching the risk index item data and/or the historical risk early warning data of the target supervision item associated with the data query instruction.

14. An electronic device, the electronic device comprising:

one or more processors;

storage means for storing one or more programs,

when executed by the one or more processors, cause the one or more processors to implement the security supervision method of any one of claims 1-7.

15. A computer readable storage medium having stored thereon a computer program, which when executed by a processor implements a security supervision method according to any one of claims 1 to 7.

16. A computer program product comprising a computer program which, when executed by a processor, implements the security supervision method according to any one of claims 1 to 7.