CN115827987A - Recommendation method, device, equipment and medium for behavior safety intervention content - Google Patents
Recommendation method, device, equipment and medium for behavior safety intervention content Download PDFInfo
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Abstract
The application provides a recommendation method, a recommendation device, recommendation equipment and a recommendation medium for behavior safety intervention content, which relate to the technical field of behavior safety intervention, and the method comprises the following steps: detecting construction dangerous behaviors, and acquiring identity information of workers who are in the current construction dangerous behaviors when the construction dangerous behaviors are detected; determining danger degree information and risk factor information based on worker identity information, construction dangerous behavior records of the workers and current construction dangerous behaviors; determining a recommended class hour critical value based on the danger degree information; matching safety training recommended contents in a safety training course library based on the risk factor information, dividing the safety training recommended contents through recommended class time critical values, determining recommended course lessons corresponding to different risk factor labels, and recommending behavior safety intervention contents based on the recommended course lessons. According to the method and the device, large-scale keyword indexes do not need to be established, the workload is reduced, and the efficiency of safety training is further improved.
Description
Technical Field
The present application relates to the field of behavioral security intervention technologies, and in particular, to a method, an apparatus, a device, and a medium for recommending behavioral security intervention content.
Background
Every industry has the safety production regulation suitable for the development of the industry, and primary practitioners in the industry need to be familiar with safety knowledge in the industry and have the safety practical operation capability to ensure the production safety of the industry and the industry, so that the irreversible harm to the industry and the self caused by the incapability of fulfilling safety responsibility is avoided. The construction safety training needs to be carried out in a classified mode, and what training needs to be carried out step by step, so that the condition that workers have qualified safety capability can be operated on duty is ensured.
At present, regular and targeted learning by workers has become popular, but in the process of popularization: most workers on site have poor learning ability, so that when they need to learn all the contents, the efficiency is low, and the repulsive psychology of workers is in reverse. And each worker has the work category under the familiar environment, the worker can further increase the rejection psychology of the worker when the work category under the familiar environment is continuously learned, and the worker is not better than the worker who learns the work category under the familiar environment, so that the worker spends time on the work category under the less familiar environment or the work category which is not qualified before, and the targeted and efficient learning is realized.
In the related art, a security education library is generated by listing education materials through a tree structure, and an identification tag of at least one dimension is created for each education material to obtain an identification tag set, however, recommendation of education contents based on keywords is not accurate enough, and a large-scale index needs to be created in advance, which is labor-intensive.
Disclosure of Invention
The application aims to provide a recommendation method, device, equipment and medium for behavior safety intervention content, large-scale keyword indexes do not need to be established, workload is reduced, and safety training efficiency is improved.
In a first aspect, the present invention provides a recommendation method for behavior safety intervention content, the method including: detecting construction dangerous behaviors, and acquiring identity information of workers who have the current construction dangerous behaviors when the construction dangerous behaviors are detected; determining danger degree information and risk factor information based on worker identity information, construction dangerous behavior records of the workers and current construction dangerous behaviors; the risk factor information comprises risk factor labels and corresponding proportions of the risk factor labels; determining a recommended class hour critical value based on the danger degree information; matching safety training recommended contents in a safety training course library based on the risk factor information, dividing the safety training recommended contents through recommended class time critical values, determining recommended course lessons corresponding to different risk factor labels, and recommending behavior safety intervention contents based on the recommended course lessons.
In an optional embodiment, the determining the risk level information and the risk factor information based on the identity information of the worker, the construction risk behavior record of the worker and the current construction risk behavior comprises: matching construction dangerous behavior records of the workers based on the identity information of the workers; if multiple records of the current construction dangerous behaviors exist in the construction dangerous behavior records, determining danger degree information based on the recording times; and determining the risk factor labels and the corresponding proportion of each risk factor label relative to all risk labels based on the construction risk behavior record.
In an alternative embodiment, the determining the risk degree information and the risk factor information based on the worker identity information, the construction risk behavior record of the worker and the current construction risk behavior includes: judging whether a training record matched with the construction dangerous behavior record of the worker exists in a course training record library corresponding to the identity information of the worker; and if so, determining danger degree information and risk factor information based on the identity information of the worker, the safety training record of the worker, the construction dangerous behavior record of the worker and the current construction dangerous behavior.
In an alternative embodiment, the method further comprises: pushing the safety training recommendation content so as to display the safety training recommendation content through a terminal corresponding to a worker; the displayed content at least comprises recommended course lessons, course icons, course lessons corresponding to the course icons and risk factor labels.
In an alternative embodiment, the method further comprises: carrying out real-time periodic sequencing on the course icons based on the duration ratio of the remaining minimum sub-courses corresponding to each risk factor label and the risk factor label corresponding to the course; the sorting conditions corresponding to the real-time periodic sorting at least comprise: and sequencing according to the time length of the residual minimum lesson, or sequencing according to the similarity between the time length of the lesson and the time length of the residual minimum lesson in the same risk factor.
In an alternative embodiment, the method further comprises: responding to the learning event of the worker aiming at the safety training recommended content, dynamically adjusting the recommended class time critical value and the recommended class lesson time corresponding to each risk factor label in real time, and displaying the residual minimum total class and the recommended class lesson time.
In an alternative embodiment, the method further comprises: a first matching relation between the risk causing factor tag and a risk behavior result and a second matching relation between the risk causing factor tag and safety training recommendation content are configured in advance; responding to completion of a learning event of a worker for recommending contents for safety training, monitoring the behavior of the worker, and determining worker behavior feedback information; optimizing the first matching relationship and the second matching relationship based on worker behavior feedback information.
In a second aspect, the present invention provides a recommendation apparatus for behavior safety intervention content, the apparatus comprising: the detection and acquisition module is used for detecting construction dangerous behaviors and acquiring the identity information of workers who are in the current construction dangerous behaviors when the construction dangerous behaviors are detected; the first determining module is used for determining danger degree information and risk factor information based on worker identity information, construction dangerous behavior records of workers and current construction dangerous behaviors; the risk factor information comprises risk factor labels and corresponding proportions of the risk factor labels; the second determination module is used for determining a recommended class time critical value based on the danger degree information; and the content recommendation module is used for matching safety training recommendation content in the safety training course library based on the risk factor information, dividing the safety training recommendation content according to the recommended class time critical value, and recommending behavior safety intervention content when determining recommended course sub-classes corresponding to different risk factor labels.
In a third aspect, the present invention provides an electronic device, including a processor and a memory, where the memory stores computer-executable instructions capable of being executed by the processor, and the processor executes the computer-executable instructions to implement the recommendation method for content of safety intervention in behavior of any one of the foregoing embodiments.
In a fourth aspect, the present invention provides a computer-readable storage medium storing computer-executable instructions that, when invoked and executed by a processor, cause the processor to implement the method of recommending behavioural safety intervention content of any of the preceding embodiments.
According to the recommendation method, device, equipment and medium for the behavior safety intervention content, the construction dangerous behavior is detected, the identity information of a worker who is in the current construction dangerous behavior is obtained when the construction dangerous behavior is detected, and then the danger degree information and the risk factor information are determined based on the identity information of the worker, the construction dangerous behavior record of the worker and the current construction dangerous behavior; the risk factor information comprises risk factor labels and corresponding proportions of the risk factor labels. And then determining a recommended class time critical value based on the danger degree information, finally matching safety training recommended contents in a safety training class library based on the risk factor information, dividing the safety training recommended contents by recommending the class time critical value, determining recommended class sublibraries corresponding to different risk factor labels, and recommending behavior safety intervention contents based on the recommended class sublibraries. According to the method, a large-scale keyword index does not need to be established, the workload is reduced, and the efficiency of safety training is further improved.
Drawings
In order to more clearly illustrate the detailed description of the present application or the technical solutions in the prior art, the drawings used in the detailed description or the prior art description will be briefly described below, and it is obvious that the drawings in the following description are some embodiments of the present application, and other drawings can be obtained by those skilled in the art without creative efforts.
Fig. 1 is a flowchart of a method for recommending content of behavior security intervention according to an embodiment of the present application;
FIG. 2 is a flowchart of content recommendation of behavior safety intervention based on risk factor according to an embodiment of the present application;
fig. 3 is a block diagram of a recommendation apparatus for content of behavioral security intervention according to an embodiment of the present application;
fig. 4 is a structural diagram of an electronic device according to an embodiment of the present application.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are some embodiments of the present application, but not all embodiments. The components of the embodiments of the present application, generally described and illustrated in the figures herein, can be arranged and designed in a wide variety of different configurations.
Thus, the following detailed description of the embodiments of the present application, presented in the accompanying drawings, is not intended to limit the scope of the claimed application, but is merely representative of selected embodiments of the application. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.
It should be noted that: like reference numbers and letters refer to like items in the following figures, and thus, once an item is defined in one figure, it need not be further defined and explained in subsequent figures.
Considering that the current safety education and training are mostly static education before operation, even if the education and training are performed in the operation process, the current safety education and training are also behavior potential safety hazard data generated in the operation process through manual statistics, risk factors caused by the behavior potential safety hazards are analyzed manually, an education and training scheme is selected manually, and prandial group education and training are performed manually, so that manual statistics is time-consuming and labor-consuming, the workload of manual course selection is large, the training scheme is lack of pertinence, and the training opportunity is lack of timeliness.
The embodiment of the application provides a recommendation method of behavior safety intervention content, and as shown in fig. 1, the method mainly includes the following steps:
and S102, detecting construction dangerous behaviors, and acquiring identity information of workers in the current construction dangerous behaviors when the construction dangerous behaviors are detected.
Step S104, determining danger degree information and risk factor information based on worker identity information, construction dangerous behavior records of the workers and current construction dangerous behaviors; the risk factor information comprises risk factor labels and corresponding proportions of the risk factor labels;
and step S106, determining a recommended class time critical value based on the danger degree information. The recommended class time critical value is used for representing the minimum total class time of training courses needing to be recommended.
And S108, matching safety training recommended contents in a safety training course library based on the risk factor information, dividing the safety training recommended contents by recommending a class time critical value, determining recommended course lessons corresponding to different risk factor labels, and recommending behavior safety intervention contents based on the recommended course lessons. The course subclause recommending time is the minimum subclause time corresponding to different risk factor labels obtained by dividing the minimum total class time of training courses needing to be recommended.
According to the recommendation method of the behavior safety intervention content, after risk factors of the behavior safety potential hazards in the operation process of a specific object (individual, team or unit) can be accurately identified and counted, an individualized training scheme can be automatically and accurately selected and pushed for the specific object according to the risk factor proportion, accurate support is provided for training management, training management capacity and efficiency are improved, and training pertinence, timeliness and effectiveness are improved; large-scale keyword indexes do not need to be established, the workload is reduced, and the efficiency of safety training is further improved.
For convenience of understanding, the following describes in detail a recommendation method of content of behavior safety intervention provided in an embodiment of the present application.
Firstly, the scheme is applied to behavior intervention of workers in the construction process, so that when dangerous construction behaviors occur, the workers can learn corresponding safety training knowledge by recommending safety training contents, and the construction safety is improved. In one example, when worker a is performing a fire operation, the most familiar operating environment is environment a, i.e., he is familiar with the fact that material cannot be deposited under the fire in environment a, or that non-operators cannot access the welding apparatus, so when identifying worker behavior, it is necessary to investigate whether the worker stacks material as desired, performs an activity within a safe range, in other words, whether the worker is operating in violation or otherwise intruding without permission into a prohibited area. If every learning pushes the relevant educational content of the fire work in environment a to him from the start to the end of the project, he will only choose to make an opportunity to get an ingenious way to escape such learning. If the corresponding work category can be pushed to the unfamiliar environment every time of learning, the operation is better than the fire operation in the environment B, so that the enthusiasm of the user in learning is generated, and the learning time is saved for the user.
In an optional embodiment, the determining of the risk degree information and the risk factor information based on the identity information of the worker, the construction risk behavior record of the worker, and the current construction risk behavior may include the following steps 1.1) to 1.3):
step 1.1), matching construction dangerous behavior records of workers based on worker identity information;
step 1.2), if multiple records of the current construction dangerous behaviors exist in the construction dangerous behavior records, determining danger degree information based on the recording times;
and step 1.3), determining risk factor tags and the corresponding proportion of each risk factor tag relative to all risk factor tags based on construction risk behavior records.
In another optional embodiment, the determining of the risk degree information and the risk factor information based on the identity information of the worker, the construction risk behavior record of the worker and the current construction risk behavior may include the following steps 2.1) and 2.2):
step 2.1), judging whether a training record matched with the construction dangerous behavior record of the worker exists in a course training record library corresponding to the identity information of the worker;
and 2.2) if the information exists, determining danger degree information and risk factor information based on the identity information of the worker, the safety training record of the worker, the construction dangerous behavior record of the worker and the current construction dangerous behavior.
Further, the method further comprises: pushing the safety training recommendation content so as to display the safety training recommendation content on an interface through a terminal corresponding to a worker; the displayed content at least comprises recommended course lessons, course icons, course lessons corresponding to the course icons and risk factor labels.
In an optional embodiment, in order to facilitate the worker to learn about the safety training courses that are not learned and to improve the display effect of the unlearned contents, the method further includes: carrying out real-time periodic sequencing on the course icons based on the duration ratio of the remaining minimum sub-courses corresponding to each risk factor label and the risk factor label corresponding to the course;
the sorting conditions corresponding to the real-time periodic sorting at least comprise: and sequencing according to the duration of the remaining minimum sub-lessons, namely, sequencing periodically in real time based on the duration ratio of the remaining minimum sub-lessons corresponding to each risk factor label and the risk factor label corresponding to the lesson, wherein the lesson corresponding to the risk factor label with the longest remaining duration is ranked first. Or, in the same risk factor, the sequence is sequenced according to the similarity between the time length of the course and the time length of the remaining minimum lesson, that is, in the same risk factor, the time length of the course is closest to the earlier time of the remaining minimum lesson, and the same time length is longer than the earlier time of the remaining minimum lesson.
Further, in order to make the recommended content more suitable for the learning mind of the worker, so as to improve the effect of the safety training, in an optional embodiment, the method further includes: responding to the learning event of the worker aiming at the safety training recommended content, dynamically adjusting the recommended class time critical value and the recommended class lesson time corresponding to each risk factor label in real time, and displaying the residual minimum total class and the recommended class lesson time.
Further, the method further comprises:
step 3.1), a first matching relation between the risk factor label and the risk behavior result and a second matching relation between the risk factor label and the safety training recommendation content are configured in advance;
step 3.2), monitoring the behavior of the worker in response to the completion of the learning event of the recommended content of the worker for safety training, and determining the feedback information of the behavior of the worker;
and 3.3) optimizing the first matching relation and the second matching relation based on worker behavior feedback information.
In an implementation manner, the recommendation method for behavior safety intervention content provided in this embodiment may perform behavior safety intervention content recommendation based on risk factors when implemented specifically, as shown in fig. 2, including the following steps S1 to S5:
step S1, a dangerous behavior list is determined.
And S2, determining dangerous behavior risk factors.
And S3, determining a mechanism of the risk factor influencing the dangerous behavior.
And S4, determining the association relationship between the educational training courseware and the risk factors.
And S5, determining an algorithm for recommending educational training courseware based on risk factors.
Among these, risk factors can be seen in the examples: for example, the risk factor causing low hook height use may be that it is not used by itself, or is not thought of, then there is a problem around thought consciousness and skill, the courseware, record, video or animation of the found educational training is pushed to the person through the educational training platform, the system automatically pushes to provide the educational training, and the way to correct the unsafe behavior is an intervention.
When the dangerous behavior list is determined in the step S1, the dangerous behavior and the identity information of workers with the dangerous behavior can be determined through administrator entry or video behavior identification;
when determining dangerous behavior risk factors in step S2, determining degree evaluation and risk factor composition based on the training record of the worker, the dangerous behavior record and the current dangerous behavior, where the risk factor composition includes a risk factor label and a proportion corresponding to the label. And determining the minimum total class time of training courses to be recommended based on the degree evaluation, and dividing the total class time based on the risk causing factor composition to obtain the minimum sub-class time corresponding to different risk causing factor labels.
For step S4, recommended alternative courses may be matched in the training course library based on the risk factor composition to determine an association relationship of the educational training course and the risk factors.
Displaying the alternative courses through an interface for a user to select; the display interface comprises a residual minimum total class time and residual minimum sub-class times corresponding to all risk factor labels, a course icon, a course class time corresponding to the course icon and the risk factor labels; the course icon is subjected to real-time periodic sequencing based on the time length ratio of the remaining minimum lessons corresponding to each risk factor label and the risk factor labels corresponding to the courses, the course corresponding to the risk factor label with the longest remaining time length is arranged in the first place, and within the same risk factor, the time length of the course is closest to the time of the remaining minimum lessons and is more front, and the same time length is greater than the time of the remaining minimum lessons;
for example, the corresponding relationship between risk factor-the minimum total class left is: a-5 min, B-10 min, C-15 min:
the icons are ordered as: course C1 (course labeled risk factor C1), course B1, course A1; course C2, course B2, course A2; course C3, course B3, course A3; .......
And dynamically adjusting the remaining minimum total class time, the remaining minimum sub-class time corresponding to each risk factor label and the display result in real time based on the courses selected by the user until the remaining minimum total class time is 0, and determining the selected courses.
Further, the selected courses can be pushed to workers who have dangerous behaviors and are urged to complete learning.
Optionally, after learning, the behavior of the worker is supervised, the training effect is determined, and the determination mode of risk factor composition is optimized.
In an embodiment, the risk factor composition may be implemented by artificial intelligence and a multi-classification model, which are not described herein again.
Based on the above method embodiment, an embodiment of the present application further provides a recommendation device for behavior safety intervention content, as shown in fig. 3, where the device mainly includes the following components:
the detection and acquisition module 32 is used for detecting construction dangerous behaviors and acquiring the identity information of workers who take the current construction dangerous behaviors when the construction dangerous behaviors are detected;
a first determining module 34, configured to determine risk degree information and risk factor information based on worker identity information, a construction risk behavior record of the worker, and a current construction risk behavior; the risk factor information comprises risk factor labels and corresponding proportions of the risk factor labels;
a second determining module 36, configured to determine a recommended class time critical value based on the risk degree information;
and the content recommendation module 38 is configured to match safety training recommendation contents in a safety training course library based on the risk factor information, divide the safety training recommendation contents according to the recommended class time critical value, and recommend the behavior safety intervention contents when determining recommended class sublibraries corresponding to different risk factor labels.
In some embodiments, the first determining module 34 is further configured to: matching construction dangerous behavior records of the workers based on the identity information of the workers; if multiple records of the current construction dangerous behaviors exist in the construction dangerous behavior records, determining danger degree information based on the recording times; and determining risk factor tags and the corresponding proportion of each risk factor tag relative to all risk factor tags based on the construction risk behavior records.
In some embodiments, the first determining module 34 is further configured to: judging whether a training record matched with the construction risk behavior record of the worker exists in a course training record library corresponding to the identity information of the worker; and if so, determining danger degree information and risk factor information based on the identity information of the worker, the safety training record of the worker, the construction dangerous behavior record of the worker and the current construction dangerous behavior.
In some embodiments, the apparatus further comprises a pushing module configured to: pushing the safety training recommendation content so as to display the safety training recommendation content on an interface through a terminal corresponding to a worker; the displayed content at least comprises recommended course lessons, course icons, course lessons corresponding to the course icons and risk factor labels.
In some embodiments, the apparatus further comprises a sorting and displaying module configured to: carrying out real-time periodic sequencing on the course icons based on the duration ratio of the remaining minimum sub-courses corresponding to each risk factor label and the risk factor label corresponding to the course; the sorting conditions corresponding to the real-time periodic sorting at least comprise: and sequencing according to the time length of the residual minimum lesson, or sequencing according to the similarity between the time length of the lesson and the time length of the residual minimum lesson in the same risk factor.
In some embodiments, the apparatus further comprises a dynamic adjustment module configured to: responding to the learning event of the worker aiming at the safety training recommended content, dynamically adjusting the recommended class time critical value and the recommended class lesson time corresponding to each risk factor label in real time, and displaying the residual minimum total class and the recommended class lesson time.
In some embodiments, the apparatus further comprises a matching relationship optimization module configured to: a first matching relation between the risk factor label and the risk behavior result and a second matching relation between the risk factor label and the safety training recommendation content are configured in advance; responding to completion of a learning event of a worker for recommending contents for safety training, monitoring the behavior of the worker, and determining worker behavior feedback information; and optimizing the first matching relationship and the second matching relationship based on worker behavior feedback information.
The implementation principle and the generated technical effect of the recommendation device for behavior safety intervention content provided by the embodiment of the application are the same as those of the embodiment of the method, and for brief description, reference may be made to corresponding contents in the embodiment of the recommendation method for behavior safety intervention content where no part of the embodiment of the recommendation device for behavior safety intervention content is mentioned.
An electronic device is further provided, as shown in fig. 4, which is a schematic structural diagram of the electronic device, where the electronic device 100 includes a processor 41 and a memory 40, the memory 40 stores computer-executable instructions that can be executed by the processor 41, and the processor 41 executes the computer-executable instructions to implement any one of the methods for recommending behavior safety intervention contents.
In the embodiment shown in fig. 4, the electronic device further comprises a bus 42 and a communication interface 43, wherein the processor 41, the communication interface 43 and the memory 40 are connected by the bus 42.
The Memory 40 may include a high-speed Random Access Memory (RAM) and may also include a non-volatile Memory (non-volatile Memory), such as at least one disk Memory. The communication connection between the network element of the system and at least one other network element is realized through at least one communication interface 43 (which may be wired or wireless), and the internet, a wide area network, a local network, a metropolitan area network, etc. may be used. The bus 42 may be an ISA (Industry Standard Architecture) bus, a PCI (Peripheral Component Interconnect) bus, an EISA (Extended Industry Standard Architecture) bus, or the like. The bus 42 may be divided into an address bus, a data bus, a control bus, etc. For ease of illustration, only one double-headed arrow is shown in FIG. 4, but this does not indicate only one bus or one type of bus.
The processor 41 may be an integrated circuit chip having signal processing capabilities. In implementation, the steps of the above method may be performed by integrated logic circuits of hardware or instructions in the form of software in the processor 41. The Processor 41 may be a general-purpose Processor, and includes a Central Processing Unit (CPU), a Network Processor (NP), and the like; the device can also be a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), a Field Programmable Gate Array (FPGA) or other Programmable logic device, a discrete Gate or transistor logic device, or a discrete hardware component. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like. The steps of the method disclosed in connection with the embodiments of the present application may be directly implemented by a hardware decoding processor, or implemented by a combination of hardware and software modules in the decoding processor. The software module may be located in ram, flash memory, rom, prom, or eprom, registers, etc. storage media as is well known in the art. The storage medium is located in a memory, and the processor 41 reads information in the memory and completes the steps of the recommendation method of the content of the behavioral safety intervention of the foregoing embodiment in combination with hardware thereof.
The embodiment of the present application further provides a computer-readable storage medium, where the computer-readable storage medium stores computer-executable instructions, and when the computer-executable instructions are called and executed by a processor, the computer-executable instructions cause the processor to implement the recommendation method for behavior safety intervention content, and specific implementation may refer to the foregoing method embodiment, and details are not described herein again.
The method, apparatus, device, and medium for recommending behavior safety intervention content provided in the embodiments of the present application include a computer-readable storage medium storing program codes, where instructions included in the program codes may be used to execute the methods described in the foregoing method embodiments, and specific implementations may refer to the method embodiments, which are not described herein again.
Unless specifically stated otherwise, the relative steps, numerical expressions, and values of the components and steps set forth in these embodiments do not limit the scope of the present application.
The functions, if implemented in the form of software functional units and sold or used as a stand-alone product, may be stored in a non-volatile computer-readable storage medium executable by a processor. Based on such understanding, the technical solution of the present application or portions thereof that substantially contribute to the prior art may be embodied in the form of a software product stored in a storage medium and including instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method according to the embodiments of the present application. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and other various media capable of storing program codes.
In the description of the present application, it is noted that the terms "first", "second", "third", and the like are used merely for distinguishing between descriptions and are not intended to indicate or imply relative importance.
In the description of the present application, it is further noted that, unless expressly stated or limited otherwise, the terms "disposed," "mounted," "connected," and "connected" are to be construed broadly, e.g., as meaning either a fixed connection, a removable connection, or an integral connection; can be mechanically or electrically connected; they may be connected directly or indirectly through intervening media, or they may be interconnected between two elements. The specific meaning of the above terms in the present application can be understood in a specific case by those of ordinary skill in the art.
Finally, it should be noted that: the above embodiments are only used for illustrating the technical solutions of the present application, and not for limiting the same; although the present application has been described in detail with reference to the foregoing embodiments, it should be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some or all of the technical features may be equivalently replaced; and the modifications or the substitutions do not make the essence of the corresponding technical solutions depart from the scope of the technical solutions of the embodiments of the present application.
Claims (10)
1. A recommendation method for behavior safety intervention content, the method comprising:
detecting construction dangerous behaviors, and acquiring identity information of workers who are in the current construction dangerous behaviors when the construction dangerous behaviors are detected;
determining danger degree information and risk factor information based on the worker identity information, the construction dangerous behavior record of the worker and the current construction dangerous behavior; the risk factor information comprises risk factor labels and corresponding proportions of the risk factor labels;
determining a recommended class hour critical value based on the danger degree information;
matching safety training recommended contents in a safety training course library based on the risk factor information, dividing the safety training recommended contents according to the recommended class time critical value, determining recommended course sub-courses corresponding to different risk factor labels, and recommending behavior safety intervention contents based on the recommended course sub-courses.
2. The recommendation method of behavior safety intervention content according to claim 1, wherein determining the risk degree information and risk factor information based on the worker identity information, the construction risk behavior record of the worker and the current construction risk behavior comprises:
matching construction dangerous behavior records of the worker based on the identity information of the worker;
determining danger degree information based on the recording times if multiple records of the current construction dangerous behaviors exist in the construction dangerous behavior records;
and determining risk factor tags and the corresponding proportion of each risk factor tag relative to all risk factor tags based on the construction risk behavior records.
3. The recommendation method of the content of the behavioral safety intervention according to claim 1 or 2, wherein determining the information of the degree of danger and the information of the risk factor based on the identity information of the worker, the record of the construction risk behavior of the worker and the current construction risk behavior comprises:
judging whether a training record matched with the construction dangerous behavior record of the worker exists in a course training record library corresponding to the identity information of the worker;
and if so, determining danger degree information and risk factor information based on the identity information of the worker, the safety training record of the worker, the construction dangerous behavior record of the worker and the current construction dangerous behavior.
4. The recommendation method of the content of the behavioral safety intervention according to claim 1, further comprising:
pushing the safety training recommendation content so as to display the safety training recommendation content through a terminal corresponding to a worker; the displayed content at least comprises recommended course lessons, course icons, course lessons corresponding to the course icons and risk factor labels.
5. The recommendation method of the content of the behavioral safety intervention according to claim 4, further comprising:
carrying out real-time periodic sequencing on the course icons based on the duration ratio of the remaining minimum sub-courses corresponding to each risk factor label and the risk factor label corresponding to the course;
the sorting conditions corresponding to the real-time periodic sorting at least comprise: and sequencing according to the time length of the residual minimum lesson, or sequencing according to the similarity between the time length of the lesson and the time length of the residual minimum lesson in the same risk factor.
6. The recommendation method of the content of the behavioral safety intervention according to claim 1, further comprising:
responding to the learning event of the worker aiming at the safety training recommended content, dynamically adjusting the recommended class time critical value and the recommended class lesson time corresponding to each risk factor label in real time, and displaying the residual minimum total class and the recommended class lesson time.
7. The method for recommending behavior safety intervention contents according to claim 1, wherein the method further comprises:
a first matching relation between the risk factor label and the risk behavior result and a second matching relation between the risk factor label and the safety training recommendation content are configured in advance;
responding to completion of a learning event of a worker for recommending contents for safety training, monitoring the behavior of the worker, and determining worker behavior feedback information;
and optimizing the first matching relationship and the second matching relationship based on worker behavior feedback information.
8. An apparatus for recommending behavior safety intervention contents, the apparatus comprising:
the detection and acquisition module is used for detecting construction dangerous behaviors and acquiring the identity information of workers who are in the current construction dangerous behaviors when the construction dangerous behaviors are detected;
the first determining module is used for determining danger degree information and risk factor information based on the identity information of the worker, the construction dangerous behavior record of the worker and the current construction dangerous behavior; the risk factor information comprises risk factor labels and corresponding proportions of the risk factor labels;
the second determining module is used for determining a recommended class hour critical value based on the danger degree information;
and the content recommendation module is used for matching safety training recommendation content in a safety training course library based on the risk factor information, dividing the safety training recommendation content according to the recommended class time critical value, and recommending behavior safety intervention content when determining recommended course subclauses corresponding to different risk factor labels.
9. An electronic device comprising a processor and a memory, the memory storing computer-executable instructions executable by the processor, the processor executing the computer-executable instructions to implement the method of recommending content for a behavioral security intervention of any one of claims 1 to 7.
10. A computer-readable storage medium storing computer-executable instructions that, when invoked and executed by a processor, cause the processor to implement the method for recommending behavioral security intervention content according to any one of claims 1 to 7.
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Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102508846A (en) * | 2011-09-26 | 2012-06-20 | 深圳中兴网信科技有限公司 | Internet based method and system for recommending media courseware |
| US20160247072A1 (en) * | 2015-02-23 | 2016-08-25 | Jeremy Auger | Systems and methods for motivation-based course selection |
| US20170243312A1 (en) * | 2016-02-19 | 2017-08-24 | Teacher Match, Llc | System and method for professional development identification and recommendation |
| CN110362742A (en) * | 2019-06-18 | 2019-10-22 | 平安普惠企业管理有限公司 | Curriculum information matching process, device, computer equipment and storage medium |
| CN113919331A (en) * | 2021-10-14 | 2022-01-11 | 平安国际智慧城市科技股份有限公司 | Environmental training course recommendation method, device, equipment and storage medium |
-
2023
- 2023-01-10 CN CN202310030184.5A patent/CN115827987A/en active Pending
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102508846A (en) * | 2011-09-26 | 2012-06-20 | 深圳中兴网信科技有限公司 | Internet based method and system for recommending media courseware |
| US20160247072A1 (en) * | 2015-02-23 | 2016-08-25 | Jeremy Auger | Systems and methods for motivation-based course selection |
| US20170243312A1 (en) * | 2016-02-19 | 2017-08-24 | Teacher Match, Llc | System and method for professional development identification and recommendation |
| CN110362742A (en) * | 2019-06-18 | 2019-10-22 | 平安普惠企业管理有限公司 | Curriculum information matching process, device, computer equipment and storage medium |
| CN113919331A (en) * | 2021-10-14 | 2022-01-11 | 平安国际智慧城市科技股份有限公司 | Environmental training course recommendation method, device, equipment and storage medium |
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