CN115223075A - Management method, system, electronic device and medium based on wearable device - Google Patents
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Abstract
The application relates to a management method, a system, an electronic device and a storage medium of a wearable device, wherein the method comprises the following steps: creating a management task through a management platform, starting to collect a video when the wearable device receives the management task, inputting the collected target video into a trained AI model to detect the operation condition of the device and the behavior of personnel, inputting the generated detection result into an intelligent analysis system to obtain an analysis result, generating alarm information if the analysis result is abnormal, generating an alarm record when the management platform receives the alarm information, sending an alarm prompt, carrying out statistical analysis on the analysis result and the alarm information, and pushing the result after the statistical analysis to appointed personnel; the method and the system solve the problems that the management of equipment failure abnormity or personnel violation behaviors cannot be simultaneously carried out and the improvement of the production capacity and the safety of enterprises cannot be facilitated in the related technology.
Description
Technical Field
The present application relates to the field of wearable technologies, and in particular, to a management method and system, an electronic device, and a storage medium based on a wearable device.
Background
Currently, wearable devices, such as AR smart glasses or helmets, are currently being used in a variety of industry scenarios, including the industries of power, aviation, rail transit, transportation, fire fighting, infrastructure, semiconductors, and the like. However, the wearable device has the following disadvantages in terms of equipment inspection and personnel behavior management in an enterprise factory: on the one hand, current AR intelligence glasses or helmet not only can't discern judgement equipment trouble unusual or personnel act in violation of rules and regulations, when the unusual or personnel act in violation of rules and regulations of equipment trouble takes place, can't handle even, flexibility and timeliness are relatively poor, not only can't ensure the production safety of enterprise's mill, more can't help improving the productivity of enterprise, caused serious economic loss for the enterprise, on the other hand, correlation technique does not establish complete intelligent management system, can't trace back equipment trouble unusual or personnel act in violation of rules and regulations's inquiry and data.
Therefore, the above problems need to be solved.
Disclosure of Invention
The embodiment of the application provides a management method and system of wearable equipment, electronic equipment and a storage medium, so as to at least solve the problems that the equipment fault abnormality or the personnel violation cannot be managed simultaneously in correlation and the production capacity and the safety of an enterprise cannot be improved.
In a first aspect, an embodiment of the present application provides a method for managing a wearable device, where the method includes the following steps:
creating a management task through a management platform;
when the wearable device receives the management task, starting to acquire a video;
inputting the collected target video into a trained AI model to detect the equipment running condition and the personnel behavior, and inputting the generated detection result into an intelligent analysis system to obtain an analysis result;
if the analysis result is abnormal, generating alarm information; the target video is shot by the wearable equipment worn by the inspection personnel in the enterprise inspection process;
when the management platform receives the alarm information, an alarm record is generated, an alarm prompt is sent out, the analysis result and the alarm information are subjected to statistical analysis, and the result after the statistical analysis is pushed to appointed personnel.
In some embodiments, after inputting the acquired target video into the trained AI model to detect the device operation condition and the personnel behavior, the method further includes:
if the analysis result is not abnormal, generating a task result, and enabling the management platform to generate a task record based on the task result;
and when a task viewing instruction is received, displaying a task viewing interface, wherein the display content of the task viewing interface at least comprises task progress and task completion condition.
In some embodiments, when the management platform receives the alarm information, an alarm record is generated, and an alarm prompt is sent, the method further includes:
and displaying an alarm prompting interface through the management platform, and displaying alarm information when the alarm prompting interface receives a click instruction, wherein the alarm information at least comprises an alarm type, violation content and a recording file of the alarm occurrence moment.
In some embodiments, in a case where the wearable device has a camera, the generated detection result is input to an intelligent analysis system, and before obtaining the analysis result, the method further includes:
configuring a plurality of analysis rules for the intelligent analysis system; wherein, the analysis rules at least comprise equipment operation condition analysis rules and personnel behavior analysis rules.
In some embodiments, in the case where the wearable device has a microphone, after the start of capturing video when the wearable device receives the management task, the method further comprises:
collecting audio contents through the microphone, and converting the audio contents into character contents;
and combining the text content and the video, storing the combined file to the management platform, and detecting the equipment operation condition and the personnel behavior based on the combined file when the AI model receives the combined file.
In some embodiments, the inputting the acquired target video into the trained AI model to detect the device operation condition and the personnel behavior includes:
detecting the equipment operation condition in the target video through a built-in equipment algorithm, wherein the equipment at least comprises one or more of equipment with a chain, equipment with a transmission belt, equipment with a material port or a zipper machine;
and detecting the human violation behaviors in the target video through a built-in behavior algorithm, wherein the human violation behaviors at least comprise one or more of behaviors without wearing safety helmets, behaviors without wearing work clothes, behaviors without wearing protective clothes, smoking behaviors, calling behaviors, border crossing behaviors or sleeping behaviors.
In some embodiments, the detecting, by a built-in device algorithm, the device operation condition in the target video includes:
when the AI model detects that the equipment in the target video is a chain, determining a marking point when a belt on the chain normally conveys materials through a built-in chain algorithm corresponding to the chain; comparing the retention time of the belt on the chain passing through the marking point in the target video with a preset retention time to obtain a comparison result, and generating the detection result based on the comparison result; or,
when the AI model detects that the equipment in the target video is provided with a material port, determining the average height of material accumulation in the material port through a built-in material blocking algorithm corresponding to the material port, marking the upper limit value of the average height to obtain a marked height, comparing the actual height of material accumulation of the material port in the target video with the marked height to obtain a comparison result, and generating the detection result based on the comparison result.
In a second aspect, an embodiment of the present application provides a management system based on a wearable device, where the system includes:
the creating unit is used for creating a management task through the management platform;
the acquisition unit is used for starting to acquire a video when the wearable device receives the management task;
the detection unit is used for inputting the collected target video into the trained AI model to detect the equipment running condition and the personnel behavior;
the analysis unit is used for inputting the generated detection result into the intelligent analysis system to obtain an analysis result;
the alarm unit is used for generating alarm information if the analysis result is abnormal; the target video is shot by the wearable equipment worn by the inspection personnel in the enterprise inspection process; when the management platform receives the alarm information, generating an alarm record and sending an alarm prompt;
and the pushing unit is used for carrying out statistical analysis on the analysis result and the alarm information and pushing the result after the statistical analysis to appointed personnel.
In a third aspect, an embodiment of the present application provides an electronic device, including a memory, a processor, and a computer program stored on the memory and executable on the processor, where the processor, when executing the computer program, implements the management method of the wearable device according to the first aspect.
In a fourth aspect, embodiments of the present application provide a storage medium, on which a computer program is stored, where the computer program, when executed by a processor, implements the management method of a wearable device as described in the first aspect above.
Compared with the related art, in the technical scheme of the embodiment, the management task is created through the management platform, when the wearable device receives the management task, the video starts to be collected, the collected target video is input into a trained AI model to detect the running condition of the device and the behavior of personnel, and the generated detection result is input into the intelligent analysis system to obtain the analysis result; if the analysis result is abnormal, alarm information is generated, so that on-site inspection personnel can find abnormal information and can take corresponding measures in time, normal operation of enterprise production equipment is guaranteed, production efficiency is improved, potential safety hazards caused by worker's illegal behaviors can be avoided, safety is improved, when the management platform receives the alarm information, an alarm record is generated, an alarm prompt is sent out, the analysis result and the alarm information are subjected to statistical analysis, and the result after the statistical analysis is pushed to appointed personnel. Therefore, even if the device is not on site, the device fault abnormity and the personnel violation behaviors can be identified in the process of routing inspection of the enterprise factory equipment, the flexibility and the timeliness of management are improved, the economic loss caused by the device fault abnormity and the personnel violation behaviors is reduced, designated personnel can conveniently check at any time, the device fault abnormity or the personnel violation behaviors can be inquired and data can be traced, and the problems that the device fault abnormity or the personnel violation behaviors cannot be managed and the production capacity and the safety of an enterprise cannot be improved simultaneously in the related technology are solved.
Drawings
The accompanying drawings, which are included to provide a further understanding of the application and are incorporated in and constitute a part of this application, illustrate embodiment(s) of the application and together with the description serve to explain the application and not to limit the application. In the drawings:
fig. 1 is a first flowchart of a management method of a wearable device according to an embodiment of the present application;
fig. 2 is a second flowchart of a management method of a wearable device according to an embodiment of the present application;
fig. 3 is a block diagram of a wearable device based management system according to an embodiment of the application;
fig. 4 is an internal 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 present application more apparent, the present application will be described and illustrated below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the present application and are not intended to limit the present application. All other embodiments obtained by a person of ordinary skill in the art based on the embodiments provided in the present application without any inventive step are within the scope of protection of the present application. Moreover, it should be appreciated that in the development of any such actual implementation, as in any engineering or design project, numerous implementation-specific decisions must be made to achieve the developers' specific goals, such as compliance with system-related and business-related constraints, which may vary from one implementation to another.
Reference in the specification to "an embodiment" means that a particular feature, structure, or characteristic described in connection with the embodiment can be included in at least one embodiment of the specification. The appearances of the phrase in various places in the specification are not necessarily all referring to the same embodiment, nor are separate or alternative embodiments mutually exclusive of other embodiments. Those of ordinary skill in the art will explicitly and implicitly appreciate that the embodiments described herein may be combined with other embodiments without conflict.
Unless otherwise defined, technical or scientific terms referred to herein should have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs. Reference to "a," "an," "the," and similar words throughout this application are not to be construed as limiting in number, and may refer to the singular or the plural. The present application is directed to the use of the terms "including," "comprising," "having," and any variations thereof, which are intended to cover non-exclusive inclusions; for example, a process, method, system, article, or apparatus that comprises a list of steps or modules (elements) is not limited to the listed steps or elements, but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus. Reference to "connected," "coupled," and the like in this application is not intended to be limited to physical or mechanical connections, but may include electrical connections, whether direct or indirect. Reference herein to "a plurality" means greater than or equal to two. "and/or" describes an association relationship of associated objects, meaning that three relationships may exist, for example, "A and/or B" may mean: a exists alone, A and B exist simultaneously, and B exists alone. Reference herein to the terms "first," "second," "third," and the like, are merely to distinguish similar objects and do not denote a particular ordering for the objects.
Fig. 1 is a first flowchart of a management method of a wearable device according to an embodiment of the present invention, and as shown in fig. 1, in an embodiment of the present invention, the management method of a wearable device includes the following steps:
step S101, a management task is established through a management platform; of course, in other embodiments, the management task may also be created by the wearable device after logging in the wearable device; in addition, in this embodiment, before creating the management task through the management platform, the method further includes: logging in a management platform;
it should be noted that, in other embodiments, the management task may also be referred to as a create walking management task or others, and accordingly, the management platform may also be referred to as an intelligent AR walking management platform or others in other embodiments, which is not limited herein;
step S102, when the wearable device receives a management task, starting to collect a video; wherein, wearable equipment includes but is not limited to AR glasses, AR helmet or other wearable equipment, and wearable equipment of this embodiment adopts AR glasses to realize, and this AR glasses includes: the functions of the above components are known to those skilled in the art, and therefore, the details are not repeated here.
Step S103, inputting the collected target video into a trained AI model to detect the equipment running condition and the personnel behavior, and inputting the generated detection result into an intelligent analysis system to obtain an analysis result; therefore, the abnormal equipment fault and the illegal personnel behavior can be conveniently identified in the routing inspection process of the enterprise factory equipment.
It should be noted that, the AI model in this embodiment may be implemented by using an existing machine learning model or other neural network models, and it is easy to understand that the trained AI model is obtained when the loss corresponding to the existing machine learning model converges; for example, the training process may be: firstly, manually judging whether the acquired video has abnormal equipment faults or illegal personnel behaviors, labeling the video, inputting the labeled video into a machine learning model for training so as to iteratively enhance the identification and analysis capability of an intelligent analysis system, and obtaining a trained AI model until loss corresponding to the machine learning model is converged. In addition, those skilled in the art know that the intelligent analysis system may use the existing AI analysis algorithm or a software program to analyze the generated detection result and obtain an analysis result, and therefore, the details are not described herein.
Step S104, if the analysis result is abnormal, alarm information is generated; the alarm information may be alarm information of abnormal equipment failure or alarm information of illegal personnel behaviors, and is not specifically limited herein; in addition, when the alarm information is generated, the wearable device can prompt in a text or voice mode, so that on-site inspection personnel can find abnormal information and take corresponding measures in time, thereby not only ensuring the normal operation of enterprise production equipment and improving the production efficiency, but also avoiding potential safety hazards caused by illegal behaviors of workers and improving the safety; the target video is shot by wearable equipment worn by an inspector in the enterprise inspection process;
and S105, when the management platform receives the alarm information, generating an alarm record, sending an alarm prompt, carrying out statistical analysis on the analysis result and the alarm information, and pushing the result after the statistical analysis to appointed personnel. Therefore, even if the device is not on site, the device fault abnormity and the personnel violation behaviors can be identified in the process of routing inspection of the enterprise factory devices, the flexibility and the timeliness of management are improved, the economic loss caused by the device fault abnormity and the personnel violation behaviors is reduced, designated personnel can conveniently check at any time, and the device fault abnormity or the personnel violation behaviors can be inquired and traced back.
Through the steps S101 to S105, in the technical scheme of this embodiment, a management task is created through a management platform, when the wearable device receives the management task, a video starts to be acquired, the acquired target video is input into a trained AI model to detect the device operation condition and the personnel behavior, and a generated detection result is input into an intelligent analysis system to obtain an analysis result; if the analysis result is abnormal, alarm information is generated, so that on-site inspection personnel can find abnormal information and can take corresponding measures in time, normal operation of enterprise production equipment is guaranteed, production efficiency is improved, potential safety hazards caused by illegal behaviors of workers can be avoided, safety is improved, when the management platform receives the alarm information, an alarm record is generated, an alarm prompt is sent, the analysis result and the alarm information are subjected to statistical analysis, and the result after the statistical analysis is pushed to appointed personnel. Therefore, even if the device is not on site, the device fault abnormity and the personnel violation behaviors can be identified in the process of routing inspection of the enterprise factory equipment, the flexibility and the timeliness of management are improved, the economic loss caused by the device fault abnormity and the personnel violation behaviors is reduced, designated personnel can conveniently check at any time, the device fault abnormity or the personnel violation behaviors can be inquired and data can be traced, and the problems that the device fault abnormity or the personnel violation behaviors cannot be managed and the production capacity and the safety of an enterprise cannot be improved simultaneously in the related technology are solved.
Fig. 2 is a second flowchart of a management method of a wearable device according to an embodiment of the present application, as shown in fig. 2, in order to facilitate personnel to inspect enterprise plant equipment and manage personnel behaviors, in some embodiments, after inputting the acquired target video into the trained AI model to detect the equipment operation condition and the personnel behaviors, the method further includes the following steps:
if the analysis result is not abnormal, generating a task result, and enabling the management platform to generate a task record based on the task result;
and when receiving a task viewing instruction, displaying a task viewing interface, wherein the display content of the task viewing interface at least comprises task progress and task completion conditions. Thereby providing data support for user management decisions.
In order to conveniently implement scene reorganization of alarm, in an optional embodiment, when the management platform receives the alarm information, an alarm record is generated, and an alarm prompt is sent out, the method further includes the following steps:
and displaying an alarm prompting interface through the management platform, and displaying alarm information when the alarm prompting interface receives a click instruction, wherein the alarm information at least comprises an alarm type, violation content and a recording file of the alarm occurrence moment.
In order to improve the accuracy of the intelligent analysis system, in some embodiments, in the case that the wearable device has a camera, the generated detection result is input into the intelligent analysis system, and before obtaining the analysis result, the method further includes the following steps:
configuring a plurality of analysis rules for the intelligent analysis system; the analysis rules at least comprise equipment operation condition analysis rules and personnel behavior analysis rules. It is easy to understand that the intelligent analysis system can receive the generated detection result only after the intelligent analysis system configures a plurality of analysis rules, and obtains the corresponding analysis result based on each plurality of analysis rules; in addition, each analysis rule is set according to the actual requirement of the user, and is not specifically limited herein.
In an application scenario, in a process that an inspector wears the wearable device to walk in an indoor or outdoor scenario, the wearable device can acquire not only video content but also audio content, in order to improve a detection effect, in some embodiments, in a case that the wearable device has a microphone, when the wearable device receives a management task, and starts to acquire a video, the method further includes the following steps:
collecting audio contents through a microphone, and converting the audio contents into character contents;
and combining the text content and the video, storing the combined file to a management platform, and detecting the operation condition of equipment and the personnel behavior based on the combined file when the AI model receives the combined file.
In order to facilitate the detection of equipment fault abnormality and personnel violation, in some embodiments, the step of inputting the acquired target video into a trained AI model to detect the equipment operation condition and the personnel behavior includes the following steps:
detecting the equipment operation condition in the target video through a built-in equipment algorithm, wherein the equipment at least comprises one or more of equipment with a chain, equipment with a transmission belt, equipment with a material port or a zipper machine; of course, in other embodiments, the device may be other devices, and is not specifically limited herein, and the wearable device management method corresponding to the present application is within the protection scope of the present application.
And detecting the person violation behaviors in the target video through a built-in behavior algorithm, wherein the person violation behaviors at least comprise one or more of behaviors without wearing safety helmets, behaviors without wearing work clothes, behaviors without wearing protective clothes, smoking behaviors, calling behaviors, border crossing behaviors or sleeping behaviors. In other embodiments, the human violation behavior may be other behaviors, and is not specifically limited herein, that is, the management method of the wearable device corresponding to the present application is all within the protection scope of the present application.
It should be noted that both the built-in behavior algorithm and the built-in device algorithm may be implemented by existing software programs or algorithms, and the specific software programs or algorithms are not specifically limited herein.
In a preferred embodiment, the step of detecting the device operation condition in the target video through the built-in device algorithm comprises the following steps:
when the AI model detects that the equipment in the target video is a chain, determining a marking point when a belt on the chain normally conveys materials through a built-in chain algorithm corresponding to the chain; comparing the retention time of the belt on the chain passing through the marking point in the target video with the preset retention time to obtain a comparison result, and generating a detection result based on the comparison result; or,
when the fact that the material port of the equipment in the target video is provided with the material port is detected through the AI model, the average height of material accumulation in the material port is determined through a built-in material blocking algorithm corresponding to the material port, the upper limit value of the average height is marked to obtain a marked height, the actual height of material accumulation of the material port in the target video is compared with the marked height to obtain a comparison result, and a detection result is generated based on the comparison result.
In another preferred embodiment, inputting the collected target video into the trained AI model to detect the device operation condition and the personnel behavior further includes the following steps:
when the behavior of a person is detected through the AI model, whether the person in the video wears a safety helmet or not is determined through a built-in safety helmet detection algorithm, and a corresponding detection result is output; for example, the built-in safety helmet detection algorithm is used for labeling according to the size and shape of the safety helmet and in combination with human body shape, and whether the head part of the human body shape of the scene-collected video picture frame meets the marked safety helmet characteristic track or not is compared, so that the intelligent analysis system receives the detection result and reminds and informs related personnel of the system.
When the person in the video is determined to be calling through a built-in calling detection algorithm, outputting a corresponding detection result; for example, a built-in call detection algorithm is used for labeling according to the average size and shape of a mobile phone and combining with human body form, and whether the human body form of a field collected video picture frame and a mobile phone combining part accord with a marked call characteristic track or not is compared, so that an intelligent analysis system receives a detection result and reminds and informs related personnel of the system;
when the person in the video is determined to be not wearing the working clothes through a built-in algorithm of not wearing the working clothes, outputting a corresponding detection result;
when the person in the video is determined to be not wearing the protective clothing through a built-in algorithm of the protective clothing, outputting a corresponding detection result;
when the person in the video is determined to smoke through a built-in smoke detection algorithm, outputting a corresponding detection result;
and outputting a corresponding detection result when the sleeping behavior in the video is determined by the built-in sleeping post detection algorithm. Since the functions of the above-mentioned built-in helmet detection algorithm, built-in unworn work clothes algorithm, built-in smoking detection algorithm, and built-in phone call detection algorithm can be easily implemented by those skilled in the art through the existing software algorithms and programs, they are not described in detail herein.
It should be noted that the steps illustrated in the above-described flow diagrams or in the flow diagrams of the figures may be performed in a computer system, such as a set of computer-executable instructions, and that, although a logical order is illustrated in the flow diagrams, in some cases, the steps illustrated or described may be performed in an order different than here.
The embodiment also provides a management system based on the wearable device, and the system is used for implementing the above embodiments and preferred embodiments, and the description of the system is omitted. As used hereinafter, the terms "module," "unit," "subunit," and the like may implement a combination of software and/or hardware for a predetermined function. Although the means described in the embodiments below are preferably implemented in software, an implementation in hardware, or a combination of software and hardware is also possible and contemplated.
Fig. 3 is a block diagram of a wearable device-based management system according to an embodiment of the present application, and as shown in fig. 3, the system includes:
a creating unit 31 for creating a management task by the management platform;
the acquisition unit 32 is used for starting to acquire videos when the wearable device receives the management task;
the detection unit 33 is used for inputting the acquired target video into the trained AI model to detect the equipment running condition and the personnel behavior;
the analysis unit 34 is used for inputting the generated detection result into the intelligent analysis system to obtain an analysis result;
the alarm unit 35 is used for generating alarm information if the analysis result is abnormal; the target video is shot by wearable equipment worn by an inspector in the enterprise inspection process; when the management platform receives the alarm information, generating an alarm record and sending an alarm prompt;
and the pushing unit 36 is used for performing statistical analysis on the analysis result and the alarm information and pushing the result after the statistical analysis to the appointed personnel. The system establishes a management task through a management platform, starts to collect videos when wearable equipment receives the management task, inputs the collected target videos into a trained AI model to detect the running condition of the equipment and the behavior of personnel, and inputs the generated detection result into an intelligent analysis system to obtain an analysis result; if the analysis result is abnormal, alarm information is generated, so that on-site inspection personnel can find abnormal information and can take corresponding measures in time, normal operation of enterprise production equipment is guaranteed, production efficiency is improved, potential safety hazards caused by illegal behaviors of workers can be avoided, safety is improved, when the management platform receives the alarm information, an alarm record is generated, an alarm prompt is sent, the analysis result and the alarm information are subjected to statistical analysis, and the result after the statistical analysis is pushed to appointed personnel. Therefore, even if the device is not on site, the device fault abnormity and the personnel violation behaviors can be identified in the process of routing inspection of the enterprise factory equipment, the flexibility and the timeliness of management are improved, the economic loss caused by the device fault abnormity and the personnel violation behaviors is reduced, designated personnel can conveniently check at any time, the device fault abnormity or the personnel violation behaviors can be inquired and data can be traced, and the problems that the device fault abnormity or the personnel violation behaviors cannot be managed and the production capacity and the safety of an enterprise cannot be improved simultaneously in the related technology are solved.
The above modules may be functional modules or program modules, and may be implemented by software or hardware. For a module implemented by hardware, the modules may be located in the same processor; or the modules may be located in different processors in any combination.
The application further provides an electronic device, which includes a memory and a processor, where the memory stores a computer program, and the processor is configured to run the computer program to perform the management method of the wearable device.
Optionally, the electronic device may further include a transmission device and an input/output device, wherein the transmission device is connected to the processor, and the input/output device is connected to the processor.
Optionally, in this embodiment, the processor may be configured to execute the following steps by a computer program:
step S101, creating a management task through a management platform;
step S102, when the wearable device receives a management task, starting to collect a video;
step S103, inputting the collected target video into a trained AI model to detect the equipment running condition and the personnel behavior, and inputting the generated detection result into an intelligent analysis system to obtain an analysis result;
step S104, if the analysis result is abnormal, alarm information is generated; the target video is shot by wearable equipment worn by inspection personnel in the enterprise inspection process;
and S105, when the management platform receives the alarm information, generating an alarm record, sending an alarm prompt, carrying out statistical analysis on the analysis result and the alarm information, and pushing the result after the statistical analysis to appointed personnel.
It should be noted that, for specific examples in this embodiment, reference may be made to examples described in the foregoing embodiments and optional implementations, and details of this embodiment are not described herein again.
In addition, in combination with the management method of the wearable device in the foregoing embodiment, the embodiment of the present application may be implemented by providing a storage medium. The storage medium having stored thereon a computer program; the computer program, when executed by a processor, implements a method of managing a wearable device as in any of the above embodiments.
In one embodiment, a computer device is provided, which may be a terminal. The computer device includes a processor, a memory, a network interface, a display screen, and an input device connected by a system bus. Wherein the processor of the computer device is configured to provide computing and control capabilities. The memory of the computer device comprises a nonvolatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of an operating system and computer programs in the non-volatile storage medium. The network interface of the computer device is used for communicating with an external terminal through a network connection. The computer program is executed by a processor to implement a method of managing a wearable device. The display screen of the computer equipment can be a liquid crystal display screen or an electronic ink display screen, and the input device of the computer equipment can be a touch layer covered on the display screen, a key, a track ball or a touch pad arranged on a shell of the computer equipment, an external keyboard, a touch pad or a mouse and the like.
In one embodiment, fig. 4 is a schematic diagram of an internal structure of an electronic device according to an embodiment of the present application, and as shown in fig. 4, there is provided an electronic device, which may be a server, and its internal structure diagram may be as shown in fig. 4. The electronic device comprises a processor, a network interface, an internal memory and a non-volatile memory connected by an internal bus, wherein the non-volatile memory stores an operating system, a computer program and a database. The processor is used for providing calculation and control capabilities, the network interface is used for communicating with an external terminal through network connection, the internal memory is used for providing an environment for an operating system and running of a computer program, the computer program is executed by the processor to realize a management method of the wearable device, and the database is used for storing data.
Those skilled in the art will appreciate that the configuration shown in fig. 4 is a block diagram of only a portion of the configuration associated with the present application, and does not constitute a limitation on the electronic device to which the present application is applied, and a particular electronic device may include more or less components than those shown in the drawings, or combine certain components, or have a different arrangement of components.
It should be understood by those skilled in the art that various features of the above-described embodiments can be combined in any combination, and for the sake of brevity, all possible combinations of features in the above-described embodiments are not described in detail, but rather, all combinations of features which are not inconsistent with each other should be construed as being within the scope of the present disclosure.
The above-mentioned embodiments only express several embodiments of the present application, and the description thereof is specific and detailed, but not to be understood as limiting the scope of the invention. It should be noted that, for a person skilled in the art, several variations and modifications can be made without departing from the concept of the present application, which falls within the scope of protection of the present application. Therefore, the protection scope of the present patent shall be subject to the appended claims.
Claims (10)
1. A wearable device-based management method, the method comprising:
creating a management task through a management platform;
when the wearable device receives the management task, starting to acquire a video;
inputting the collected target video into a trained AI model to detect the equipment running condition and the personnel behavior, and inputting the generated detection result into an intelligent analysis system to obtain an analysis result;
if the analysis result is abnormal, generating alarm information; the target video is shot by the wearable equipment worn by the inspection personnel in the enterprise inspection process;
and when the management platform receives the alarm information, generating an alarm record, sending an alarm prompt, performing statistical analysis on the analysis result and the alarm information, and pushing the result after statistical analysis to appointed personnel.
2. The method of claim 1, wherein after inputting the collected target video into the trained AI model to detect the device operation and the human behavior, the method further comprises:
if the analysis result is not abnormal, generating a task result, and enabling the management platform to generate a task record based on the task result;
and when receiving a task viewing instruction, displaying a task viewing interface, wherein the display content of the task viewing interface at least comprises task progress and task completion conditions.
3. The method of claim 1, wherein when the management platform receives the alarm information, an alarm record is generated, and when an alarm prompt is issued, the method further comprises:
and displaying an alarm prompting interface through the management platform, and displaying alarm information when the alarm prompting interface receives a click instruction, wherein the alarm information at least comprises an alarm type, violation content and a recording file of the alarm occurrence moment.
4. The method according to claim 1, wherein in a case that the wearable device has a camera, the generated detection result is input into an intelligent analysis system, and before obtaining the analysis result, the method further comprises:
configuring a plurality of analysis rules for the intelligent analysis system; wherein, the analysis rules at least comprise equipment operation condition analysis rules and personnel behavior analysis rules.
5. The method of claim 1, wherein in a case where the wearable device has a microphone, after the wearable device starts capturing video when receiving the management task, the method further comprises:
collecting audio contents through the microphone, and converting the audio contents into character contents;
and combining the text content and the video, storing the combined file to the management platform, and detecting the equipment operation condition and the personnel behavior based on the combined file when the AI model receives the combined file.
6. The method of claim 1, wherein the inputting the collected target video into the trained AI model to detect the device operation and the human behavior comprises:
detecting the equipment operation condition in the target video through a built-in equipment algorithm, wherein the equipment at least comprises one or more of equipment with a chain, equipment with a transmission belt, equipment with a material port or a zipper machine;
and detecting the human violation behaviors in the target video through a built-in behavior algorithm, wherein the human violation behaviors at least comprise one or more of behaviors without wearing safety helmets, behaviors without wearing work clothes, behaviors without wearing protective clothes, smoking behaviors, calling behaviors, border crossing behaviors or sleeping behaviors.
7. The method of claim 6, wherein the detecting the device behavior in the target video through the built-in device algorithm comprises:
when the AI model detects that the equipment in the target video is a chain, determining a marking point when a belt on the chain normally conveys materials through a built-in chain algorithm corresponding to the chain; comparing the retention time of the belt on the chain passing through the marking point in the target video with a preset retention time to obtain a comparison result, and generating the detection result based on the comparison result; or,
when the AI model detects that the equipment in the target video is provided with a material port, determining the average height of material accumulation in the material port through a built-in material blocking algorithm corresponding to the material port, marking the upper limit value of the average height to obtain a marked height, comparing the actual height of material accumulation of the material port in the target video with the marked height to obtain a comparison result, and generating the detection result based on the comparison result.
8. A wearable device based management system, the system comprising:
the creating unit is used for creating a management task through the management platform;
the acquisition unit is used for starting to acquire a video when the wearable device receives the management task;
the detection unit is used for inputting the collected target video into the trained AI model to detect the equipment running condition and the personnel behavior;
the analysis unit is used for inputting the generated detection result into the intelligent analysis system to obtain an analysis result;
the alarm unit is used for generating alarm information if the analysis result is abnormal; the target video is shot by the wearable equipment worn by the inspection personnel in the enterprise inspection process; when the management platform receives the alarm information, generating an alarm record and sending an alarm prompt;
and the pushing unit is used for carrying out statistical analysis on the analysis result and the alarm information and pushing the result after the statistical analysis to appointed personnel.
9. An electronic device comprising a memory and a processor, wherein the memory has stored therein a computer program, and wherein the processor is configured to execute the computer program to perform the wearable device based management method of any of claims 1 to 7.
10. A storage medium having stored thereon a computer program, wherein the computer program is arranged to perform the wearable device based management method of any of claims 1-7 when executed.
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