Method and system for predicting dynamic risk

Abstract

A dynamic risk prediction method and system are disclosed. A dynamic risk prediction method according to one embodiment may include the step of predicting a dynamic risk level of a task using task information and outdoor environment information; and the step of providing the dynamic risk level of the task to a user terminal through a service platform.

Description

Technology Field

[0001] The following embodiments relate to a dynamic risk prediction method and system. Background Technology

[0003] Recently, an apartment building collapsed at a construction site. This is analyzed to be the result of forcibly carrying out concrete pouring in sub-zero temperatures without considering the risk factors, such as the delayed development of concrete strength due to low temperatures which could lead to structural collapse.

[0004] As various industrial accidents can occur when risk factors based on the type of work and outdoor environmental information such as weather and temperature are not taken into account, the Serious Accidents Punishment Act came into effect on January 27, 2022, and began to apply to companies with 50 or more employees.

[0005] According to the Serious Accidents Punishment Act, if one or more deaths occur at a site where five or more workers are working, if two or more injuries requiring treatment for six months or more occur as a result of the same accident, or if three or more cases of work-related diseases caused by the same risk factor occur within one year, the person in charge of management of the corporation or institution responsible for the work may be punished.

[0006] Therefore, there is a need to propose a technology that predicts the dynamic risk level of a task by considering the task's risk factors and outdoor environment information. The problem to be solved

[0008] The technical objective that the embodiments aim to achieve is to prevent industrial accidents and the punishment of management responsible under the Serious Accidents Punishment Act by providing a method and system that predicts the dynamic risk level of a work using work information corresponding to risk factors according to the type of work and outdoor environment information of the current work site, and provides this through a service platform.

[0009] In this case, one embodiment proposes a method and system that statistically aggregates and utilizes environmental values ​​that caused risk factors to improve prediction accuracy.

[0010] Here, one embodiment proposes a method and system that utilizes multiple environmental reference values ​​representing the degree of risk of an operation to predict the dynamic risk level of an operation into multiple levels.

[0011] In addition, some embodiments propose a method and system for visualizing and providing the dynamic risk level of a task on a service platform so that a manager or operator can intuitively recognize the dynamic risk level of the task.

[0012] In addition, one embodiment proposes a method and system that provides support information through a service platform to support training on a task based on the dynamic risk level of the task, or to support decision-making regarding whether to proceed with the task or scheduling.

[0013] In addition, one embodiment proposes a method and system that calculates a safety score for a task based on the work site conditions and the worker's equipment usage status, in addition to the dynamic risk class of the task, and provides it through a service platform.

[0014] At this time, one embodiment proposes a method and system for repeatedly updating and predicting the dynamic risk level of an operation by reflecting real-time changing outdoor environment information.

[0015] In addition, one embodiment proposes a method and system for storing and providing information on actions taken by workers and managers as dynamic risk levels of work are provided.

[0016] The technical problems that the embodiments aim to solve are not limited to those mentioned above, and other unmentioned technical problems will be clearly understood by those skilled in the art to which the embodiments belong from the description below. means of solving the problem

[0018] To achieve the above technical objective, a dynamic risk prediction method performed by a computer device according to one embodiment may include: a step of predicting a dynamic risk level of a task using task information and outdoor environment information; and a step of providing the dynamic risk level of the task through a service platform.

[0019] According to one aspect, the predicting step may be characterized by including: a step of identifying an environmental standard value corresponding to the task based on the task information; and a step of predicting a dynamic risk level of the task by comparing the environmental standard value with an environmental value included in the outdoor environmental information.

[0020] According to another aspect, the above environmental standard value may be characterized by being set based on risk factors according to the type of work.

[0021] According to another aspect, the above environmental standard value may be characterized by being set by statistically aggregating the environmental values ​​that caused the above risk factors.

[0022] According to another aspect, the environmental standard value is set as a plurality of values ​​representing the degree of risk of the operation, and the predicting step may be characterized as a step of predicting the dynamic risk level of the operation by comparing the environmental value with the plurality of environmental standard values.

[0023] According to another aspect, the step of providing the above may be characterized by providing a dynamic risk rating of the above operation by visualizing it on the service platform.

[0024] According to another aspect, the step of providing the above may further include the step of providing support information through the service platform that supports training for the said task or supports decision-making regarding whether to proceed with or schedule the said task, based on the dynamic risk level of the said task.

[0025] According to another aspect, the step of providing the above may further include: a step of calculating a safety score of the said work based on the dynamic risk level of the said work, the conditions of the work site of the said work, and the conditions of the equipment worn by at least one worker associated with the said work; and a step of providing the safety score of the said work through the service platform.

[0026] According to another aspect, the step of providing the above may further include the step of providing an alarm related to the dynamic risk level of the task to at least one worker's terminal and at least one manager's terminal related to the task.

[0027] According to another aspect, the predicting step may be characterized as a step of periodically predicting the dynamic risk level of the operation in response to the outdoor environment information being periodically updated at preset time intervals.

[0028] According to another aspect, the step of providing the above may further include the step of storing and providing the history of changes in the dynamic risk level of the periodically predicted task through the service platform.

[0029] According to another aspect, the step of storing and providing may be characterized by storing and providing information regarding measures taken by at least one worker and at least one manager related to the task as the dynamic risk level of the task is provided, along with the change history of the dynamic risk level.

[0030] According to one embodiment, in a computer-readable recording medium having a computer program for executing a dynamic risk prediction method on a computer device, the dynamic risk prediction method may include: a step of predicting a dynamic risk level of a task using task information and outdoor environment information; and a step of providing the dynamic risk level of the task through a service platform.

[0031] According to one embodiment, a computer device for performing a dynamic risk prediction method includes at least one processor configured to execute computer-readable instructions, and the at least one processor may include a prediction unit that predicts a dynamic risk level of a task using task information and outdoor environment information; and a providing unit that provides the dynamic risk level of the task through a service platform.

[0032] According to one aspect, the prediction unit may be characterized by identifying an environmental standard value corresponding to the task based on the task information, and predicting a dynamic risk level of the task by comparing the environmental standard value with an environmental value included in the outdoor environmental information. Effects of the invention

[0034] One embodiment proposes a method and system that predicts the dynamic risk level of a task using task information corresponding to risk factors according to the type of task and outdoor environment information of the current work site, and provides this through a service platform, thereby achieving a technical effect of preventing industrial accidents and preventing management personnel from being punished under the Serious Accidents Punishment Act.

[0035] In this case, some embodiments may propose a method and system that statistically aggregates and utilizes environmental values ​​that caused risk factors to improve prediction accuracy.

[0036] Here, one embodiment may propose a method and system that utilizes multiple environmental reference values ​​representing the degree of risk of an operation to predict the dynamic risk level of an operation into multiple levels.

[0037] In addition, some embodiments may propose a method and system for visualizing and providing the dynamic risk level of a task on a service platform so that a manager or operator can intuitively recognize the dynamic risk level of the task.

[0038] In addition, some embodiments may propose a method and system that provides support information through a service platform to support training on a task based on the dynamic risk level of the task, or to support decision-making regarding whether to proceed with the task or scheduling.

[0039] In addition, some embodiments may propose a method and system that calculates a safety score for a task based on the work site conditions and the worker's equipment wearing status, in addition to the dynamic risk class of the task, and provides it through a service platform.

[0040] At this time, one embodiment may propose a method and system for repeatedly updating and predicting the dynamic risk level of an operation by reflecting real-time changing outdoor environment information.

[0041] In addition, one embodiment may propose a method and system for storing and providing information on actions taken by workers and managers as dynamic risk levels of work are provided.

[0042] The technical effects described are not limited to those stated above and should be understood to include all effects that can be inferred from the composition of the invention described in the detailed description below or the claims. Brief explanation of the drawing

[0044] FIG. 1 is a drawing illustrating an example of a service environment according to one embodiment. FIG. 2 is a block diagram illustrating an example of a computer device according to one embodiment. FIG. 3 is a block diagram illustrating examples of components that may be included in the processor illustrated in FIG. 2. FIG. 4 is a conceptual diagram illustrating a dynamic risk prediction method that can be performed by the computer device shown in FIG. 2. FIG. 5 is a diagram illustrating a dynamic risk prediction method that can be performed by the computer device shown in FIG. 2. FIGS. 6a to 6d are screens of a terminal showing a service platform in which a dynamic risk rating of an operation is provided as the dynamic risk prediction method illustrated in FIG. 5 is performed. Specific details for implementing the invention

[0045] The present invention will be described below with reference to the attached drawings. However, the present invention may be implemented in various different forms and is therefore not limited to the embodiments described herein. Furthermore, in order to clearly explain the present invention in the drawings, parts unrelated to the explanation have been omitted, and similar parts throughout the specification have been given similar reference numerals.

[0046] Throughout the specification, when it is stated that a part is "connected (connected, in contact, combined)" with another part, this includes not only cases where they are "directly connected," but also cases where they are "indirectly connected" with other members interposed between them. Furthermore, when it is stated that a part "includes" a certain component, this means that, unless specifically stated otherwise, it does not exclude other components but rather allows for the inclusion of additional components.

[0047] The terms used herein are merely for describing specific embodiments and are not intended to limit the invention. Singular expressions include plural expressions unless the context clearly indicates otherwise. In this specification, terms such as “comprising” or “having” are intended to indicate the presence of the features, numbers, steps, actions, components, parts, or combinations thereof described in the specification, and should be understood as not precluding the existence or addition of one or more other features, numbers, steps, actions, components, parts, or combinations thereof.

[0048] In the following embodiments, a dynamic risk prediction method and system are described that predict the dynamic risk level of a task using task information and outdoor environment information and provide it through a service platform.

[0049] The service platform is implemented in the form of a dedicated program, application, or web page installed on a worker's terminal, a manager's terminal, or a server, and can operate as an interface that provides a dynamic risk level of a predicted task as a dynamic risk prediction method is performed.

[0050] The dynamic risk prediction method may be performed by a dynamic risk prediction system comprising at least one computer device including a processor, and the dynamic risk prediction system may be driven under the control of a computer program. The aforementioned computer program may be combined with the computer device and stored on a computer-readable recording medium to execute the dynamic risk prediction method on the computer device. The computer program described herein may take the form of an independent program package, or it may take the form of an independent program package already installed on the computer device and linked with an operating system or other program packages.

[0052] FIG. 1 is a drawing illustrating an example of a service environment according to one embodiment. The service environment of FIG. 1 illustrates an example including a plurality of electronic devices (110, 120, 130, 140), a plurality of servers (150, 160), and a network (170).

[0053] Figure 1 is an example for explaining the invention, and the number of electronic devices or servers is not limited to that shown in Figure 1. Furthermore, the service environment of Figure 1 is merely an example of one of the environments applicable to the embodiments, and the environments applicable to the embodiments are not limited to the service environment of Figure 1.

[0054] Multiple electronic devices (110, 120, 130, 140) may be fixed terminals or mobile terminals implemented as computer devices. Examples of multiple electronic devices (110, 120, 130, 140) include smartphones, mobile phones, navigation systems, computers, laptops, digital broadcasting terminals, PDAs (Personal Digital Assistants), PMPs (Portable Multimedia Players), tablet PCs, etc. For example, FIG. 1 shows the form of a smartphone as an example of an electronic device (110), but in the embodiments, the electronic device (110) may refer to one of various physical computer devices capable of communicating with other electronic devices (120, 130, 140) and / or servers (150, 160) via a network (170) using a wireless or wired communication method.

[0055] Here, the electronic devices (110, 120, 130, 140) may refer to a worker's terminal or a manager's terminal. For example, the electronic devices (110, 120, 130, 140) may refer to a manager's terminal that manages the site of work.

[0056] The method of communication between electronic devices (110, 120, 130, 140) and servers (150, 160) is not limited and may include not only communication methods utilizing communication networks (e.g., mobile communication networks, wired internet, wireless internet, broadcasting networks) that the network (170) may include, but also short-range wireless communication between devices. For example, the network (170) may include any one or more networks such as a PAN (personal area network), LAN (local area network), CAN (campus area network), MAN (metropolitan area network), WAN (wide area network), BBN (broadband network), and the Internet. Additionally, the network (170) may include any one or more network topologies such as a bus network, star network, ring network, mesh network, star-bus network, tree or hierarchical network, but is not limited thereto.

[0057] Each of the servers (150, 160) may be implemented as a computer device or multiple computer devices that communicate with multiple electronic devices (110, 120, 130, 140) through a network (170) to provide commands, code, files, content, services, etc. For example, the server (150) may be a system that implements a dynamic risk prediction method that provides a dynamic risk level of an operation through a service platform installed and operated on multiple electronic devices (110, 120, 130, 140) connected through the network (170).

[0059] FIG. 2 is a block diagram illustrating an example of a computer device according to one embodiment. Each of the plurality of electronic devices (110, 120, 130, 140) or servers (150, 160) described above can be implemented by the computer device (200) illustrated in FIG. 2.

[0060] As illustrated in FIG. 2, such a computer device (200) may include memory (210), a processor (220), a communication interface (230), and an input / output interface (240). The memory (210) is a computer-readable recording medium and may include a non-perishable mass storage device such as RAM (random access memory), ROM (read only memory), and a disk drive. Here, a non-perishable mass storage device such as a ROM and a disk drive may be included in the computer device (200) as a separate permanent storage device distinct from the memory (210). Additionally, an operating system and at least one program code may be stored in the memory (210). These software components may be loaded into the memory (210) from a computer-readable recording medium separate from the memory (210). This separate computer-readable recording medium may include a computer-readable recording medium such as a floppy drive, a disk, a tape, a DVD / CD-ROM drive, or a memory card. In another embodiment, software components may be loaded into memory (210) via a communication interface (230) rather than a computer-readable recording medium. For example, software components may be loaded into memory (210) of a computer device (200) based on a computer program installed by files received through a network (170).

[0061] The processor (220) may be configured to process instructions of a computer program by performing basic arithmetic, logic, and input / output operations. Instructions may be provided to the processor (220) via memory (210) or a communication interface (230). For example, the processor (220) may be configured to execute instructions received according to program code stored in a recording device such as memory (210).

[0062] The communication interface (230) may provide a function for the computer device (200) to communicate with other devices (e.g., storage devices described above) through the network (170). For example, requests, commands, data, files, etc. generated by the processor (220) of the computer device (200) according to program code stored in a recording device such as memory (210) may be transmitted to other devices through the network (170) under the control of the communication interface (230). Conversely, signals, commands, data, files, etc. from other devices may be received by the computer device (200) through the communication interface (230) of the computer device (200) via the network (170). Signals, commands, data, etc. received through the communication interface (230) may be transmitted to the processor (220) or memory (210), and files, etc. may be stored in a storage medium (the permanent storage device described above) that the computer device (200) may further include.

[0063] The input / output interface (240) may be a means for interfacing with an input / output device (250). For example, the input device may include a device such as a microphone, keyboard, or mouse, and the output device may include a device such as a display or speaker. As another example, the input / output interface (240) may be a means for interfacing with a device in which the functions for input and output are integrated into one, such as a touchscreen. The input / output device (250) may be composed of a computer device (200) and a single device.

[0064] Additionally, in other embodiments, the computer device (200) may include fewer or more components than the components of FIG. 2. However, it is not necessary to clearly illustrate most of the prior art components. For example, the computer device (200) may be implemented to include at least some of the input / output devices (250) described above, or may include other components such as a transceiver, a database, etc.

[0065] Specific embodiments of the dynamic risk prediction method, system, and service platform will be described below.

[0067] FIG. 3 is a block diagram illustrating examples of components that may be included in the processor shown in FIG. 2, FIG. 4 is a conceptual diagram for explaining a dynamic risk prediction method that can be performed by the computer device shown in FIG. 2, FIG. 5 is a diagram illustrating a dynamic risk prediction method that can be performed by the computer device shown in FIG. 2, and FIG. 6a to 6d are screens of a terminal showing a service platform in which a dynamic risk rating of an operation is provided as the dynamic risk prediction method shown in FIG. 5 is performed.

[0068] In embodiments of the present invention, the computer device (200) can predict the dynamic risk level of an operation by performing a dynamic risk prediction method and provide it through a service platform, which is a dedicated program, application, or web page installed on electronic devices (110, 120, 130, 140). To this end, the computer device (200) may be configured with a dynamic risk prediction system that is the entity performing the dynamic risk prediction method. For example, the dynamic risk prediction system may be implemented in the form of a program that operates independently, or configured as an in-app of a dedicated application so that it can operate on the dedicated application.

[0069] The processor (220) of the computer device (200) may be implemented as a component for performing the dynamic risk prediction method according to FIGS. 4 and 5. For example, the processor (220) may include a prediction unit (310) and a providing unit (320) as shown in FIG. 3 so as to be able to perform the steps (S510 to S520) shown in FIG. 5. Depending on the embodiment, the components of the processor (220) may optionally be included in or excluded from the processor (220). Additionally, depending on the embodiment, the components of the processor (220) may be separated or merged to represent the function of the processor (220).

[0070] These processors (220) and components of the processor (220) can control a computer device (200) to perform steps (S510 to S520) included in the dynamic risk prediction method of FIG. 5. For example, the processor (220) and components of the processor (220) may be implemented to execute instructions according to the code of an operating system included in memory (210) and the code of at least one program.

[0071] Here, the components of the processor (220) may be representations of different functions performed by the processor (220) according to instructions provided by program code stored in the computer device (200). For example, a providing unit (320) may be used as a functional representation of the processor (220) that controls the computer device (200) to provide a dynamic risk level of a task through a service platform.

[0072] The processor (220) can read necessary commands from memory (210) in which commands related to the control of the computer device (200) are loaded. In this case, the read commands may include commands to control the processor (220) to execute steps (S510 to S520) to be described later.

[0073] The steps (S510 to S520) to be described later may be performed in a different order than the order shown in FIG. 5, and some of the steps (S510 to S520) may be omitted or additional processes may be included.

[0074] Prior to step (S510), the processor (220) (more precisely, the prediction unit (310) included in the processor (220)) can acquire, collect, and receive work information and outdoor environment information to be utilized in step (S510). For example, prior to step (S510), the processor (220) (more precisely, the prediction unit (310) included in the processor (220)) can acquire, collect, and receive outdoor environment information of a region corresponding to the work site from at least one weather sensor installed at the work site or a weather agency server. As another example, prior to step (S510), the processor (220) (more precisely, the prediction unit (310) included in the processor (220)) can acquire, collect, and receive information regarding the type, content, etc. of work input by at least one worker or manager through a service platform as work information.

[0075] In step (S510), the processor (220) (more precisely, the prediction unit (310) included in the processor (220)) can predict the dynamic risk level of the work using work information and outdoor environment information.

[0076] More specifically, in step (S510), the processor (220) (more precisely, the prediction unit (310) included in the processor (220)) can predict the dynamic risk level of the work by checking the environmental reference value corresponding to the work based on the work information and comparing the environmental reference value with the environmental value included in the outdoor environmental information.

[0077] At this time, the environmental standard value may be set based on risk factors according to the type of work. Hereinafter, the risk factors of the work refer to risks that may occur due to weather conditions such as precipitation, snowfall, wind speed, and temperature indicated by outdoor environmental information. For example, in the case of detailed work related to the assembly and dismantling of a tower crane during construction work, the risk factor may be "collapse of the tower crane due to gusts." Accordingly, based on the risk factor of "collapse of the tower crane due to gusts," the environmental standard value for detailed work related to the assembly and dismantling of the tower crane may be set to "wind speed 7 m / s."

[0078] As such, environmental standard values ​​are set based on risk factors, and these values ​​can be set by statistically aggregating the environmental values ​​that caused the risk factors. For example, if the wind speeds that caused the risk factor of "tower crane collapse due to gusts" are aggregated as 7 m / s, 8 m / s, and 6 m / s, the environmental standard value for detailed work related to tower crane assembly and dismantling can be set to "7 m / s," which is the result of statistically aggregating the wind speeds of 7 m / s, 8 m / s, and 6 m / s.

[0079] Additionally, the environmental standard values ​​can be set to multiple values ​​representing the degree of risk of the work. Accordingly, in step (S510), the processor (220) (more precisely, the prediction unit (310) included in the processor (220)) can predict the dynamic risk level of the work by comparing the environmental values ​​included in the outdoor environment information with the multiple environmental standard values. For example, when a first environmental standard value and a second environmental standard value are set as environmental standard values, in step (S510), the processor (220) (more precisely, the prediction unit (310) included in the processor (220)) compares the environmental value included in the outdoor environmental information with the first environmental standard value and the second environmental standard value, so that if the environmental value included in the outdoor environmental information is less than the first environmental standard value, the dynamic risk level of the work can be predicted as a caution level, if the environmental value included in the outdoor environmental information is greater than or equal to the first environmental standard value and less than the second environmental standard value, the dynamic risk level of the work can be predicted as a warning level, and if the environmental value included in the outdoor environmental information is greater than or equal to the second environmental standard value, the dynamic risk level of the work can be predicted as a severe level.

[0080] Although the above description explains that the multiple environmental standard values ​​are multiple values ​​representing the degree of risk of work for the same type of environment (e.g., wind speed), they are not limited to or restricted thereto and may also be multiple values ​​representing the degree of risk of work for different types of environments (e.g., rain or wind speed). For example, the first environmental standard value may be a value indicating whether it is raining, and the second environmental standard value may be a value related to wind speed. For a more specific example, if a first environmental standard value indicating whether it is raining, a second environmental standard value related to wind speed, and a third environmental standard value are set as environmental standard values, in step (S510), the processor (220) (more precisely, the prediction unit (310) included in the processor (220)) compares the environmental value included in the outdoor environmental information with the first environmental standard value, the second environmental standard value, and the third environmental standard value, so that if the environmental value included in the outdoor environmental information corresponds to the first environmental standard value (value indicating raining), the dynamic risk level of the work can be predicted as a caution level; if the environmental value included in the outdoor environmental information is greater than or equal to the second environmental standard value, the dynamic risk level of the work can be predicted as a warning level; and if the environmental value included in the outdoor environmental information is greater than or equal to the third environmental standard value, the dynamic risk level of the work can be predicted as a severe level.

[0081] In step (S520), the processor (220) (more precisely, the providing unit (320) included in the processor (220)) can provide the dynamic risk level of the operation through the service platform.

[0082] Hereinafter, providing the dynamic risk level of a task through a service platform may not be limited to displaying the dynamic risk level of the task on the service platform, but may also include providing an alarm related to the dynamic risk level of the task to at least one worker's terminal and at least one manager's terminal related to the task. In such cases, the alarm may also be provided through a service platform running on the terminal. However, it is not limited to or restricted thereto.

[0083] At this time, the processor (220) (more precisely, the providing unit (320) included in the processor (220)) can provide a visualized dynamic risk level of the work on the service platform, thereby enabling an administrator or worker using the service platform to intuitively recognize the operational risk level of the work.

[0084] Additionally, in step (S520), the processor (220) (more precisely, the providing unit (320) included in the processor (220)) may generate support information that supports training for the work or decision-making regarding whether to proceed with the work or scheduling, based on the dynamic risk level of the work, and then provide it through the service platform. For example, if the environmental value included in the outdoor environmental information is greater than or equal to the third environmental standard value (wind speed 8 m / s) and the dynamic risk level of the work is predicted to be severe, the processor (220) (more precisely, the providing unit (320) included in the processor (220)) may generate support information (work stoppage request, recommendation, or command) that supports decision-making regarding work stoppage based on the severe dynamic risk level, and then provide it through the service platform.

[0085] Additionally, in step (S520), the processor (220) (more precisely, the providing unit (320) included in the processor (220)) may provide the calculated safety score of the work through a service platform by calculating the safety score of the work based on the dynamic risk level of the work, the situation at the work site of the work, and the situation of wearing equipment of at least one worker related to the work.

[0086] The described steps (S510 to S520) may be performed repeatedly at preset time intervals to reflect outdoor environment information that changes in real time. More specifically, in step (S510), the processor (220) (more precisely, the prediction unit (310) included in the processor (220)) may periodically predict the dynamic risk level of the task in response to the outdoor environment information being periodically updated at preset time intervals. Accordingly, in step (S520), the processor (220) (more precisely, the providing unit (320) included in the processor (220)) may periodically update and provide the dynamic risk level of the task that is periodically predicted through a service platform. That is, in step (S520), the processor (220) (more precisely, the providing unit (320) included in the processor (220)) may store and provide the change history of the dynamic risk level of the task that is periodically predicted through a service platform.

[0087] Along with the change history of the dynamic risk level being stored and provided through the service platform, information regarding actions taken by at least one worker and at least one manager as the dynamic risk level of the task is provided can also be stored and provided through the service platform.

[0089] As the dynamic risk prediction method described above is performed, the service platform can display work-related information as illustrated in FIGS. 6a to 6d. For example, the service platform displays information about the site of a specific work on the main screen as illustrated in FIG. 6a, and as the aforementioned dynamic risk prediction method is performed, it can provide and display the dynamic risk level of the work through the service platform as illustrated in FIGS. 6b, 6c, or 6d.

[0091] The device described above may be implemented as a hardware component, a software component, and / or a combination of a hardware component and a software component. For example, the device and components described in the embodiments may be implemented using one or more general-purpose or special-purpose computers, such as a processor, a controller, an arithmetic logic unit (ALU), a digital signal processor, a microcomputer, a field programmable gate array (FPGA), a programmable logic unit (PLU), a microprocessor, or any other device capable of executing and responding to instructions. The processing unit may execute an operating system (OS) and one or more software applications executed on said operating system. Additionally, the processing unit may access, store, manipulate, process, and generate data in response to the execution of the software. For ease of understanding, the processing unit may be described as being used as a single unit, but those skilled in the art will understand that the processing unit may include multiple processing elements and / or multiple types of processing elements. For example, the processing unit may include multiple processors or one processor and one controller. In addition, other processing configurations, such as parallel processors, are also possible.

[0092] Software may include computer programs, code, instructions, or a combination of one or more of these, and may configure a processing unit to operate as desired or instruct the processing unit independently or collectively. Software and / or data may be embodied in any type of machine, component, physical device, computer storage medium, or device so as to be interpreted by the processing unit or to provide instructions or data to the processing unit. Software may be distributed over networked computer systems and may be stored or executed in a distributed manner. Software and data may be stored on one or more computer-readable recording media.

[0093] The method according to the embodiment may be implemented in the form of program instructions that can be executed through various computer means and recorded on a computer-readable medium. In this case, the medium may continuously store a program executable by a computer, or temporarily store it for execution or download. Additionally, the medium may be various recording or storage means in the form of a single or several hardware combined, and may not be limited to a medium directly connected to a computer system but may exist distributed over a network. Examples of media may include magnetic media such as hard disks, floppy disks, and magnetic tapes; optical recording media such as CD-ROMs and DVDs; magneto-optical media such as floptical disks; and media configured to store program instructions, including ROM, RAM, and flash memory. Additionally, other examples of media may include recording or storage media managed by app stores that distribute applications or sites and servers that supply or distribute various other software.

[0094] In addition, the service platform according to the present invention can predict individual dynamic risks for one or more work / construction sites (domestic and overseas), while simultaneously presenting integrated prediction work and corresponding response guides. More specifically, according to an example of the present invention, the head office or a manager, etc., can check in real-time details regarding dynamic risk predictions for multiple sites being conducted in domestic and overseas regions through the service platform according to the present invention, and may further include a step of relatively comparing and analyzing work-related environmental standards, regulatory compliance, or risk factors for each site (this can be performed in parallel with or sequentially thereafter with the step of predicting dynamic risks according to the present invention).

[0095] In addition, the service platform according to the present invention can perform a dynamic risk prediction method by comparing and analyzing data monitored in real time through various environmental sensors installed at each site (e.g., sensors measuring temperature, wind speed, work altitude, humidity, air quality, etc.) with pre-set environmental standard values. Along with this, the service platform according to the present invention may support improving the accuracy of dynamic risks or responding preemptively by performing a dynamic risk prediction method based on the location of each site and the altitude (height) of major work sites, predicting past and / or current weather information and weather information for a set period (using techniques such as Random Forest or receiving weather prediction information through an external API), and comparing and analyzing this prediction information with pre-set environmental standard values. In the case of such real-time and / or prediction-based dynamic risk prediction, it is possible to support faster response, prevention of disasters and accidents, and compliance with environmental standards by providing / instructing response instructions for each work site and / or at the corporate level—such as at the headquarters—simultaneously setting up and responding to multiple work sites located in specific regions through the service platform according to the present invention via the terminals of field workers.

[0096] Although the embodiments have been described above with reference to limited examples and drawings, those skilled in the art can make various modifications and variations from the description above. For example, suitable results can be achieved even if the described techniques are performed in a different order than described, and / or the components of the described system, structure, device, circuit, etc. are combined or assembled in a form different from described, or replaced or substituted by other components or equivalents.

[0097] Therefore, other implementations, other embodiments, and equivalents to the claims also fall within the scope of the claims set forth below.

[0098] The foregoing description of the present invention is for illustrative purposes only, and those skilled in the art will understand that other specific forms can be easily modified without altering the technical spirit or essential features of the present invention. Therefore, the embodiments described above should be understood as illustrative in all respects and not restrictive. For example, each component described as a single unit may be implemented in a distributed manner, and components described as distributed may likewise be implemented in a combined form.

[0099] The scope of the present invention is defined by the claims set forth below, and all modifications or variations derived from the meaning and scope of the claims and equivalent concepts thereof should be interpreted as being included within the scope of the present invention.

Claims

Claim 1 A dynamic risk prediction method performed by a computer device comprises: a step of predicting a dynamic risk level of a task using task information and outdoor environment information; and a step of providing the dynamic risk level of the task through a service platform, wherein the predicting step comprises: a step of identifying an environmental reference value corresponding to the task based on the task information; and a step of predicting a dynamic risk level of the task by comparing an environmental value included in the outdoor environment information with the environmental reference value, and wherein the environmental reference value is It is established based on risk factors according to the type of the above-mentioned work, and It is characterized by being set with a plurality of values ​​representing the degree of risk of the above-mentioned work, and composed of a plurality of standard values ​​representing the degree of risk of work corresponding to the same type of environment or different types of environments. The above risk factors are, It is characterized by including risk details that may occur due to the above outdoor environment information, and The above-mentioned predicting step is characterized by multi-stage predicting the dynamic risk level of the work into caution, alert, and severe by comparing the environmental value with the plurality of environmental standard values, and the above-mentioned service platform is characterized by controlling the step of predicting the dynamic risk level based on outdoor environmental information or external weather forecast information collected through a plurality of environmental sensors installed at each work site. Based on the predicted risk rating results for multiple work sites, The step of comparing and analyzing risk levels among the multiple work sites by providing environmental standard values, regulatory compliance items, and risk factors set for each work site separately on the service platform is performed in parallel with or subsequently to the step of predicting dynamic risk grades. Based on the predicted risk rating results above, A dynamic risk prediction method characterized by generating and providing individual response guides or integrated instructions for each work site. Claim 2 delete Claim 3 delete Claim 4 A dynamic risk prediction method according to claim 1, characterized in that the environmental standard value is set by statistically aggregating the environmental values ​​that caused the risk factor. Claim 5 delete Claim 6 A dynamic risk prediction method according to claim 1, characterized in that the step of providing is a step of visualizing and providing the dynamic risk rating of the operation on the service platform. Claim 7 A dynamic risk prediction method according to claim 1, wherein the step of providing further comprises the step of providing support information through the service platform that supports training for the task or supports decision-making regarding whether to proceed with or schedule the task based on the dynamic risk level of the task. Claim 8 A dynamic risk prediction method according to claim 1, wherein the step of providing further comprises: a step of calculating a safety score of said work based on a dynamic risk grade of said work, a work site condition of said work, and a condition of wearing equipment of at least one worker related to said work; and a step of providing the safety score of said work through said service platform. Claim 9 A dynamic risk prediction method according to claim 1, wherein the step of providing further comprises the step of providing an alarm related to the dynamic risk level of the task to at least one worker's terminal and at least one manager's terminal related to the task. Claim 10 A dynamic risk prediction method according to claim 1, wherein the predicting step is a step of periodically predicting the dynamic risk level of the operation in response to the outdoor environment information being periodically updated at preset time intervals. Claim 11 A dynamic risk prediction method according to claim 10, wherein the step of providing further includes the step of storing and providing the history of changes in the dynamic risk level of the periodically predicted task through the service platform. Claim 12 A dynamic risk prediction method according to claim 11, wherein the step of storing and providing is a step of storing and providing information on measures taken by at least one worker and at least one manager related to the work as the dynamic risk level of the work is provided, along with the change history of the dynamic risk level. Claim 13 delete Claim 14 delete Claim 15 delete

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