KR102607503B1 - Dynamic safety range setting method and system according to the characteristics and environment of mobile IoT - Google Patents

Abstract

A method and system for setting a dynamic safety range to prevent accidents in a system that controls the risk of collision of mobile IoT devices attached to IoT devices is provided. A dynamic safety range setting system according to an embodiment of the present invention includes a communication unit that collects location information from one or more mobile IoT devices; A storage unit that stores each collected location information separately by mobile IoT device; Inferring the movement characteristics of the mobile IoT device based on real-time location information for a specific mobile IoT device and historical data of location information stored for a certain period of time, and setting the safety range of the mobile IoT device based on the inference results of the movement characteristics It includes a processor that does. As a result, the system that controls the risk of collision of mobile IoT devices attached to IoT devices can dynamically change the width of the safety range by reflecting external environmental information and the object movement characteristics of the mobile IoT device in real time, more effectively preventing safety accidents. can be prevented.

Description

Dynamic safety range setting method and system according to the characteristics and environment of mobile IoT}

The present invention relates to a system that controls the risk of collision of mobile IoT devices attached to IoT devices. More specifically, the system controls the risk of collision of mobile IoT devices attached to IoT devices by providing a dynamic safety range to prevent accidents. It relates to setting methods and systems.

In large industrial sites such as shipyards and ports, technologies have been developed to identify real-time location information and movement paths of widely distributed equipment, or to monitor the movement status of equipment based on location information and movement speed of equipment.

However, these conventional technologies only monitor the current movement status of equipment by collecting GPS data, determine whether a mobile IoT device exists in a specific fixed area, detect collisions using physical sensor information, or detect movement patterns. As a method of determining collisions using the abnormality detection results, there is a limitation in that it cannot prevent possible collisions by reflecting the safety distances of all detectable mobile IoT devices.

The present invention was created to solve the above problems, and the purpose of the present invention is to provide real-time external environmental information and object movement characteristics of the mobile IoT device in a system that controls the risk of collision of mobile IoT devices attached to IoT devices. The aim is to provide a dynamic safety range setting method and system that can dynamically change the width of the safety range by reflecting the

In order to achieve the above object, a dynamic safety range setting system according to an embodiment of the present invention includes a communication unit that collects location information from one or more mobile IoT devices; A storage unit that stores each collected location information separately by mobile IoT device; Inferring the movement characteristics of the mobile IoT device based on real-time location information for a specific mobile IoT device and historical data of location information stored for a certain period of time, and setting the safety range of the mobile IoT device based on the inference results of the movement characteristics It includes a processor that does.

The storage unit may include a time series data DB in which location information of one or more mobile IoT devices is stored and an external environment data DB in which information about the external environment is stored.

Additionally, the processor includes a data management module that manages data stored in a time series data DB and an external environment data DB; A moving object motion inferrator that infers the motion characteristics of a mobile IoT device based on location information about a specific mobile IoT device and historical data of location information stored for a certain period of time; and a device safety range setter that sets the safety range of the mobile IoT device based on the inference results of the motion characteristics.

And, when the location information of a specific mobile IoT device for a preset period is accumulated in the time series data DB, the data management module generates location history data for the preset period based on the accumulated location information and stores it in the time series data DB. , The mobile object motion inference unit can infer the motion characteristics of the mobile IoT device based on the location information of the specific mobile IoT device collected through the communication unit and the location history data of the specific mobile IoT device stored in the time series data DB.

Additionally, the device safety range setter can set the safety range based on movement speed, direction information, and external environment information.

And, when setting the safety range, the device safety range setter is a first point that is spaced apart by the set value (n) of the preset safety range along the movement direction from the current location of the mobile IoT device, and is inclined 30° in the direction of movement. A second point spaced apart by 3/4 of the set value (n) of the preset safety range in the direction, a distance of 2/4 of the set value (n) of the preset safety range in the direction inclined 60° from the direction of movement. A safety range can be set with a third point spaced apart and a fourth point spaced apart at a distance equal to 1/4 of the set value (n) of the preset safety range in a direction inclined at 90° from the direction of movement as the border.

In addition, the device safety range setter sets the safety range setting value according to the moving speed of the mobile IoT device so that the relatively faster moving speed sets the safety range setting value (n) larger, but does not depend on external environmental information. If an obstacle exists in the movement path by analyzing the included terrain information, the set value (n) of the safety range can be set relatively lower than when there is no obstacle.

The processor may further include a real-time data processing engine module that calculates the collision risk of two mobile IoT devices by calculating the overlapping area between the safety ranges of different mobile IoT devices at the same time.

In addition, the real-time data processing engine module can crawl and reconstruct the current location of each mobile IoT device and points on the border of the safety range at preset intervals.

Meanwhile, according to another embodiment of the present invention, a dynamic safety range setting method includes: a system collecting location information from one or more mobile IoT devices; The system stores each collected location information separately by mobile IoT device; Inferring, by the system, the movement characteristics of a mobile IoT device based on location information about a specific mobile IoT device and historical data of location information stored for a certain period of time; And a step of the system setting a safety range of the mobile IoT device based on the inference result of the movement characteristics.

And according to another embodiment of the present invention, the dynamic safety range setting system is a moving object motion function that infers the motion characteristics of the mobile IoT device based on the location information for a specific mobile IoT device and the history data of the location information stored for a certain period of time. feature inferencer; And a device safety range setter that sets the safety range of the mobile IoT device based on the inference results of the motion characteristics.

In addition, in the dynamic safety range setting method according to another embodiment of the present invention, the system infers the movement characteristics of the mobile IoT device based on location information for a specific mobile IoT device and history data of the location information stored for a certain period of time. steps; And a step of the system setting a safety range of the mobile IoT device based on the inference result of the movement characteristics.

As described above, according to embodiments of the present invention, the system for controlling the risk of collision of a mobile IoT device attached to an IoT device reflects the external environment information and the object movement characteristics of the mobile IoT device in real time to determine the width of the safety range. can be changed dynamically, preventing safety accidents more effectively.

1 is a diagram provided to explain the configuration of a dynamic safety range setting system according to the characteristics and environment of mobile IoT according to an embodiment of the present invention;
Figure 2 is a diagram provided for a more detailed configuration explanation of the processor shown in Figure 1;
Figure 3 is a diagram provided to explain the operation characteristics of a dynamic safety range setting system according to the characteristics and environment of mobile IoT according to an embodiment of the present invention;
Figure 4 is a diagram illustrating a safety range set according to an embodiment of the present invention;
Figure 5 is a diagram illustrating some of the safety ranges of different mobile IoT devices at the same time overlapping according to an embodiment of the present invention, and
Figure 6 is a flowchart provided to explain a method for setting a dynamic safety range according to the characteristics and environment of mobile IoT according to an embodiment of the present invention.

Hereinafter, the present invention will be described in more detail with reference to the drawings.

Figure 1 is a diagram provided to explain the configuration of a dynamic safety range setting system according to the characteristics and environment of mobile IoT according to an embodiment of the present invention.

Referring to FIG. 1, the dynamic safety range setting system according to the characteristics and environment of mobile IoT (hereinafter collectively referred to as the 'dynamic safety range setting system') includes a communication unit 100, a processor 200, and a storage unit ( 300).

The communication unit 100 is a communication means for connecting the system to the outside through a communication network.

For example, the communication unit 100 may collect external environmental data from an external server or individually collect location information (ex. GPS information) from one or more mobile IoT devices using an IoT platform.

The storage unit 300 is a storage medium that stores programs and data necessary for the processor 200 to operate.

For example, the storage unit 300 may include a time series data DB 310 in which location information of one or more mobile IoT devices is stored and an external environment data DB 320 in which information about the external environment is stored.

Here, each location information collected through the communication unit 100 may be stored separately for each mobile IoT device in the time series data DB 310.

The processor 200 is provided to process all aspects of the system.

Specifically, since the safety range of the mobile IoT device is affected by the movement characteristics and external environment, the processor 200 derives the movement characteristics from the recent location data record of the mobile IoT device and links the external environment data to the mobile IoT device. The safety range can be calculated based on the device and periodically modified in response to changes in movement characteristics and external environment data.

That is, the processor 200 manages data stored in the time series data DB 310 and the external environment data DB 320, and based on real-time location information for a specific mobile IoT device and historical data of location information stored for a certain period of time. You can infer the movement characteristics of a mobile IoT device and set the safety range of the mobile IoT device based on the inference results of the movement characteristics.

At this time, the processor 200 determines the safety range because the movement characteristics such as speed, direction of movement, and path of the mobile IoT device, terrain, and weather conditions (ex. precipitation, snowfall, fog, etc.) affect the stopping distance of the mobile IoT device. Since it is a major factor in calculation, a stable range can be set by reflecting this information periodically.

Additionally, the processor 200 may calculate the collision risk between two mobile IoT devices by calculating the overlapping area between the safety ranges of different mobile IoT devices at the same time.

FIG. 2 is a diagram provided for a more detailed configuration explanation of the processor 200 shown in FIG. 1, and FIG. 3 is a diagram of a dynamic safety range setting system according to the characteristics and environment of mobile IoT according to an embodiment of the present invention. This is a diagram provided in the description of the operating characteristics, and FIG. 4 is a diagram illustrating the safety range set according to an embodiment of the present invention, and FIG. 5 is a diagram showing the safety range of different mobile IoT devices at the same time according to an embodiment of the present invention. This drawing shows an example of some of the safety ranges overlapping.

Referring to Figures 2 and 3, the processor 200 according to this embodiment includes a data management module 210, a moving object motion inferrator 220, a device safety range setter 230, and a real-time data processing engine module. It may include (240).

The data management module 210 manages data stored in the time series data DB 310 and the external environment data DB 320, and, if necessary, sends it to the moving object motion inferrator 220 or the device safety range setter 230. Data stored in the time series data DB 310 and the external environment data DB 320 may be provided.

For example, when the location information of a specific mobile IoT device for a preset period is accumulated in the time series data DB 310, the data management module 210 stores location history data for the preset period based on the accumulated location information. can be created and stored in the time series data DB 310.

The moving object motion inferrator 220 can infer the motion characteristics of a mobile IoT device based on location information about a specific mobile IoT device and history data of location information stored for a certain period of time.

For example, the mobile object motion inferrator 220 determines the location of the mobile IoT device based on the location information of the specific mobile IoT device collected through the communication unit and the location history data of the specific mobile IoT device stored in the time series data DB 310. Movement characteristics can be inferred. Here, the movement characteristics of the mobile IoT device may include the speed, movement direction, and path of the mobile IoT device. Additionally, the external environment information stored in the external environment data DB 320 may include terrain information, weather information, etc. that affect the stopping distance of the mobile IoT device. And the history data of location information stored for a certain period of time refers to location history data generated by accumulating location information collected over the last n times (randomly set).

The device safety range setter 230 can set the safety range of the mobile IoT device based on the inference results of the movement characteristics.

That is, the device safety range setter 230 can set the safety range based on the movement speed, direction information, and external environment information every preset first cycle (ex. n minutes).

Specifically, for example, when setting the safety range as illustrated in FIG. 4, the device safety range setter 230 sets a preset safety range setting value (n) along the movement direction from the current location of the mobile IoT device. A first point at a distance of 30° from the direction of movement, and a second point at a distance of 3/4 of the set value (n) of the preset safety range, at an angle of 60° from the direction of movement. A third point is spaced apart by 2/4 of the set value (n) of the preset safety range and is spaced apart by 1/4 of the set value (n) of the preset safety range in a direction inclined 90° from the direction of movement. You can set a safety range with the fourth point as the border.

That is, the device safety range setter 230 can set the separation distance (distance from the current location of the mobile IoT device to the border of the safety range) from the first point to the fourth point to gradually become shorter.

Additionally, the device safety range setter 230 can set the safety range setting value according to the moving speed of the mobile IoT device.

For example, the device safety range setter 230 sets the safety range setting value according to the moving speed of the mobile IoT device, so that the relatively faster the moving speed, the larger the safety range setting value (n) is set. It can be done as much as possible. This is because the stopping distance increases when the mobile IoT device stops depending on the moving speed.

And the device safety range setter 230 reflects the weather conditions (e.g., precipitation, snowfall, fog, etc.), and sets a relatively safe range value on days when precipitation, snowfall, fog, etc. occur compared to days when the weather conditions are clear. (n) can be set large.

In addition, the device safety range setter 230 analyzes the terrain information included in the external environment information and, when an obstacle exists in the movement path, sets the safety range setting value (n) to be relatively higher than when there is no obstacle. It can be set low.

Through this, the system that controls the risk of collision of mobile IoT devices attached to IoT devices can dynamically change the width of the safety range by reflecting external environmental information and object movement characteristics of the mobile IoT device in real time.

For another example, the device safety range setter 230 may dynamically change the width of the safety range by reflecting the path direction according to the movement path.

For example, the device safety range setter 230 compares one or more predicted paths predicted through a regression analysis model with the movement path, and the higher the similarity with the movement path among the predicted paths, the higher the safety range setting value. (n) can be set large.

Meanwhile, the real-time data processing engine module 240 can calculate the risk of collision between two mobile IoT devices by cross-checking the safety ranges of different mobile IoT devices located nearby at the same time.

Specifically, the real-time data processing engine module 240 may calculate the risk of collision between two mobile IoT devices by calculating the overlapping area between the safety ranges of different mobile IoT devices at the same time, as illustrated in FIG. 5.

In addition, the real-time data processing engine module 240 can reconstruct the current location of each mobile IoT device by crawling the points on the border of the safety range at every preset second cycle (ex. m minutes). .

For example, the real-time data processing engine module 240 crawls the raw data of the current location of the mobile IoT device and the list of points on the border of the safety range every preset second cycle and The risk of collision between other mobile IoT devices located nearby can be recalculated.

And, if the calculation result of the collision risk is greater than or equal to a threshold, the real-time data processing engine module 240 may transmit this to the outside to generate a collision risk warning (external notification).

Figure 6 is a flowchart provided to explain a method for setting a dynamic safety range according to the characteristics and environment of mobile IoT according to an embodiment of the present invention.

The dynamic safety range setting method according to the characteristics and environment of the mobile IoT according to this embodiment can be executed by the dynamic safety range setting system described above with reference to FIGS. 1 to 5.

This method of setting a dynamic safety range according to the characteristics and environment of mobile IoT collects each location information from one or more mobile IoT devices through a dynamic safety range setting system (S610), and sends each collected location information to the mobile IoT device. It can be stored separately (S620).

In addition, the dynamic safety range setting method according to the characteristics and environment of the mobile IoT infers the movement characteristics of the mobile IoT device based on the location information about the specific mobile IoT device collected in real time and the history data of the location information stored for a certain period of time (S630 ), the safety range of the mobile IoT device can be set based on the inference results of the motion characteristics (S640), and the risk of collision between the two mobile IoT devices can be calculated (S650).

At this time, when calculating the risk of collision between two mobile IoT devices, the dynamic safety range setting system calculates the overlapping area between the safety ranges of different mobile IoT devices at the same time as described above to calculate the risk of collision between the two mobile IoT devices. You can. Through this, safety accidents can be prevented more effectively.

Meanwhile, of course, the technical idea of the present invention can be applied to a computer-readable recording medium containing a computer program that performs the functions of the device and method according to this embodiment. Additionally, the technical ideas according to various embodiments of the present invention may be implemented in the form of computer-readable code recorded on a computer-readable recording medium. A computer-readable recording medium can be any data storage device that can be read by a computer and store data. For example, of course, computer-readable recording media can be ROM, RAM, CD-ROM, magnetic tape, floppy disk, optical disk, hard disk drive, etc. Additionally, computer-readable codes or programs stored on a computer-readable recording medium may be transmitted through a network connected between computers.

In addition, although preferred embodiments of the present invention have been shown and described above, the present invention is not limited to the specific embodiments described above, and the technical field to which the invention pertains without departing from the gist of the present invention as claimed in the claims. Of course, various modifications can be made by those of ordinary skill in the art, and these modifications should not be understood individually from the technical idea or perspective of the present invention.

100: Department of Communications
200: processor
210: data management module
220: Moving object motion inference device
230: Device safety range setter
240: Real-time data processing engine module
300: storage unit
310: Time series data DB
320: External environment data DB

Claims (12)

A communication unit that collects location information from one or more mobile IoT devices;
A storage unit that stores each collected location information separately by mobile IoT device; and
Inferring the movement characteristics of a mobile IoT device based on real-time location information for a specific mobile IoT device and historical data of location information stored for a certain period of time, and setting the safety range of the mobile IoT device based on the inference results of the movement characteristics Including a processor;
The storage department,
It includes a time series data DB in which location information of one or more mobile IoT devices is stored and an external environment data DB in which information about the external environment is stored,
The processor is
A data management module that manages data stored in the time series data DB and external environment data DB;
A moving object motion inferrator that infers the motion characteristics of a mobile IoT device based on location information about a specific mobile IoT device and historical data of location information stored for a certain period of time; and
It includes a device safety range setter that sets the safety range of the mobile IoT device based on the inference results of the movement characteristics,
The device safety range configurator,
Sets a safety range based on movement speed, direction information, and external environment information,
The device safety range configurator,
When setting the safety range, a first point is spaced apart by the set value (n) of the preset safety range along the direction of movement from the current location of the mobile IoT device, and a preset safety range in a direction inclined 30° from the direction of movement. A second point spaced apart by 3/4 of the set value (n), a third point spaced apart by 2/4 of the set value (n) of the preset safety range in a direction inclined 60° from the direction of movement, and A dynamic safety range setting system characterized in that the safety range is set as a border at a fourth point spaced apart by 1/4 of the set value (n) of the preset safety range in a direction inclined at 90° from the moving direction.
delete delete In claim 1,
The data management module is,
When the location information of a specific mobile IoT device for a preset period is accumulated in the time series data DB, location history data for the preset period is generated based on the accumulated location information and stored in the time series data DB,
The moving object motion inference device is,
A dynamic safety range setting system characterized by inferring the movement characteristics of a mobile IoT device based on the location information of a specific mobile IoT device collected through the communication unit and the location history data of a specific mobile IoT device stored in a time series data DB.
delete delete In claim 1,
The device safety range configurator,
Set the safety range setting value according to the moving speed of the mobile IoT device so that the relatively faster the moving speed, the larger the safety range setting value (n) is set.
A dynamic safety range setting system that analyzes the terrain information included in the external environment information and sets the safety range setting value (n) relatively lower than when there are obstacles in the movement path, compared to the case where no obstacles exist. .
In claim 1,
The processor is
A dynamic safety range setting system further comprising a real-time data processing engine module that calculates the risk of collision between two mobile IoT devices by calculating the overlapping area between the safety ranges of different mobile IoT devices at the same time.
In claim 8,
The real-time data processing engine module is,
A dynamic safety range setting system characterized by crawling and reconstructing the current location of each mobile IoT device and points on the border of the safety range at preset intervals.
The system collects location information from one or more mobile IoT devices;
The system stores each collected location information separately by mobile IoT device;
Inferring, by the system, the movement characteristics of a mobile IoT device based on location information about a specific mobile IoT device and historical data of location information stored for a certain period of time; and
It includes the step of the system setting a safety range for the mobile IoT device based on the inference results of the movement characteristics,
The system is,
It includes a time series data DB in which location information of one or more mobile IoT devices is stored and an external environment data DB in which information about the external environment is stored,
The system is,
A data management module that manages data stored in the time series data DB and external environment data DB;
A moving object motion inferrator that infers the motion characteristics of a mobile IoT device based on location information about a specific mobile IoT device and historical data of location information stored for a certain period of time; and
It further includes a device safety range setter that sets the safety range of the mobile IoT device based on the inference results of the movement characteristics,
The steps to set the safety range are:
The device safety range setter sets the safety range based on movement speed, direction information, and external environment information,
The steps to set the safety range are:
When setting the safety range, a first point is spaced apart by the set value (n) of the preset safety range along the direction of movement from the current location of the mobile IoT device, and a preset safety range in a direction inclined 30° from the direction of movement. A second point spaced apart by 3/4 of the set value (n), a third point spaced apart by 2/4 of the set value (n) of the preset safety range in a direction inclined 60° from the direction of movement, and A dynamic safety range setting method characterized by setting a safety range with a border at a fourth point spaced apart by 1/4 of the set value (n) of the preset safety range in a direction inclined 90° from the moving direction.
delete delete