JP7614080B2 - Danger situation reporting system - Google Patents

Description

An embodiment of the present invention relates to a system for reporting dangerous situations during the operation of loading and unloading machines such as cranes.

In the cargo handling machinery industry, the operator of the cargo handling machinery performs operations such as hoisting, traversing or running to pick up the target object, and aligns the equipment with a gripping mechanism such as spreaders, tongs or buckets. After gripping the target object, the operator performs operations such as hoisting, traversing or running again to place it in the target position.

The operation of such cargo handling machines is controlled by a control system that includes a control device and a drive device. The control device, which is part of the control system, receives electrical signals from the driving equipment operated by the driver, and generates electrical signals to control the drive device based on the received electrical signals, thereby driving the drive device and controlling the cargo handling machine.

The operating status of the loading and unloading machine is displayed on a monitoring device connected to the control device or stored in a data collection device, so that the operator of the loading and unloading machine or a technician who performs maintenance on the loading and unloading machine can check the operating status of the loading and unloading machine. In addition to the electrical signals sent and received by the control device, the data collection device may also be connected to a photographing device to capture image data of the surrounding conditions during operation and store the captured image data.

The cab of a loading and unloading machine and the drive parts such as the spreader are often located in separate locations, and even if the driver operates the machine while paying careful attention to his or her surroundings, blind spots may occur due to the object being transported and the location of the cab and drive parts. In such cases, dangerous situations may arise where the object is about to collide with the loading and unloading machine, ship, or other surrounding structures, or where an actual collision occurs, causing an accident. Such dangerous situations are sometimes called "near misses."

When a near miss occurs, the driver must report it after the accident or in a daily report. Daily reports are often created manually and stored on paper, making it difficult to identify the circumstances of the near miss in relation to the accident. This can mean that it can take a very long time to analyze and clarify the cause of an accident and to prepare a report. In addition, it is necessary to take measures to prevent accidents from occurring by checking the target operating status based on data from data collection devices, but it takes a lot of time to identify the target operating data from a huge amount of data.

JP 2016-18317 A

The object of an embodiment of the present invention is to provide a dangerous situation reporting system that can generate, save, and output a dangerous situation report based on a control signal when a dangerous situation occurs and video data of the surrounding situation.

According to an embodiment of the present invention, there is provided a control device for controlling a driving device by transmitting and receiving a plurality of control signals between a driving device operated by a driver of a loading machine and a driving device that drives an electric motor that drives an operating unit of the loading machine, and for generating a trigger signal representing the timing of occurrence of a dangerous situation occurring during operation of the loading machine based on a preset condition , a camera for acquiring video data of a desired field of view during operation of the loading machine, a data collection device for collecting one or more control signals that are preset among the plurality of control signals, collecting the video data in time synchronization with the one or more control signals , and storing the one or more control signals and the video data for a predetermined period including a period before and after the generation of the trigger signal , and a report creation device for creating, storing, and outputting a dangerous situation report in a predetermined report format for reporting the dangerous situation that has occurred based on the one or more control signals and the video data stored in the data collection device . The report creation device allows a comment regarding the dangerous situation that has occurred to be input into the dangerous situation report .

In this embodiment, a dangerous situation reporting system is realized that can generate, save, and output a dangerous situation report based on a control signal when a dangerous situation occurs and video data of the surrounding situation.

1 is a schematic block diagram illustrating a dangerous situation reporting system according to a first embodiment; 4 is an example of a flowchart for explaining an operation of the dangerous situation reporting system according to the first embodiment. 4 is an example of a flowchart for explaining an operation of the dangerous situation reporting system according to the first embodiment. FIG. 11 is a schematic block diagram illustrating a dangerous situation reporting system according to a second embodiment. 13 is an example of a flowchart for explaining an operation of the dangerous situation reporting system according to the second embodiment. FIG. 13 is a schematic block diagram illustrating a dangerous situation reporting system according to a third embodiment. 13 is an example of a flowchart for explaining an operation of the dangerous situation reporting system according to the third embodiment. 13 is an example of a flowchart for explaining an operation of the dangerous situation reporting system according to the second embodiment.

Hereinafter, an embodiment of the present invention will be described with reference to the drawings.
The drawings are schematic or conceptual, and the relationship between the thickness and width of each part, the size ratio between parts, etc. are not necessarily the same as in reality. Even when the same part is shown, the dimensions and ratios of each part may be different depending on the drawing.
In this specification and each drawing, elements similar to those described above with reference to the previous drawings are given the same reference numerals and detailed description thereof will be omitted as appropriate.

(First embodiment)
FIG. 1 is a schematic block diagram illustrating a dangerous situation reporting system according to the present embodiment.
In this embodiment and other embodiments described later, a dangerous situation reporting system is described which is applied to an electrical control system of a cargo handling machine including a cab 1, an electric room 2, a leg section 3, and a machine room 4. The cargo handling machine is, for example, a crane, such as a gantry crane. The configurations of the cab 1, the electric room 2, the leg section 3, and the machine room 4 may vary depending on the configuration of the cargo handling machine to which the dangerous situation reporting system is applied, but even if these configurations are different, the system can be easily applied based on the specific example described below.

As shown in FIG. 1, the hazard situation reporting system 100 of this embodiment includes a control device 20, a data collection device 30, a camera 40, and a report creation device 80. In this example, the control device 20, the data collection device 30, and the report creation device 80 are provided in the electrical room 2. The cameras 40 are provided in each of the cab 1, the electrical room 2, the legs 3, and the machine room 4.

The cab 1 is where the driver who operates the loading and unloading machine sits. The cab 1 is provided with driving equipment 10 and push buttons 70. The driving equipment 10 is equipment operated by the driver, such as a start switch and operating levers. For example, a display device and meters that show the height and position of the container are also arranged in the cab 1 as driving equipment 10.

The push button 70 is connected to the control device 20 via the driving operation equipment 10. The driver presses the push button 70 when he determines that a dangerous situation has occurred. The push button 70 is provided in the driver's cab 1 and may be a button that is pressed by hand or a foot switch that is pressed by foot. The push button 70 is not limited to being provided in the driver's cab 1 and operated by the driver, but may be provided in the electrical room 2 as in this example, or may be provided outside the loading machine. For example, an electrical signal when the push button 70 is pressed may be transmitted by wireless communication and received by the control device 20, allowing a supervisor outside the loading machine to monitor the operating status of the loading machine and operate the push button 70.

The camera 40 is installed to capture images of the inside of the cab 1. The camera 40 is installed, for example, so that the driver seated in the driver's seat is included in the field of view. By arranging the camera 40 in this way, the driver's actions when a dangerous situation occurs can be captured and recorded. The number of cameras 40 installed in the cab 1 is not limited to one, and two or more cameras may be installed.

The camera 40 can be installed not only in the driver's cab 1 but also in any desired location. In this example, the camera 40 is also installed in the legs 3 and the machine room 4. In this example, no camera 40 is installed in the electrical room 2, but one may be installed if necessary. The number of cameras 40 installed in each location is not limited to one, and multiple cameras may be installed so that the object to be monitored is included in the field of view.

The driving operation equipment 10 is connected to the control device 20, and the camera 40 is connected to the data collection device 30. The control device 20 receives control signals emitted from the driving operation equipment 10 and the push button 70. The data collection device 30 is connected to the camera 40 and collects video data captured by the camera 40.

In this example, the control device 20, the data collection device 30, and the report creation device 80 are provided in the electrical room 2. All or part of the control device 20, the data collection device 30, and the report creation device 80 may be provided in other locations, such as the machine room 4, and not limited to the electrical room 2.

The legs 3 are provided when the loading and unloading machine is a gantry crane or the like. The gantry crane is installed, for example, on the quay of a port where ships are loaded. Rails are laid along the quay, and the gantry crane can move along the rails. The legs 3 are provided with wheels for running on the rails, and are provided with an electric motor (not shown) that drives the wheels and a drive unit 60 that drives the electric motor.

When the loading and unloading machine is a gantry crane or the like, the machine room 4 is provided with electric motors and reducers for driving the spreader position to move sideways and to raise and lower. In this example, the machine room 4 is also provided with a drive unit 50 for driving these electric motors.

The drive units 50, 60 of the legs 3 and the machine room 4 are connected to the control device 20. The control device 20 operates based on a preset control program and an electrical signal from the driving operation equipment 10. The control device 20 receives the electrical signal generated by the drive units 50, 60, generates an electrical signal for displaying information such as the container's position based on the received electrical signal, and transmits it to the driving operation equipment 10. The electrical signals transmitted and received between the control device 20 and the driving operation equipment 10, the electrical signals transmitted and received between the control device 20 and the push button 70, and the electrical signals transmitted and received between the control device 20 and the drive units 50, 60 may be partially or entirely electrical signals, and may be optical signals, etc. Hereinafter, the signals transmitted and received by the control device 20 to and from other elements are referred to as control signals. Note that the push button 70 is pressed, and the control signal generated by the control device 20 to indicate that the push button 70 has been pressed is referred to as a trigger signal when it is to be distinguished from other control signals.

The data collection device 30 collects one or more control signals from the control device 20. The type of control signal that the data collection device 30 will collect is set in advance. The data collection device 30 also collects video data captured by the cameras 40. If multiple cameras 40 are installed, the data collection device 30 collects the video data from the cameras 40 as video data, along with a signal that identifies each camera 40.

When the control device 20 generates a trigger signal by pressing the push button 70, it stores a control signal for a period including the period before and after the trigger signal in the data collection device 30. The data collection device 30 stores the video data of the camera 40 as video data in time synchronization with the stored control signal. The periods before and after the trigger signal are set in advance. The periods before and after the trigger signal may be the same length or different lengths. The periods before and after the trigger signal may be common to the control signals collected and stored, or may be set differently for each control signal.

For example, the data collection device 30 has a storage device (not shown) and receives a preset control signal from the control device 20 and stores the received control signal in the storage device. When the data collection device 30 detects that a trigger signal has been generated by the control device 20, it stores, for example, the control signal for a period including the period before and after the trigger signal in another area of the storage device. The data collection device 30 saves video data for a period including the period before and after the trigger signal in the storage device, time-synchronizing the video data with the control signal.

When multiple push buttons 70 are provided, a signal that can be identified for each installation location of the push buttons 70 is added to the trigger signal. The data collection device 30 stores in a storage device a control signal and video data time-synchronized with the control signal for each identified trigger signal.

In the above case, the data collection device 30 stores the control signal and video data for the entire period in the storage device, but if the storage capacity of the storage device is small, it may store only the period including the period before and after the trigger signal.

The report creation device 80 is connected to the data collection device 30. The report creation device 80 acquires the control signals and video data collected by the data collection device 30, for example, at a preset timing. The preset time is determined, for example, based on the closing time when work for the day ends, and the report creation device 80 outputs the daily dangerous situations in a report format. The report created by the report creation device 80 is created, for example, for each period including the period before and after the time when the push button 70 is pressed. If multiple push buttons 70 are provided, a report is created for each location where the push button 70 is installed.

The operator of the report creation device 80, for example the driver on that day, can manually input comments such as countermeasures and precautions to the generated report via an input device connected to the report creation device 80.

For example, the reports generated and output by the report creation device 80 are sent periodically or as needed to a server installed in a data center, for example, and shared with loading and unloading machine drivers, managers, and maintenance and inspection personnel for the electrical control system, etc.

The report creation device 80 can generate reports according to preset classification criteria. The classification criteria are set, for example, for each operation of the loading and unloading machine. Specifically, one classification is whether or not the container is lifted or lowered. The other classification is whether or not the container is moved sideways. The lifting and lowering operation of the container may be divided into an upward operation and a downward operation. In addition, the above-mentioned operations may be further classified according to more detailed classification criteria. For example, the range of the lifting speed or the range of the downward speed during the lifting and lowering operation of the container, or the range of the lateral movement speed of the container may be used as the criteria for further classification. In addition, since the control device 20 can also obtain information on the position and height of the container, the range of the height of the container and the range of the lateral movement position of the container may be set as classification criteria.

These classification criteria can be determined by appropriately selecting the type of control signal sent and received by the control device 20, the speed reference data based on the control signal, etc., and in some cases, based on data obtained by calculating the data held by multiple control signals.

Classification criteria are not limited to items related to the operation of loading and unloading machinery, but may also be, for example, whether the work was done in the early morning, midday, evening, etc., the weather at the time of the work, the month in which the work was done, etc.

A series of operations of the dangerous situation reporting system 100 of this embodiment will be described with reference to a flowchart.
2 and 3 are examples of flowcharts for explaining the operation of the dangerous situation reporting system of this embodiment.
As shown in FIG. 2, in step S1, when the driver or the like presses the push button 70, the push button 70 transmits to the control device 20 a control signal indicating that the push button 70 has been pressed.

In step S2, the control device 20 generates a trigger signal at the timing when the control signal generated when the push button 70 is pressed is received, and stores the control signal for a period including the period before and after the trigger signal in the data collection device 30. The data collection device 30 stores the video data together with the control signal in time synchronization with the control signal to be stored.

In step S3, the report creation device 80 converts the stored control signal and video data into a predetermined format, generates a dangerous situation report, and makes it available for output.

In step S4, the report creation device 80 stores the generated dangerous situation report in its own storage device, server, etc.

As shown in FIG. 3, in step S5, the report creation device 80 classifies the generated risk situation report according to preset classification criteria.

In step S6, the report creation device 80 enables output of a danger situation report for each classification criterion.

The effects of the dangerous situation reporting system 100 of this embodiment will be described.
In the dangerous situation reporting system 100 of this embodiment, the period of control signals and video data to be collected can be set based on the trigger signal generated by pressing the push button 70. Therefore, the necessary data can be stored with a small storage capacity.

The stored control signals and video data can be used by the report creation device 80 to generate and output a dangerous situation report in a specified format. This can be useful for sharing information about each dangerous situation.

Comments about dangerous situations can be manually entered for each unit of stored control signals and video data. This can be useful in coming up with more effective countermeasures in relation to actual data.

In this embodiment, the dangerous situation reporting system 100 outputs dangerous situations as a report according to a classification that takes into account the operating state of the loading and unloading machine and the natural conditions (weather, season, etc.) during the work. This makes it possible to grasp problems by taking into account conditions that make it difficult to analyze dangerous situations.

The report includes video data, so depending on the driver's level of skill, it is possible to check useful actions, such as methods for avoiding dangerous situations, which can also be useful for transferring skills and techniques.

By having the push button 70 carried not only by the driver but also by an external supervisor, it can be useful for investigating the cause of dangerous situations occurring in places out of the driver's line of sight.

Second Embodiment
FIG. 4 is a schematic block diagram illustrating a dangerous situation reporting system according to the present embodiment.
As shown in FIG. 4 , the dangerous situation reporting system 200 of this embodiment includes a control device 220 , a data collecting device 30 , a camera 40 , and a report creating device 80 .
In this embodiment, the control device 220 generates an equipment failure signal 225 as a trigger signal when a predetermined condition is satisfied. The data collection device 30 stores the control signal and video data based on the equipment failure signal 225. The dangerous situation report system 200 of this embodiment differs from that of the first embodiment in that the configuration of the control device 220 generates the equipment failure signal 225, but is otherwise the same as that of the first embodiment. The same components are denoted by the same reference numerals, and detailed descriptions will be omitted as appropriate.

The control device 220 has a function of generating an equipment failure signal 225. The equipment failure signal 225 is generated by a control signal that the control device 220 receives from the driving operation equipment 10 and the drive devices 50 and 60. The equipment failure signal 225 is generated, for example, when one control signal exceeds or falls below a preset threshold value. The equipment failure signal 225 is not limited to being generated from one control signal, but may also be generated based on the results of performing a predetermined calculation on multiple control signals.

The control device 220 stores the control signal and video data for a period including the period before and after the time when the equipment failure signal 225 was generated in the data collection device 30.

FIG. 5 is an example of a flowchart for explaining the operation of the dangerous situation reporting system of this embodiment.
As shown in FIG. 5, in step S21, the control device 220 detects that a preset control signal satisfies a predetermined condition, and generates an equipment fault signal 225.

In step S22, the data collection device 30 stores the control signal and video data for a period including the period before and after the time when the equipment failure signal 225 was generated.

In step S23, the report creation device 80 generates a dangerous situation report in a predetermined format and enables output.

In step S24, the report creation device 80 saves the danger situation report, for example, according to preset classification criteria.

The effects of the dangerous situation reporting system 200 of this embodiment will be described.
The dangerous situation reporting system 200 of this embodiment stores a predetermined control signal and video data based on the equipment failure signal 225 generated by the control device 220. Therefore, it is possible to detect a more objective failure or dangerous situation, independent of judgment based on the five human senses such as the driver's operation.

In addition, in the control device 220 of this embodiment, the push button 70 of the first embodiment may be installed, and the generation of a trigger signal by the push button 70 may be used in combination with a trigger by the device failure signal 225. Also, a new device failure signal may be generated by calculating a specific device failure signal and the trigger signal by the push button 70.

Third Embodiment
FIG. 6 is a schematic block diagram illustrating a dangerous situation reporting system according to the present embodiment.
As shown in FIG. 6 , the dangerous situation report system 300 of this embodiment includes a control device 20, a data collection device 30, a camera 40, a report creation device 80, a machine learning device 385, and a dangerous situation lamp 390.
The dangerous situation report system 300 of this embodiment differs from that of the first embodiment in that it further includes a machine learning device 385 and a dangerous situation lamp 390, but is otherwise the same as that of the first embodiment. The same components are denoted by the same reference numerals and detailed descriptions thereof will be omitted as appropriate.

The machine learning device 385 acquires a dangerous situation report from the report creation device 80. The machine learning device 385 inputs the acquired dangerous situation report, identifies a control signal that becomes a dangerous situation, and identifies the conditions when the dangerous situation is determined. The machine learning device 385 sets a threshold value of an appropriate level for the identified control signal, for example, based on the conditions when the dangerous situation is determined. The machine learning device 385 transmits the identified control signal and its threshold value to the control device 20, and the control device 20 sets the received control signal and threshold value.

The control signal for determining a dangerous situation is identified, and the control device 20, in which the threshold value is set, generates a warning signal when the control signal exceeds the threshold value, and as in this example, the warning signal may cause a dangerous situation lamp to light up.

More specifically, the machine learning device 385 determines, from the dangerous situation report, for example, that a suspended load exceeding a certain value is being transported as a dangerous situation, identifies the corresponding control signal (e.g., a torque signal generated by a drive device, etc.), and sets an appropriate threshold value. For example, it determines, from the dangerous situation report, that a lateral speed exceeding a certain value is being transported as a dangerous situation, identifies the corresponding control signal (e.g., a speed reference output by the control device 20, etc.), and sets an appropriate threshold value. For example, it determines, from the dangerous situation report, that a detected value of the sway angle of a container exceeds a certain value, identifies the corresponding control signal (e.g., an output signal of a laser detector for detecting the container position, etc.), and sets an appropriate threshold value.

The parameters that the machine learning model is trained on can be the hoisting position, hoisting speed, traverse position, traverse speed, traveling position, traveling speed, cargo load, gripping state of each hoisting device, cargo position before transport, cargo position after transport, state of obstacles outside the cargo handling machine, month, time, etc.

When setting the appropriate threshold value described above, the machine learning model possessed by the machine learning device 385 may set the level of the dangerous situation in multiple stages, for example, by taking into consideration the contents of comments entered by the driver or the like in the dangerous situation report.

In addition, by associating the dangerous situation report with control signals, video data, and also the date and time (year, month, and day) and weather conditions at that date and time, the machine learning model can use seasonal lighting conditions (glare and darkness when working) as a criterion for determining dangerous situations.

The machine learning model may be configured to set dangerous situations and threshold values for each operation pattern of the loading and unloading machinery that is used as a classification criterion in the dangerous situation report, i.e., for each operating pattern.

The data learned by the machine learning device 385 is not limited to data collected from one cargo handling machine, but may be information from multiple cargo handling machines collected via a communication network to collect a wider range and larger amount of data. The machine learning device 385 may perform deep learning on the learning model based on the collected data. With deep learning, video data can also be used for supervised learning to create a more effective dangerous situation judgment model.

When the control device 20 determines that a dangerous situation exists based on the dangerous situation determination conditions set by the machine learning device 385, it generates a signal representing the dangerous situation and stores the control signal and video data for a period including the period before and after the time the signal was generated in the data collection device 30.

The danger situation reporting system 300 of this embodiment can be applied in combination with the first and second embodiments described above.

A series of operations of the dangerous situation reporting system 300 of this embodiment will be described with reference to a flowchart.
7 and 8 are examples of flowcharts for explaining the operation of the dangerous situation reporting system of this embodiment.
As shown in FIG. 7 , in step S31, the machine learning device 385 sets a dangerous situation determination condition in the control device 20.

In step S32, when the control device 20 detects that the dangerous situation determination condition has been exceeded, in step S33, it generates a warning signal and outputs it to the driving operation equipment 10.

In step S33, the driving operation equipment 10 turns on the danger situation lamp 390 based on the warning signal.

As shown in FIG. 8, in step S31, the control device 20 sets the dangerous situation determination condition. When the control device 20 detects an excess of the dangerous situation determination condition in step S32, the control device 20 generates a trigger signal, and in step S35, the control signal and video data for a period including the period before and after the time the trigger signal was generated are stored in the data collection device 30.

In step S36, the report creation device 80 generates a dangerous situation report and makes it available for output.

In step S37, the report creation device 80 saves the generated report, for example, for each dangerous situation judgment condition.

The effects of the dangerous situation reporting system 300 of this embodiment will be described.
The dangerous situation report system 300 of this embodiment includes a machine learning device 385. The machine learning device 385 acquires a dangerous situation report from the report creation device 80, inputs the dangerous situation report to a machine learning model, and generates and outputs dangerous situation determination conditions. The dangerous condition determination conditions are used for new dangerous situation determination for the control device 20. Therefore, the previously set trigger signal generation conditions can be further advanced to become appropriate conditions.

In this embodiment, the control device 20 sets the dangerous situation judgment conditions based on the control signal indicating the dangerous situation and the data set by the machine learning device 385. Therefore, the control device 20 can generate a warning signal based on such dangerous situation judgment conditions, making it possible to encourage the driver to act more safely and to prevent the dangerous situation from developing into an actual accident.

According to the embodiment described above, it is possible to realize a danger situation report system that automatically generates and outputs a danger situation report based on a control signal when a danger situation occurs and video data of the surrounding situation.

Although several embodiments of the present invention have been described above, these embodiments are presented as examples and are not intended to limit the scope of the invention. These novel embodiments can be implemented in various other forms, and various omissions, substitutions, and modifications can be made without departing from the gist of the invention. These embodiments and their variations are included within the scope and gist of the invention, as well as within the scope of the invention and its equivalents described in the claims. In addition, the above-mentioned embodiments can be implemented in combination with each other.

1 Cab, 2 Electrical room, 3 Legs, 4 Machine room, 10 Driving equipment, 20, 220 Control device, 30 Data collection device, 40 Camera, 50, 60 Drive device, 70 Push button, 100, 200, 300 Danger situation report system, 225 Equipment failure signal, 385 Machine learning device, 390 Danger situation lamp

Claims (5)

a control device that controls a driving device by transmitting and receiving a plurality of control signals between a driving operation tool operated by a driver of the cargo handling machine and a driving device that drives an electric motor that drives an operating unit of the cargo handling machine, and that generates a trigger signal that indicates the timing of occurrence of a dangerous situation that occurs during operation of the cargo handling machine based on a preset condition ;
a camera for acquiring video data of a desired field of view during operation of the cargo handling machine;
a data collection device that collects one or more preset control signals from among the plurality of control signals, collects the video data in time synchronization with the one or more control signals , and stores the one or more control signals and the video data for a predetermined period including a period before and after the generation of the trigger signal ;
a report creation device that creates, stores, and outputs a dangerous situation report in a predetermined report format for reporting the dangerous situation that has occurred based on the one or more control signals and the video data stored in the data collection device ;
Equipped with
The report creation device is a dangerous situation report system that enables comments regarding the dangerous situation that has occurred to be input into the dangerous situation report . A plurality of push buttons are further provided at a plurality of locations to be monitored of the cargo handling machine,
The control device identifies which of the plurality of push buttons has been pressed and generates the identified plurality of trigger signals;
2. The dangerous situation reporting system according to claim 1, wherein the report generating device generates, stores, and outputs the dangerous situation report for each of the identified plurality of trigger signals. 3. The dangerous situation reporting system according to claim 1, wherein the control device generates the trigger signal when a preset control signal among the plurality of control signals satisfies a predetermined condition. the report creation device is capable of creating, storing, and outputting the risk situation report for each of a plurality of preset classification criteria;
A dangerous situation reporting system as described in any one of claims 1 to 3, wherein the multiple classification criteria are set based on the operation of the loading machine, the operation date and time of the loading machine, and the position of the cargo being transported by the loading machine. a machine learning device having a machine learning model that receives the dangerous situation report generated by the report creation device and outputs a dangerous situation determination condition for determining a new dangerous situation,
The control device sets the dangerous situation determination condition output by the machine learning device, and generates a warning signal when the dangerous situation determination condition is satisfied. A dangerous situation reporting system according to any one of claims 1 to 4.

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