A method of determining whether a safety line is being misused

Abstract

A method for determining whether safety ropes are being used improperly is disclosed, relating to the field of power construction safety. To address the problem that existing technologies rely on manual observation to determine whether safety ropes are being used improperly, which can easily lead to oversights or misjudgments due to the large number of construction workers on site, potentially causing accidents, this invention utilizes an AI trainer to train an AI recognition module. This module identifies construction workers, safety ropes, the position of the safety rope on the worker, and the rope's attachment point. When a scenario of improper safety rope use is detected, the AI ​​recognition module transmits an alarm signal to an alarm device. This method uses an AI recognition module for accurate identification, replacing manual observation, avoiding oversights or misjudgments, thus preventing safety accidents and ensuring the safety of construction workers. This invention is applicable to the field of power construction safety.

Description

Technical Field

[0001] This invention relates to the field of power construction safety, and specifically to a method for determining whether a safety rope has been used improperly. Background Technology

[0002] High-altitude work is common in the power industry and related fields. A crucial safety measure to prevent falls from heights is the use of safety ropes. To ensure the effectiveness of safety ropes, usage regulations have been established. Furthermore, each construction site has safety inspectors who monitor and inspect the work area either on-site or remotely via video equipment. However, given the large number of workers on power industry work sites, relying solely on visual observation by safety inspectors can easily lead to omissions or misjudgments.

[0003] In summary, current technologies rely on manual observation to determine whether safety ropes are being used improperly. However, due to the large number of construction workers on site, oversights or misjudgments can easily occur, potentially leading to accidents. Summary of the Invention

[0004] This invention addresses the problem that existing technologies rely on manual observation to determine whether safety ropes are being used improperly. This is because, due to the large number of construction workers at the site, oversights or misjudgments can easily occur, potentially leading to accidents. Therefore, this invention proposes a method to determine whether safety ropes are being used improperly.

[0005] The present invention provides a method for determining whether a safety rope has been used improperly, the specific method of which is as follows:

[0006] Step 1: First, deploy and install n cameras at the construction site, where n is a positive integer, and connect the video signal output of the cameras to the video signal input of the artificial intelligence recognition module through wires;

[0007] Step 2: Train the AI ​​recognition module through an AI trainer;

[0008] Step 3: After completing the training of the artificial intelligence recognition module, record or photograph the environment and construction personnel at the construction site through the camera, and transmit the video signal to the artificial intelligence recognition module in real time; based on the data processing of the video or photo by the artificial intelligence recognition module, manually identify the height of the construction personnel and the height of people in the surrounding environment, and determine the height of the working surface.

[0009] Step 4: Use the trained artificial intelligence recognition module to determine whether there is a phenomenon of low hanging and high use of the safety rope (strip) in the video or photo. If so, the artificial intelligence recognition module will transmit an alarm signal to the alarm device to issue an alarm; and the artificial intelligence recognition module will archive the video or photo; if not, continue monitoring.

[0010] Step 5: Use the trained artificial intelligence recognition module to determine the knot position of the safety rope (belt) in the video or photo. If the knot position of the safety rope (belt) is far away from the worker's waist, the artificial intelligence recognition module will transmit an alarm signal to the alarm device to issue a warning; and the artificial intelligence recognition module will archive the video or photo; if it does not exist, it will continue to monitor.

[0011] Furthermore, the number of cameras n, 2≤n≤50;

[0012] Furthermore, the specific method for training the AI ​​recognition module through an AI trainer in step two is as follows:

[0013] Step 2: 1. Establish a descriptive model of the construction workers and input the model into the artificial intelligence recognition module so that the artificial intelligence recognition module can identify the construction workers at the construction site.

[0014] Step 22: Establish a description model of the safety rope (belt) and input the model into the artificial intelligence recognition module so that the artificial intelligence recognition module can recognize the safety rope (belt);

[0015] Steps 2 and 3: The AI ​​trainer trains the AI ​​recognition module to identify safety ropes (belts) of various specifications (purposes);

[0016] Step 24: The AI ​​trainer trains the AI ​​recognition module to determine the working height, and sets and modifies the minimum height for the use of safety ropes (belts) according to the different requirements of various industries and fields.

[0017] Step 25: The AI ​​trainer trains the AI ​​recognition module to identify dangerous scenarios where construction workers are not using safety ropes (belts) at a fixed working height;

[0018] Step 26: The AI ​​trainer trains the AI ​​recognition module to identify unsafe scenarios where the safety rope (strip) is used at a low angle and is suspended at a high angle.

[0019] Step 27: The AI ​​trainer trains the AI ​​recognition module to identify whether the knot of the safety rope (belt) is located in a safe position on the construction worker, thereby completing the recognition training of the AI ​​recognition module.

[0020] Furthermore, in step two, the artificial intelligence recognition module is trained using a description model of construction workers. During the training, through continuous training of human vision and continuous correction of the construction worker model, the vision of the artificial intelligence recognition module can correctly identify the construction workers on the work site.

[0021] Furthermore, in step two, the description model of the safety rope (belt) is used to train the artificial intelligence recognition module. During the training, the description model of the safety rope (belt) is tied to the description model of the construction worker, and the two ends of the safety rope (belt) model are knotted. Through continuous training of artificial vision and continuous correction of the safety rope (belt) model, the vision of the artificial intelligence recognition module can correctly identify the position of the safety rope (belt) tied on the construction worker.

[0022] Furthermore, the aforementioned artificial intelligence recognition module connects to the mobile phone via wireless signal. If the artificial intelligence recognition module identifies a dangerous scene, it will transmit an alarm signal to the mobile phone to issue a warning.

[0023] Furthermore, in step one, multiple cameras are deployed and installed at the construction site to monitor and capture the construction site without blind spots.

[0024] Compared with the prior art, the present invention has the following advantages:

[0025] This invention overcomes the shortcomings of existing technologies by using an AI trainer to train the AI ​​recognition module. This allows the AI ​​recognition module to accurately identify construction workers, safety ropes, the position of the safety ropes on the workers, and the location where the safety ropes are attached. When a scenario of improper use of the safety rope is identified, the AI ​​recognition module transmits an alarm signal to the alarm device to issue a warning. This judgment method uses the AI ​​recognition module for precise intelligent identification, replacing manual observation, avoiding oversights or misjudgments, thereby preventing safety accidents and ensuring the safety of construction workers. Attached Figure Description

[0026] Figure 1 This is a flowchart of a method for determining whether a safety rope is being used improperly, as described in this invention. Detailed Implementation

[0027] Specific implementation method one: Combining Figure 1 This embodiment describes a method for determining whether a safety rope has been used improperly. The specific method is as follows:

[0028] Step 1: First, deploy and install n cameras at the construction site, where n is a positive integer, and connect the video signal output of the cameras to the video signal input of the artificial intelligence recognition module through wires;

[0029] Step 2: Train the AI ​​recognition module through an AI trainer;

[0030] Step 3: After completing the training of the artificial intelligence recognition module, record or photograph the environment and construction personnel at the construction site through the camera, and transmit the video signal to the artificial intelligence recognition module in real time; based on the data processing of the video or photo by the artificial intelligence recognition module, manually identify the height of the construction personnel and the height of people in the surrounding environment, and determine the height of the working surface.

[0031] Step 4: Use the trained artificial intelligence recognition module to determine whether there is a phenomenon of low hanging and high use of the safety rope in the video or photo. If there is, the artificial intelligence recognition module will transmit an alarm signal to the alarm device to issue an alarm; and the artificial intelligence recognition module will archive the video or photo; if there is no such phenomenon, monitoring will continue.

[0032] Step 5: Use the trained artificial intelligence recognition module to determine the knot position of the safety rope in the video or photo. If the knot position of the safety rope is far away from the worker's waist, the artificial intelligence recognition module will transmit an alarm signal to the alarm device to issue a warning; and the artificial intelligence recognition module will archive the video or photo; if it does not exist, monitoring will continue.

[0033] In this specific implementation, besides the worker needing to correctly use the safety rope according to safety regulations, safety inspectors often need to supervise and inspect the work site either on-site or remotely via video equipment. While there are many inspectors at power industry work sites, oversights are inevitable, meaning violations of safety rope usage may not be detected in time. This invention utilizes an AI trainer to train an AI recognition module, enabling it to accurately identify the worker, the safety rope, the rope's position on the worker, and the rope's attachment point. When a violation is detected, the AI ​​recognition module transmits an alarm signal to the alarm device. This method uses precise intelligent identification via AI, replacing manual observation, avoiding oversights or misjudgments, thus preventing accidents and ensuring the safety of construction workers.

[0034] Specific Implementation Method Two: Combining Figure 1This embodiment further defines the judgment method described in Specific Embodiment 1. In this embodiment, a method for determining whether a safety rope is being used improperly is provided, wherein the number of cameras n is 2 ≤ n ≤ 50.

[0035] Specific implementation method three: Combining Figure 1 This embodiment further defines the judgment method described in Specific Embodiment 1. The specific method for training the artificial intelligence recognition module by an AI trainer in step two of the method for determining whether a safety rope is being used improperly, as described in this embodiment, is as follows:

[0036] Step 2: 1. Establish a descriptive model of the construction workers and input the model into the artificial intelligence recognition module so that the artificial intelligence recognition module can identify the construction workers at the construction site.

[0037] Step 22: Establish a descriptive model of the safety rope and input the model into the artificial intelligence recognition module so that the artificial intelligence recognition module can recognize the safety rope;

[0038] Steps two and three: The AI ​​trainer trains the AI ​​recognition module to identify safety ropes of various specifications (purposes);

[0039] Step 24: The AI ​​trainer trains the AI ​​recognition module to determine the working height and sets and modifies the minimum height for the use of safety ropes according to the different requirements of various industries and fields.

[0040] Step 25: The AI ​​trainer trains the AI ​​recognition module to identify dangerous scenarios where construction workers are not using safety ropes at a fixed working height;

[0041] Step 26: The AI ​​trainer trains the AI ​​recognition module to identify unsafe scenarios where the safety rope is used with a low attachment point and a high attachment point.

[0042] Step 27: The AI ​​trainer trains the AI ​​recognition module to identify whether the knot of the safety rope is located in a safe position on the construction worker, thereby completing the recognition training of the AI ​​recognition module.

[0043] In this specific implementation, an AI trainer is used to train the AI ​​recognition module, which enables the AI ​​recognition module to accurately identify construction workers, safety ropes, the position of the safety ropes on the construction workers, and the location where the safety ropes are attached, thus avoiding omissions and misjudgments.

[0044] Specific implementation method four: Combination Figure 1This embodiment further defines the judgment method described in Specific Embodiment Three. In this embodiment, a method for determining whether a safety rope is being used improperly is described. In step two, the artificial intelligence recognition module is trained using a description model of construction workers. During training, through continuous training of human vision and continuous correction of the construction worker model, the vision of the artificial intelligence recognition module can correctly identify construction workers at the work site.

[0045] Specific Implementation Method Five: Combining Figure 1 This embodiment further defines the judgment method described in Specific Embodiment Three. This embodiment provides a method for determining whether a safety rope is being used improperly. In step two, the artificial intelligence recognition module is trained using a safety rope description model. During training, the safety rope description model is tied to the construction worker's description model, and knots are tied at both ends of the safety rope model. Through continuous training of human vision and continuous correction of the safety rope model, the artificial intelligence recognition module can correctly identify the location where the safety rope is tied on the construction worker.

[0046] Specific Implementation Method Six: Combination Figure 1 This embodiment further defines the judgment method described in Specific Embodiment 1. This embodiment describes a method for determining whether a safety rope is being used improperly. The artificial intelligence recognition module is connected to a mobile phone via a wireless signal. If the artificial intelligence recognition module identifies a dangerous scene, it will transmit an alarm signal to the mobile phone to issue a warning.

[0047] In this specific implementation, an artificial intelligence recognition module is connected to a mobile phone via a wireless signal. If the artificial intelligence recognition module identifies a dangerous scene, it will transmit an alarm signal to the mobile phone to issue a warning, thereby realizing human-computer interaction and improving supervision efficiency.

[0048] Specific implementation method seven: Combination Figure 1 This embodiment is a further limitation of the judgment method described in Specific Embodiment 1. The method described in this embodiment can determine whether a safety rope is used illegally. In step one, multiple cameras are deployed and installed at the construction site to monitor and photograph the construction site without blind spots.

[0049] This specific implementation method involves deploying multiple cameras at the construction site to provide comprehensive monitoring and filming, preventing any omissions. It also allows for simultaneous monitoring of multiple construction site images displayed on the command center's video wall. Any violations can be documented and trigger an alarm, resolving the issues of omissions and oversights inherent in manual inspections.

Claims

1. A method for determining whether a safety rope has been used improperly, characterized in that: The specific method is as follows: Step 1: First, deploy and install n cameras at the construction site, where n is a positive integer, and connect the video signal output of the cameras to the video signal input of the artificial intelligence recognition module through wires; Step 2: Train the AI ​​recognition module through an AI trainer; Step 3: After completing the training of the artificial intelligence recognition module, record or photograph the environment and construction personnel at the construction site through the camera, and transmit the video signal to the artificial intelligence recognition module in real time; based on the data processing of the video or photo by the artificial intelligence recognition module, manually identify the height of the construction personnel and the height of people in the surrounding environment, and determine the height of the working surface. Step 4: Use the trained artificial intelligence recognition module to determine whether there is a phenomenon of low hanging and high use of the safety rope in the video or photo. If there is, the artificial intelligence recognition module will transmit an alarm signal to the alarm device to issue an alarm, and the artificial intelligence recognition module will archive the video or photo; if there is no such phenomenon, continue monitoring. Step 5: Use the trained artificial intelligence recognition module to determine the knot position of the safety rope in the video or photo. If the knot position of the safety rope is far away from the worker's waist, the artificial intelligence recognition module will transmit an alarm signal to the alarm device to issue a warning; and the artificial intelligence recognition module will archive the video or photo; if it does not exist, monitoring will continue. The specific method for training the AI ​​recognition module by an AI trainer in step two is as follows: Step 2:

1. Establish a descriptive model of the construction workers and input the model into the artificial intelligence recognition module so that the artificial intelligence recognition module can identify the construction workers at the construction site. Step 22: Establish a descriptive model of the safety rope and input the model into the artificial intelligence recognition module so that the artificial intelligence recognition module can recognize the safety rope; Steps two and three: The AI ​​trainer trains the AI ​​recognition module to identify safety ropes of various specifications. Step 24: The AI ​​trainer trains the AI ​​recognition module to determine the working height and sets and modifies the minimum height for the use of safety ropes according to the different requirements of various industries and fields. Step 25: The AI ​​trainer trains the AI ​​recognition module to identify dangerous scenarios where construction workers are not using safety ropes at a fixed working height; Step 26: The AI ​​trainer trains the AI ​​recognition module to identify unsafe scenarios where the safety rope is used with a low attachment point and a high attachment point. Step 27: The AI ​​trainer trains the AI ​​recognition module to identify whether the knot of the safety rope is located in a safe position on the construction worker, thus completing the recognition training of the AI ​​recognition module.

2. The method for determining whether a safety rope has been used improperly, as described in claim 1, is characterized in that: The number of cameras, n, is 2 ≤ n ≤ 50.

3. The method for determining whether a safety rope has been used improperly, as described in claim 1, is characterized in that: In step two, the artificial intelligence recognition module is trained using a descriptive model of construction workers. Through continuous training of human vision and continuous correction of the construction worker model, the vision of the artificial intelligence recognition module can correctly identify construction workers on the work site.

4. The method for determining whether a safety rope has been used improperly, as described in claim 1, is characterized in that: In step two, the description model of the safety rope is used to train the artificial intelligence recognition module. During training, the description model of the safety rope is tied to the description model of the construction worker, and the two ends of the safety rope model are knotted. Through continuous training of human vision and continuous correction of the safety rope model, the vision of the artificial intelligence recognition module can correctly identify the position of the safety rope tied on the construction worker.

5. The method for determining whether a safety rope has been used improperly, as described in claim 1, is characterized in that: The AI ​​recognition module connects to the mobile phone via wireless signal. If the AI ​​recognition module identifies a dangerous scene, it will transmit an alarm signal to the mobile phone to issue a warning.

6. The method for determining whether a safety rope has been used improperly, as described in claim 1, is characterized in that: In step one, multiple cameras are deployed and installed at the construction site to monitor and capture the construction site without blind spots.

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