A safety warning method, system and terminal for safety visual detection camera

Abstract

The present invention relates to a safety warning method, system and terminal for a security visual detection camera, and relates to the field of image recognition technology, which includes obtaining a warning image; judging whether there is a person according to the warning image; when there is a person, determining the person's clothing according to the warning image; determining the person's access level according to the person's clothing; determining a warning area according to the warning image; determining the warning level of the area according to the warning area; when the access level is lower than the warning level, controlling a preset alarm device to issue a safety alarm. The present application has the effect of improving the convenience of using a security visual detection camera and reducing the false alarm of the security visual detection camera.

Description

Technical Field

[0001] The present invention relates to the field of image recognition technology, and in particular to a safety early warning method, system and terminal for a safety visual detection camera. Background Art

[0002] A security visual detection camera is a device used for monitoring and detection. This type of camera usually has the characteristics of high resolution, low latency and high accuracy, and can provide reliable monitoring and alarm functions in complex environments.

[0003] In the prior art, security visual detection cameras are often used in industrial environments. Security visual detection cameras can be used to monitor the entry and exit of personnel in dangerous areas, thereby promptly issuing an alarm when personnel mistakenly enter the dangerous area, and controlling the equipment in the dangerous area to stop running to ensure the safety of personnel. Dangerous areas are generally equipped with professional maintenance personnel, and maintenance personnel are generally equipped with special identity cards to reduce the situation where security visual detection cameras detect maintenance personnel and issue an alarm.

[0004] When maintenance personnel do not wear identity cards, it is easy for the safety visual detection camera to sound an alarm and control the equipment in the danger zone to stop urgently, which will reduce the service life of the equipment or even damage the equipment, causing great economic losses. Summary of the invention

[0005] In order to improve the convenience of using a security visual detection camera and reduce the false alarms of the security visual detection camera, the present invention provides a security early warning method, system and terminal for a security visual detection camera.

[0006] In a first aspect, the present invention provides a safety warning method for a safety visual detection camera, which adopts the following technical solution:

[0007] A safety early warning method for a safety visual detection camera, comprising:

[0008] Obtain early warning images;

[0009] Determine whether there is a person based on the warning image;

[0010] When there are people, determine their clothing based on the warning image;

[0011] Determine the level of access for personnel based on their clothing;

[0012] Determine the warning area based on the warning image;

[0013] Determine the warning level of the region according to the warning area;

[0014] When the access level is lower than the warning level, the preset alarm device is controlled to sound a security alarm.

[0015] By adopting the above technical solution, in an industrial environment, personnel in different positions generally wear different clothes. When maintenance personnel enter a dangerous area, their identity can be confirmed from their clothes, thereby reducing false alarms of safety visual detection cameras and improving the convenience of using safety visual detection cameras.

[0016] Optionally, also include:

[0017] When the access level is lower than the warning level, the number of personnel is determined based on the warning image;

[0018] When the number of people exceeds a preset individual threshold, the distribution of people is determined based on the early warning image;

[0019] Determine the group's direction based on early warning images;

[0020] Determine the leadership position of the group leader based on personnel distribution and group direction;

[0021] Determine the leadership clothing of the group leader based on the leadership position;

[0022] Determine the level of the group based on the leader’s clothing;

[0023] When the group level is lower than the warning level, the preset alarm device is controlled to sound a security alarm.

[0024] By adopting the above technical solution, when multiple people enter a dangerous area together, the leader among the people can be judged by the direction and distribution of the people, and then whether the leader is a maintenance personnel can be judged based on their clothing. This will reduce the situation where professional maintenance personnel lead non-professionals into dangerous areas and cause false alarms of safety visual detection cameras, thereby improving the convenience of using safety visual detection cameras.

[0025] Optionally, a group management method is also included, and the group management method includes:

[0026] When the group level is below the warning level, the verification path is determined based on the leadership position;

[0027] Control the preset UAV to fly to the leader position according to the verification path, and control the preset UAV to issue a preset verification prompt voice;

[0028] After the verification prompt voice, control the preset drone to obtain the verification image of the group leader;

[0029] Extracting verification features according to the verification image;

[0030] Determine the calibration level based on the calibration characteristics;

[0031] When the verification level is lower than the warning level, the preset alarm device is controlled to issue a safety alarm, and the preset drone is controlled to issue a preset expulsion prompt voice.

[0032] By adopting the above technical solution, when a large number of people enter the danger zone at the same time, it is easy for other people to block the camera from obtaining the image of the leader, making it difficult to identify the leader's clothes. At this time, the leader's facial image is obtained by the drone to further determine the leader's identity, thereby reducing the situation where professional maintenance personnel lead non-professionals into the danger zone, causing false alarms of the safety visual detection camera, and improving the convenience of using the safety visual detection camera.

[0033] Optionally, the group management method further includes:

[0034] When the verification level is not lower than the warning level, the leadership threshold of the group leader is determined according to the verification level;

[0035] When the number of personnel is higher than the leadership threshold, the outlier position of the outlier is determined based on the leadership position and personnel distribution;

[0036] Determine monitoring paths based on leadership and outlier positions;

[0037] Control the preset UAV to fly to the out-of-group location according to the monitoring path, and obtain the out-of-group image of the group;

[0038] Determine the direction of people based on outlier images;

[0039] Calculate the difference between the individual's direction and the group's direction and define it as the deviation direction;

[0040] When the deviation direction exceeds the preset following interval, the preset drone is controlled to issue a preset out-of-group warning voice.

[0041] By adopting the above technical solution, when the maintenance personnel are led by too many non-professionals, it is easy for the maintenance personnel to be unable to fully control the behavior of all non-professionals, which may lead to accidents caused by non-professionals accidentally touching the surface. Uncontrolled personnel can be identified by their movements, and reminders can be given through drones to reduce the situation where non-professionals accidentally touch the surface and cause accidents.

[0042] Optionally, the group management method further includes:

[0043] When the number of personnel is higher than the leadership threshold, the difference between the number of personnel and the leadership threshold is calculated and defined as the number of over-management;

[0044] Calculate the quotient of the number of super-controllers and the preset monitoring threshold, and round it up to get the monitoring number;

[0045] Determine management distance based on leadership position, leadership threshold, and personnel distribution;

[0046] Determine the distribution of super-management according to personnel distribution and management distance;

[0047] Determine monitoring partitions based on super-management distribution and monitoring quantity;

[0048] Determine the zone location of stray persons in the zone based on the monitored zones;

[0049] Determine the monitoring path based on the partition location.

[0050] By adopting the above technical solution, the area that a single drone can control is limited. When there are too many non-professionals led by maintenance personnel, the uncontrolled personnel will be divided into zones, and then drones will be dispatched according to the zones to control the non-professionals, thereby improving the control of non-professionals and reducing the situation where accidents are caused by accidental touch by non-professionals.

[0051] Optionally, it also includes a wearing management method, and the wearing management method includes:

[0052] When the verification level is not lower than the warning level, protective clothing is determined according to the warning area;

[0053] Determine whether personnel are fully dressed based on protective clothing;

[0054] When personnel clothing is incomplete, determine the missing clothing based on protective clothing and personnel clothing;

[0055] Generate clothing reminder voice according to missing clothing, and determine the person's location based on the warning image;

[0056] Determine prompt paths based on leadership and personnel positions;

[0057] Control the preset drone to fly to the personnel's location according to the prompted path, and control the drone to issue clothing prompt voice.

[0058] By adopting the above technical solution, it is generally necessary to wear corresponding protective equipment when entering a dangerous area, and whether the person is fully dressed can be judged from the image, so that the drone can be used to prompt when the person is not fully dressed or is dressed incorrectly.

[0059] Optionally, the wearing management method further includes:

[0060] When personnel are incompletely clothed, determine the type of danger in the area based on the warning area;

[0061] Determine primary clothing based on hazard type and protective clothing;

[0062] Determine whether the missing clothing includes the main clothing;

[0063] When the missing clothing includes the main clothing, the indication angle is determined based on the person’s position and the missing clothing;

[0064] According to the indication angle, the indication device preset on the drone is controlled to indicate the clothes that the person is not wearing, and the preset drone is controlled to issue a preset no-entry voice prompt.

[0065] By adopting the above technical solution, the protective equipment required to enter the dangerous area is generally divided into conventional equipment and professional equipment for dangerous areas. When personnel do not wear professional equipment, the probability of accidents will greatly increase. The wearing status of personnel's professional equipment can be judged from the image, and a drone will be used to prompt when the professional equipment is not worn or worn incorrectly.

[0066] Optionally, a personnel protection method is also included, and the personnel protection method includes:

[0067] When the alarm device sounds a security alarm, an alarm image is acquired;

[0068] Determine the mobile location based on the alarm image;

[0069] Determine whether the person is far away from the warning area based on the person's location, movement location and warning area;

[0070] When the personnel do not leave the warning area, the warning path is determined according to the moving position and the warning area;

[0071] According to the warning path, the preset UAV is controlled to fly between the personnel and the center of the danger zone, and the flash device preset on the UAV is controlled to issue a flash warning to the personnel.

[0072] By adopting the above technical solution, when a person still moves towards a dangerous area after an alarm is sounded, the person is judged to be a dangerous person. At this time, the flash device on the drone is used to flash a warning to the person, and the security personnel are notified to handle it in time.

[0073] In the second aspect, the present application provides a safety visual detection camera safety warning system, which adopts the following technical solutions:

[0074] A safety visual detection camera safety warning system, comprising:

[0075] An acquisition module, used for acquiring early warning images, verification images, outlier images and alarm images;

[0076] A memory, used to store a program of any of the above-mentioned safety visual detection camera safety warning methods;

[0077] The program in the memory can be loaded and executed by the processor.

[0078] In a third aspect, the present application provides a smart terminal, which adopts the following technical solution:

[0079] A smart terminal includes a memory and a processor, wherein the memory stores a computer program that can be loaded by the processor and execute any one of the above-mentioned safety visual detection camera safety warning methods.

[0080] By adopting the above technical solution, in an industrial environment, personnel in different positions generally wear different clothes. When maintenance personnel enter a dangerous area, their identity can be confirmed from their clothes, thereby reducing false alarms of safety visual detection cameras and improving the convenience of using safety visual detection cameras.

[0081] In summary, the present application includes at least one of the following beneficial technical effects:

[0082] 1. In industrial environments, personnel in different positions generally wear different clothes. When maintenance personnel enter dangerous areas, their identities can be confirmed from their clothes, thereby reducing false alarms from safety visual detection cameras and improving the convenience of using safety visual detection cameras.

[0083] 2. When multiple people enter a dangerous area together, the leader among the people can be judged by their direction and distribution, and then whether the leader is a maintenance personnel can be judged based on their clothing. This will reduce the situation where professional maintenance personnel lead non-professional personnel into dangerous areas, causing false alarms of safety visual detection cameras, and improve the convenience of using safety visual detection cameras;

[0084] 3. When there are a large number of people entering the danger zone at the same time, it is easy for other people to block the camera from obtaining the image of the leader, making it difficult to identify the leader's clothing. At this time, the leader's facial image is obtained through the drone to further determine the leader's identity, thereby reducing the situation where professional maintenance personnel lead non-professionals into the danger zone, causing false alarms of the safety visual detection camera, and improving the convenience of using the safety visual detection camera. BRIEF DESCRIPTION OF THE DRAWINGS

[0085] Figure 1 It is a process of a safety warning method of a safety visual detection camera Figure 1 ;

[0086] Figure 2 It is a process of a safety warning method of a safety visual detection camera Figure 2 ;

[0087] Figure 3 It is the process of group management method Figure 1 ;

[0088] Figure 4 It is the process of group management method Figure 2 ;

[0089] Figure 5 It is the process of group management method Figure 3 ;

[0090] Figure 6 It is the process of wearing management method Figure 1 ;

[0091] Figure 7 It is the process of wearing management method Figure 2 ;

[0092] Figure 8 It is a flow chart of the personnel protection method. DETAILED DESCRIPTION

[0093] In order to make the purpose, technical solution and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0094] The embodiment of the present invention discloses a safety warning method for a security visual detection camera. In an industrial environment, personnel in different positions generally wear different clothes. The present invention is used to confirm the identity of the maintenance personnel from their clothes when the maintenance personnel enter a dangerous area, thereby reducing the false alarm of the security visual detection camera and improving the convenience of using the security visual detection camera.

[0095] Reference Figure 1 , a safety early warning method for a safety visual detection camera, comprising:

[0096] Step 100: Acquire a warning image.

[0097] The warning image refers to the picture of the dangerous area obtained by the safety visual detection camera. The method of obtaining the warning image is selected by the staff according to the actual situation and will not be elaborated here.

[0098] Step 101: Determine whether there is a person based on the warning image.

[0099] Image recognition technology can be used to determine whether there is a person in the warning image. The method of determining whether there is a person is common knowledge among people in this field and will not be elaborated here.

[0100] Step 102: When there is a person, determine the person's clothing based on the warning image.

[0101] The presence of personnel means that someone has entered the danger zone. Personnel clothing refers to the type of clothing worn by personnel entering the danger zone. Personnel clothing can be identified through image recognition technology. The method for identifying personnel clothing is common knowledge among people in this field and will not be elaborated here.

[0102] Step 103: Determine the personnel's access level based on the personnel's clothing.

[0103] The access level refers to a pre-set value used to show the professional level of personnel. The more professional knowledge a person possesses and the richer experience he has, the higher his access level. Professional knowledge refers to the instructions required to enter the warning area. The identity of the personnel, such as the masses, ordinary workers, and maintenance personnel, can be judged based on their clothing. Then, the access level corresponding to the personnel's clothing can be obtained from the preset access level table based on the personnel's identity. The identity of the personnel can be judged through image recognition technology. The access level table refers to a relationship table that records the identity of the personnel and their corresponding access levels in advance.

[0104] Step 104: Determine the warning area according to the warning image.

[0105] The warning area refers to the scope and type of the dangerous area monitored by the safety visual detection camera. The type of the warning area refers to the physical quantities such as electricity and temperature that need to be specially protected in the warning area. The dangerous position of the dangerous area can be determined by image recognition technology, and then the warning area can be obtained by querying from the warning area table according to the dangerous position. The warning area table refers to a relationship table that records the scope and type of the dangerous position and its corresponding dangerous area.

[0106] Step 105: Determine the warning level of the area according to the warning area.

[0107] The warning level refers to a pre-set value used to show the minimum professional level of personnel required to enter the danger zone. The more professional knowledge personnel need to master to enter the danger zone, and the greater the difference between the physical quantities that need to be protected in the danger zone and the physical quantities in the normal environment, the higher the access level.

[0108] Step 106: When the access level is lower than the warning level, a preset alarm device is controlled to issue a security alarm.

[0109] The alarm device refers to a device installed in the dangerous area and used to light up to remind people to stay away. The alarm device is selected by the staff according to the actual situation and will not be described in detail here. If the access level is lower than the warning level, it means that the professional knowledge of the personnel is not enough to enter and exit the dangerous area safely. At this time, the alarm device will issue a safety alarm to warn people to stay away from the dangerous area in time, thereby reducing the situation where non-professionals mistakenly enter the dangerous area.

[0110] Reference Figure 2 , a safety early warning method for a safety visual detection camera, further comprising:

[0111] Step 107: When the admission level is lower than the warning level, the number of personnel is determined according to the warning image.

[0112] The number of personnel refers to the total number of personnel entering the danger zone. The number of personnel can be obtained through image recognition technology. The method for identifying the number of personnel is common knowledge among people in this field and will not be elaborated here.

[0113] Step 108: When the number of people exceeds a preset individual threshold, determine the distribution of people according to the early warning image.

[0114] The individual threshold refers to the maximum number of people entering the danger zone. The individual threshold is generally 1. The individual threshold is selected by the staff according to the actual situation and will not be described in detail here. The number of people exceeding the individual threshold means that there are more people entering the danger zone. Personnel distribution refers to the set of positions of all people in the warning image. Personnel distribution can be obtained through image recognition technology. The method for determining personnel distribution is common knowledge among people in this field and will not be described in detail here.

[0115] Step 109: Determine the direction of the group based on the warning image.

[0116] The group direction refers to the main moving direction of the personnel. The center position of the personnel can be identified through image recognition technology, and then the group direction can be judged according to the change of the center position. The method for determining the group direction is common knowledge among people in this field and will not be elaborated here.

[0117] Step 110: Determine the leadership position of the group leader based on personnel distribution and group direction.

[0118] The leadership position refers to the position of the person who walks in the front of the group. The method of determining the leadership position is common knowledge among people in this field and will not be elaborated here.

[0119] Step 111: Determine the leadership attire of the group leader based on the leadership position.

[0120] Leadership clothing refers to the type of clothing worn by people in leadership positions. Leadership clothing can be identified through image recognition technology. The identification method of leadership clothing is common knowledge among people in this field and will not be elaborated here.

[0121] Step 112: Determine the level of the group based on the leader’s clothing.

[0122] Group level refers to the entry level of personnel in leadership positions. The method for determining group level can be referred to the reference method for entry level mentioned above and will not be elaborated here.

[0123] Step 113: When the group level is lower than the warning level, the preset alarm device is controlled to send out a safety alarm.

[0124] A group level lower than the warning level means that the professional knowledge of the person in the leadership position is not enough to enter and exit the danger zone safely. At this time, a safety alarm is issued through the alarm device to warn people to stay away from the danger zone in time, thereby reducing the situation where non-professionals mistakenly enter the danger zone.

[0125] When multiple people enter a dangerous area together, the leader among the people can be judged by their direction and distribution, and whether the leader is a maintenance personnel can be judged based on their clothing. This will reduce the situation where professional maintenance personnel lead non-professionals into dangerous areas, causing false alarms of safety visual detection cameras, and improve the convenience of using safety visual detection cameras.

[0126] Reference Figure 3 , group management methods include:

[0127] Step 200: When the group level is lower than the warning level, the verification path is determined according to the leadership position.

[0128] The drone refers to a device used to further verify the identity of a person. The drone is selected by the staff according to the actual situation and will not be described in detail here. The verification path refers to the route that the drone flies to the leader's position. The verification path can be automatically generated from the control program of the drone according to the leader's position. The method of generating the verification path is common knowledge among people in this field and will not be described in detail here.

[0129] Step 201: Control a preset UAV to fly to a leadership position according to a verification path, and control the preset UAV to issue a preset verification prompt voice.

[0130] Verification prompt voice refers to the voice information used to notify the group leader to face the drone so that the drone can obtain the facial image of the group leader. The verification prompt voice is selected by the staff according to the actual situation and will not be described here. When it is judged from the clothing that the professional knowledge of the person in the leadership position is not enough to safely enter and exit the dangerous area, the drone will fly to the leadership position to further verify the identity of the group leader.

[0131] Step 202: After the verification prompt voice, control the preset drone to obtain the verification image of the group leader.

[0132] The verification image is the facial image of the group leader obtained after the drone issues a verification prompt voice. The verification image can be obtained through the camera on the drone. The method for obtaining the verification image is selected by the staff according to the actual situation and will not be elaborated here.

[0133] Step 203: extracting verification features according to the verification image.

[0134] Verification features refer to feature information extracted during face recognition, including the shape, size, positional relationship of facial contours, eyes, nose, mouth and other parts. The method of extracting verification features is common knowledge among people in this field and will not be elaborated here.

[0135] Step 204: Determine the verification level according to the verification characteristics.

[0136] The verification level refers to the access level of the personnel corresponding to the verification characteristics. The personnel identity can be first identified from the preset personnel database through the verification characteristics, and then the verification level can be obtained by querying from the preset access level table based on the personnel identity, where the personnel database refers to a database that pre-records all personnel and their corresponding verification characteristics.

[0137] Step 205: When the verification level is lower than the warning level, the preset alarm device is controlled to issue a safety alarm, and the preset drone is controlled to issue a preset expulsion prompt voice.

[0138] The expulsion prompt voice refers to the voice information used to notify the group to leave the dangerous area. The expulsion prompt voice is selected by the staff according to the actual situation and will not be described in detail here.

[0139] If the verification level is lower than the warning level, it means that the professional knowledge of the person in the leadership position is not enough to enter and exit the danger zone safely. At this time, a safety alarm is issued through the alarm device to warn the personnel to stay away from the danger zone in time, and an expulsion prompt voice is played through the drone, thereby reducing the situation where non-professionals mistakenly enter the danger zone.

[0140] Reference Figure 4 , group management methods also include:

[0141] Step 206: When the verification level is not lower than the warning level, the leadership threshold of the group leader is determined according to the verification level.

[0142] An inspection level not lower than the warning level represents that the professional knowledge of the personnel in the leadership position is sufficient to safely enter and exit the dangerous area. The leadership threshold refers to the maximum number of non-professionals that can be controlled by professional maintenance personnel. The higher the access level of the maintenance personnel, the larger the leadership threshold. The leadership threshold can be obtained from the leadership threshold corresponding table. The leadership threshold corresponding table refers to a table that records the access levels and their corresponding leadership thresholds.

[0143] Step 207: When the number of personnel is higher than the leadership threshold, the outlier position of the outlier is determined according to the leadership position and personnel distribution.

[0144] The number of people higher than the leadership threshold means that there are outliers in the group who are not controlled by the group leader. Generally, the farther away from the group leader, the lower the degree of control by the group leader. The outlier position refers to the position of the person farthest from the leadership position in the group. The method for determining the outlier position is common knowledge among people in this field and will not be elaborated here.

[0145] Step 208: Determine a monitoring path according to the leading position and the outlier position.

[0146] The monitoring path refers to the route that the UAV flies from the leading position to the outlier position. The monitoring path can be automatically generated from the control program supporting the UAV according to the leading position. The method for generating the monitoring path is common knowledge among people in this field and will not be elaborated here.

[0147] Step 209: Control the preset UAV to fly to the outlier position according to the monitoring path, and obtain the outlier image of the group.

[0148] Outlier images refer to pictures of a group taken by a drone at an outlier position. Outlier images can be obtained through the camera on the drone. The method for obtaining outlier images is selected by the staff according to the actual situation and will not be elaborated here.

[0149] Step 210: Determine the direction of the person based on the outlier image.

[0150] The direction of a person refers to the direction in which the person moves. The position changes of the person can be identified through image recognition technology to determine the direction of the person. The method for determining the direction of a person is common knowledge among people in this field and will not be elaborated here.

[0151] Step 211: Calculate the difference between the individual's direction and the group's direction, and define it as the offset direction.

[0152] The deviation direction refers to the difference between the direction of an individual and the direction of a group. The deviation direction shows the degree to which a person is controlled.

[0153] Step 212: When the deviation direction exceeds the preset following interval, the preset UAV is controlled to emit a preset out-of-group prompt voice.

[0154] The out-of-group prompt voice refers to the voice information used to notify personnel to follow the group in time. The out-of-group prompt voice is selected by the staff according to the actual situation and will not be described in detail here. The following interval refers to the offset direction interval in which personnel move with the group. The following interval is selected by the staff according to the actual situation and will not be described in detail here. If the offset direction exceeds the following interval, it means that the personnel do not move with the group at this time, that is, the personnel are less controlled. At this time, the out-of-group prompt voice is played by the drone to prompt the out-of-group personnel to follow the group in time, and remind the group leader to pay attention to the out-of-group personnel to reduce the situation where the out-of-group personnel mistakenly enter the dangerous area.

[0155] Reference Figure 5 , group management methods also include:

[0156] Step 213: When the number of personnel is higher than the leadership threshold, the difference between the number of personnel and the leadership threshold is calculated and defined as the number of excess management.

[0157] The number of over-managers refers to the number of people in a group who exceed the leadership threshold. The number of over-managers shows the number of potential outliers.

[0158] Step 214: Calculate the quotient of the number of super-pipes and the preset monitoring threshold, and round up to obtain the monitoring number.

[0159] The monitoring threshold refers to the maximum number of people that a single drone can control. The monitoring threshold is selected by the staff based on the actual situation and will not be elaborated here. The monitoring number is the number of drones required to control all potential stray persons through drones.

[0160] Step 215: Determine the management distance according to the leadership position, leadership threshold and personnel distribution.

[0161] The degree of control that a group leader has over people generally decreases as the distance between the people and the group leader increases. The management distance refers to the farthest distance that a group leader can control over people. The people can be sorted from small to large based on the distance between them and the leadership position in the personnel distribution, and then the people with the sequence number of the leadership threshold are selected from the sorted people and the distance between them and the leadership position is read as the management distance.

[0162] Step 216: Determine the super-management distribution according to the personnel distribution and the management distance.

[0163] The over-manager distribution refers to the location information of all personnel whose distance from the group leader exceeds the management distance. The method for determining the over-manager distribution is common knowledge among personnel in this field and will not be elaborated here.

[0164] Step 217: Determine the monitoring partition according to the super-management distribution and the monitoring quantity.

[0165] Monitoring zones refer to zones where multiple drones are used to monitor and control personnel in a super-control distribution. The number of super-controllers in the super-control distribution can be read first, and then the quotient of the number of super-controllers and the number of monitoring can be calculated to obtain the number of personnel in each zone. Finally, the monitoring zones are defined based on the number of personnel. The method for determining monitoring zones is common knowledge among people in this field and will not be elaborated here.

[0166] Step 218: Determine the zone location of the stray person in the zone based on the monitored zone.

[0167] The partition position refers to the outlier position within each monitoring partition. The method for determining the partition position refers to the method for determining the outlier position mentioned above.

[0168] Step 219: Determine the monitoring path according to the partition location.

[0169] The monitoring path is the route for dispatching drones according to the zone locations. The area that a single drone can control is limited. When there are too many non-professionals led by maintenance personnel, the uncontrolled personnel will be divided into zones, and then drones will be dispatched according to the zones to control the non-professionals, thereby improving the control of non-professionals and reducing the situation where non-professionals accidentally touch the zone and cause accidents.

[0170] Reference Figure 6 , clothing management methods include:

[0171] Step 300: When the verification level is not lower than the warning level, protective clothing is determined according to the warning area.

[0172] Protective clothing refers to the protective equipment such as helmets, protective clothing, gloves, etc. that need to be worn when entering the warning area. The required protective clothing varies depending on the type of warning area. For example, when the warning area is electricity, insulating helmets, insulating clothing, insulating gloves and other protective equipment are required. Protective clothing can be obtained from the protective clothing relationship table. The protective clothing relationship table refers to a relationship table that records different warning areas and their corresponding protective clothing.

[0173] Step 301: Determine whether the personnel's clothing is complete based on the protective clothing.

[0174] Image recognition technology can be used to determine whether a person is wearing protective clothing correctly. The method for determining protective clothing is common knowledge among people in the field and will not be elaborated here.

[0175] Step 302: When the personnel clothing is incomplete, the missing clothing is determined based on the protective clothing and the personnel clothing.

[0176] Incomplete clothing of personnel means that the personnel have worn less or wrong protective clothing. Missing clothing means that the personnel have worn less or wrong protective clothing. Missing clothing can be determined by image recognition technology. The method for determining missing clothing is common knowledge among people in this field and will not be elaborated here.

[0177] Step 303: Generate clothing reminder voice according to the missing clothing, and determine the person's location according to the warning image.

[0178] Clothing reminder voice refers to voice information used to remind people that they are wearing less or the wrong protective clothing. Clothing reminder voice can be automatically generated through a big data model. The method of generating clothing reminder voice is common knowledge in this field and will not be described in detail here. Personnel position refers to the coordinate position of a person. Personnel position can be obtained through image recognition technology. The method of determining personnel position is common knowledge in this field and will not be described in detail here.

[0179] Step 304: Determine a prompt path according to the leader's position and the personnel's position.

[0180] The prompt path refers to the route that the UAV flies from the leader's position to the personnel's position. The prompt path can be automatically generated from the control program supporting the UAV according to the leader's position and the personnel's position. The method for generating the prompt path is common knowledge among people in this field and will not be elaborated here.

[0181] Step 305: Control the preset drone to fly to the personnel's location according to the prompt path, and control the drone to issue a clothing prompt voice.

[0182] When entering a dangerous area, it is generally necessary to wear appropriate protective equipment. The image can be used to determine whether the person is fully dressed, so that the drone can provide reminders when the person is not fully dressed or is dressed incorrectly.

[0183] Reference Figure 7 , clothing management methods also include:

[0184] Step 306: When the personnel are not fully clothed, the danger type of the area is determined based on the warning area.

[0185] The hazard type is the type of warning area extracted from the warning area. The method of extracting the hazard type is selected by the staff according to the actual situation and will not be elaborated here.

[0186] Step 307: Determine primary clothing according to the hazard type and protective clothing.

[0187] Main clothing refers to protective equipment for hazardous types in protective clothing. For example, when the hazardous type is electricity, the required protective clothing generally includes insulating helmets, insulating clothing, insulating gloves, protective glasses, safety shoes and reflective vests, etc. Among them, insulating helmets, insulating clothing and insulating gloves are the main clothing in the power environment. The method for determining the main clothing is common knowledge among people in this field and will not be elaborated here.

[0188] Step 308: Determine whether the missing clothing includes main clothing.

[0189] The probability of an accident occurring to a person in a dangerous area can be determined by whether the missing clothing includes the main clothing. The method for determining the main clothing is common knowledge among those skilled in the art and will not be elaborated on here.

[0190] Step 309: When the missing clothing includes the main clothing, the indication angle is determined according to the person's position and the missing clothing.

[0191] The indicator device refers to a device installed on the drone to indicate missing clothing. The indicator device generally uses a laser indicator light. The indicator device is selected by the staff according to the actual situation and will not be described in detail here. Missing clothing includes main clothing, which means that the probability of an accident occurring in a dangerous area is high. The indicator angle refers to the angle of the main clothing that the indicator device indicates that the person is wearing less or wearing the wrong clothing. The method for determining the indicator angle is common knowledge among people in this field and will not be described in detail here.

[0192] Step 310: Control the indicating device preset on the drone to indicate the clothes that the person is not wearing according to the indicating angle, and control the preset drone to issue a preset no-entry voice prompt.

[0193] No-entry voice prompt refers to the voice information used to notify personnel that they are wearing less or the wrong main clothing. The no-entry voice prompt is selected by the staff according to the actual situation and will not be described here. The protective equipment required to enter the dangerous area is generally divided into conventional equipment and main equipment for dangerous areas. When the personnel do not wear the main equipment, the probability of an accident will greatly increase. The wearing of the main equipment of the personnel will be judged from the image, and the drone will indicate when the main equipment is not worn or worn incorrectly, and the no-entry voice prompt will be used to prevent the personnel from continuing to enter the dangerous area.

[0194] Reference Figure 8 , personnel protection methods include:

[0195] Step 400: After the alarm device issues a security alarm, an alarm image is acquired.

[0196] The alarm image refers to a picture of the dangerous area obtained after the alarm device sends out a safety alarm. The method of obtaining the alarm image is selected by the staff according to the actual situation and will not be elaborated here.

[0197] Step 401: Determine the moving position according to the alarm image.

[0198] The mobile position refers to the position of the person in the alarm image, and the mobile position can be obtained through image recognition technology. The method for determining the mobile position is common knowledge among people in this field and will not be elaborated here.

[0199] Step 402: Determine whether the person is far away from the warning area based on the person's location, movement location and warning area.

[0200] The direction of the person is determined from the change from the person's position to the moving position, and then the range of the warning area is used to determine whether the person is heading into the danger zone or out of the danger zone. When the person is heading out of the danger zone, it is determined that the person is away from the warning area.

[0201] Step 403: When the person is within the warning area, a warning path is determined according to the moving position and the warning area.

[0202] The fact that the person has not left the warning area means that the person is still going deep into the danger zone after the alarm device has issued a warning. At this time, the person is judged to be a dangerous person and needs further warning processing. The warning path refers to the route that the drone flies to the front of the dangerous person. The center position of the danger zone can be determined based on the warning area, and then the warning position located between the moving position and the center position can be determined based on the moving position and the center position. Finally, the warning path is automatically generated from the control program of the drone based on the warning position. The method for generating the warning path is common knowledge known to people in this field and will not be elaborated here.

[0203] Step 404: Control the preset UAV to fly between the personnel and the center of the danger zone according to the warning path, and control the flash device preset on the UAV to issue a flash warning to the personnel.

[0204] A flash device refers to a device installed on a drone to flash a warning light to dangerous persons to prevent them from going further into the dangerous area. The flash device generally uses a flashlight. The flash device is selected by the staff according to actual conditions and will not be elaborated here.

[0205] Based on the same inventive concept, an embodiment of the present invention provides a safety warning system for a safety visual detection camera, comprising:

[0206] An acquisition module, used for acquiring early warning images, verification images, outlier images and alarm images;

[0207] A memory, used to store a program of any of the above-mentioned safety visual detection camera safety warning methods;

[0208] The program in the memory can be loaded and executed by the processor.

[0209] Based on the same inventive concept, an embodiment of the present invention provides a smart terminal, including a memory and a processor, wherein the memory stores a computer program that can be loaded by the processor and execute any of the above-mentioned security visual detection camera safety warning methods.

[0210] Those skilled in the art can clearly understand that for the convenience and simplicity of description, only the division of the above-mentioned functional modules is used as an example. In actual applications, the above-mentioned functions can be assigned to different functional modules as needed, that is, the internal structure of the device is divided into different functional modules to complete all or part of the functions described above. The specific working process of the system, device and unit described above can refer to the corresponding process in the aforementioned method embodiment, and will not be repeated here.

[0211] The above is only a preferred embodiment of the present invention, and the protection scope of the present invention is not limited to the above embodiments. All technical solutions under the concept of the present invention belong to the protection scope of the present invention. It should be pointed out that for ordinary technicians in this technical field, some improvements and modifications without departing from the principle of the present invention should also be regarded as the protection scope of the present invention.

Claims

1. A safety warning method for a safety visual detection camera, characterized in that: include: Obtain early warning images; Determine whether there is a person based on the warning image; When there are people, determine their clothing based on the warning image; Determine the level of access for personnel based on their clothing; Determine the warning area based on the warning image; Determine the warning level of the region according to the warning area; When the access level is lower than the warning level, the preset alarm device is controlled to sound a security alarm; Also includes: When the access level is lower than the warning level, the number of personnel is determined based on the warning image; When the number of people exceeds a preset individual threshold, the distribution of people is determined based on the early warning image; Determine the group's direction based on early warning images; Determine the leadership position of the group leader based on personnel distribution and group direction; Determine the leadership clothing of the group leader based on the leadership position; Determine group hierarchy based on leader clothing; When the group level is lower than the warning level, the preset alarm device is controlled to sound a safety alarm; Also included is a group management method, the group management method comprising: When the group level is below the warning level, the verification path is determined based on the leadership position; Control the preset UAV to fly to the leader position according to the verification path, and control the preset UAV to issue a preset verification prompt voice; After the verification prompt voice, control the preset drone to obtain the verification image of the group leader; Extracting verification features according to the verification image; Determine the calibration level based on the calibration characteristics; When the verification level is lower than the warning level, the preset alarm device is controlled to issue a safety alarm, and the preset drone is controlled to issue a preset expulsion prompt voice.

2. A safety early warning method for a safety visual detection camera according to claim 1, characterized in that: The group management method further comprises: When the verification level is not lower than the warning level, the leadership threshold of the group leader is determined according to the verification level; When the number of personnel is higher than the leadership threshold, the outlier position of the outlier is determined based on the leadership position and personnel distribution; Determine monitoring paths based on leadership and outlier positions; Control the preset UAV to fly to the out-of-group location according to the monitoring path, and obtain the out-of-group image of the group; Determine the direction of people based on outlier images; Calculate the difference between the individual's direction and the group's direction and define it as the deviation direction; When the deviation direction exceeds the preset following interval, the preset drone is controlled to issue a preset out-of-group warning voice.

3. A safety warning method for a safety visual detection camera according to claim 2, characterized in that: The group management method further comprises: When the number of personnel is higher than the leadership threshold, the difference between the number of personnel and the leadership threshold is calculated and defined as the number of over-management; Calculate the quotient of the number of super-controllers and the preset monitoring threshold, and round it up to get the monitoring number; Determine management distance based on leadership position, leadership threshold, and personnel distribution; Determine the distribution of super-management according to personnel distribution and management distance; Determine monitoring partitions based on super-management distribution and monitoring quantity; Determine the zone location of stray persons in the zone based on the monitored zones; Determine the monitoring path based on the partition location.

4. The method for early warning of a safety visual detection camera according to claim 3, characterized in that: Also included is a wearing management method, the wearing management method comprising: When the verification level is not lower than the warning level, protective clothing is determined according to the warning area; Determine whether personnel are fully dressed based on protective clothing; When personnel clothing is incomplete, determine the missing clothing based on protective clothing and personnel clothing; Generate clothing reminder voice according to missing clothing, and determine the person's location based on the warning image; Determine prompt paths based on leadership and personnel positions; Control the preset drone to fly to the personnel's location according to the prompted path, and control the drone to issue clothing prompt voice.

5. A safety warning method for a safety visual detection camera according to claim 4, characterized in that: The wearing management method further comprises: When personnel are incompletely clothed, determine the type of danger in the area based on the warning area; Determine primary clothing based on hazard type and protective clothing; Determine whether the missing clothing includes the main clothing; When the missing clothing includes the main clothing, the indication angle is determined based on the person’s position and the missing clothing; According to the indication angle, the indication device preset on the drone is controlled to indicate the clothes that the person is not wearing, and the preset drone is controlled to issue a preset no-entry voice prompt.

6. A safety warning method for a safety visual detection camera according to claim 4, characterized in that: Also included is a personnel protection method, the personnel protection method comprising: When the alarm device sounds a security alarm, an alarm image is acquired; Determine the mobile location based on the alarm image; Determine whether the person is far away from the warning area based on the person's location, movement location and warning area; When the personnel do not leave the warning area, the warning path is determined according to the moving position and the warning area; According to the warning path, the preset UAV is controlled to fly between the personnel and the center of the danger zone, and the flash device preset on the UAV is controlled to issue a flash warning to the personnel.

7. A safety visual detection camera safety warning system, characterized in that: include: An acquisition module, used for acquiring early warning images, verification images, outlier images and alarm images; A memory for storing a program of a safety warning method for a safety visual detection camera according to any one of claims 1 to 6; The program in the memory can be loaded and executed by the processor.

8. An intelligent terminal, characterized in that: The invention comprises a memory and a processor, wherein the memory stores a computer program which can be loaded by the processor and executes a safety warning method for a safety visual detection camera as claimed in any one of claims 1 to 6.

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