Personnel gathering prediction method and system

Abstract

The invention provides a personnel gathering prediction method and system, and the method comprises the steps: carrying out the real-time matching of a target planning map corresponding to a factory in a preset database, and determining a production region, a public region and a living region in the factory according to the target planning map in real time; detecting a mobile terminal corresponding to each employee in the factory in real time through a signal base station, and creating a real-time monitoring map corresponding to the factory in real time according to the production area, the public area and the living area based on a preset program; positioning each employee to the interior of the real-time monitoring graph through the mobile terminal, so as to form a corresponding monitoring point in the real-time monitoring graph, and detecting the stay position of each monitoring point in real time in the real-time monitoring graph; judging whether a target set correspondingly formed by the monitoring points appears in the real-time monitoring map or not according to the stop position; and if yes, correspondingly determining that a person gathering phenomenon occurs in the factory. The working efficiency can be effectively improved.

Description

Technical Field

[0001] The present invention relates to the technical field of data processing, and particularly relates to a method and system for predicting personnel aggregation. Background Art

[0002] With the progress of technology and the rapid development of productivity, in order to meet the market demand, people have correspondingly built various types of factories, specifically, such as automobile production factories, clothing production factories, and food production factories, etc., to produce corresponding products.

[0003] Among them, since existing factories all need to produce products in large quantities, a large number of employees are required. Based on this, in order to produce products safely and stably, it is necessary to effectively manage a large number of employees to prevent safety accidents.

[0004] Furthermore, during the daily production of existing factories, when there is a phenomenon of large-scale aggregation of employees, the probability of accidents will increase significantly. Based on this, it is necessary to predict in real time whether employees will aggregate to prevent accidents accordingly. Specifically, in the process of predicting whether people will aggregate in the prior art, most will set corresponding cameras inside the factory area and subjectively judge whether there will be a phenomenon of personnel aggregation by manually viewing surveillance videos. However, in the actual application process of this judgment method, it is easily affected by human subjective factors, resulting in easy misjudgment or missed judgment, correspondingly reducing work efficiency. Summary of the Invention

[0005] Based on this, the purpose of the present invention is to provide a method and system for predicting personnel aggregation to solve the problem that in the prior art, most of the judgments on whether there will be a phenomenon of personnel aggregation are subjectively made by humans, resulting in the judgment results being easily affected by human subjective factors, thus prone to misjudgment or missed judgment.

[0006] The first aspect of the embodiment of the present invention proposes:

[0007] A method for predicting personnel aggregation, which is applied to a factory. A number of signal base stations are provided inside the factory, and the detection ranges of the number of signal base stations correspondingly cover the factory. The method includes:

[0008] Realtime match a target planning map corresponding to the factory in a preset database, and determine in real time the production areas, public areas, and living areas respectively included in the factory according to the target planning map;

[0009] The signal base station detects in real time the mobile terminals corresponding to each employee in the factory, and based on a preset program, creates a live monitoring map corresponding to the factory in real time according to the production area, the public area, and the living area;

[0010] Each employee is positioned inside the live monitoring map through the mobile terminal, so as to form corresponding monitoring points inside the live monitoring map. Among them, one employee corresponds to one monitoring point, and the staying position of each monitoring point is detected in real time in the live monitoring map;

[0011] Judge whether a target set formed by the corresponding monitoring points appears in the live monitoring map according to the staying position;

[0012] If it is judged according to the staying position in the live monitoring map that the target set formed by the corresponding monitoring points appears, it is correspondingly determined that there will be a phenomenon of personnel gathering inside the factory.

[0013] The beneficial effect of the present invention is that by obtaining the target planning map of the factory in real time, the overall structure of the current factory can be correspondingly obtained. Based on this, since several areas are correspondingly divided inside the factory and the functions of each area are different, the personnel existing in each area will not be the same. Based on this, each employee will be correspondingly mapped into the constructed live monitoring map in the form of a monitoring point through the mobile terminal of each employee, and the staying position of each monitoring point will be further detected. Based on this, it can finally be judged in real time whether there is a phenomenon of personnel gathering inside the factory according to the obtained staying position, so as to save the process of manual judgment, avoid errors, and improve work efficiency at the same time.

[0014] Further, the step of creating a live monitoring map corresponding to the factory in real time according to the production area, the public area, and the living area based on a preset program includes:

[0015] When the production area, the public area, and the living area are respectively obtained, a corresponding blank monitoring template is retrieved in the preset program;

[0016] According to the target planning map, the target area sizes corresponding to the production area, the public area, and the living area are detected in real time, and the target template size corresponding to the blank monitoring template is detected in real time;

[0017] The live monitoring map is created according to the target area size and the target template size, and the blank monitoring template is unique.

[0018] Further, the step of creating the live monitoring map according to the target area size and the target template size includes:

[0019] When the target area size and the target template size are respectively obtained, a target reduction factor adapted to the blank monitoring template is calculated in real time according to the target area size and the target template size;

[0020] The production area, the public area, and the living area are respectively mapped to the inside of the blank monitoring template according to the target reduction factor to generate corresponding initial monitoring maps in real time;

[0021] The live monitoring map is created in real time according to the initial monitoring map, and both the target area size and the target template size are unique.

[0022] Further, the step of creating the live monitoring map in real time according to the initial monitoring map includes:

[0023] Corresponding first identifiers are added to the production area in the initial monitoring map in real time, and a first monitoring threshold adapted to the production area is set in real time;

[0024] Corresponding second identifiers are added to the public area in the initial monitoring map in real time, and a second monitoring threshold adapted to the production area is set in real time;

[0025] Corresponding third identifiers are added to the living area in the initial monitoring map in real time, and a third monitoring threshold adapted to the living area is set in real time to generate the live monitoring map correspondingly, and the live monitoring map will change dynamically.

[0026] Further, the step of determining whether the target set formed by the monitoring points appears in the live monitoring map according to the staying position includes:

[0027] When the monitoring points corresponding to the employee are detected in the live monitoring map in real time, the monitoring points are processed by a preset tracking algorithm in real time to obtain the movement path corresponding to the monitoring points in real time;

[0028] The movement path is analyzed in real time to detect the starting point and the ending point corresponding to the movement path in real time;

[0029] Whether the target set formed by the monitoring points appears in the live monitoring map is determined according to the starting point and the ending point.

[0030] Further, the step of determining whether the target set corresponding to the monitoring point appears in the live monitoring graph according to the starting point and the ending point includes:

[0031] When the ending point of the moving path of the monitoring point is detected in real time, the residence time corresponding to the ending point is detected in real time, and it is determined in real time whether the residence time exceeds a preset time threshold;

[0032] If it is determined in real time that the residence time exceeds the preset time threshold, the ending point is correspondingly determined as the residence position corresponding to the monitoring point, the target area corresponding to the residence position is detected in real time, and it is determined in real time whether the target set corresponding to the monitoring point appears in the target area, and the target area is one of the living area, the production area, and the public area.

[0033] Further, the step of determining in real time whether the target set corresponding to the monitoring point appears in the target area includes:

[0034] When the target area is detected in real time, the target monitoring threshold corresponding to the target area is matched in real time;

[0035] The total number of targets corresponding to all the monitoring points in the target area is counted in real time, and it is determined in real time whether the number of targets is greater than the target monitoring threshold;

[0036] If it is determined in real time that the number of targets is greater than the target monitoring threshold, it is correspondingly determined that the target set corresponding to the monitoring point appears in the target area, and the number of targets will change dynamically.

[0037] The second aspect of the embodiments of the present invention proposes:

[0038] A personnel gathering prediction system, which is applied to a factory, and a plurality of signal base stations are arranged inside the factory, and the detection ranges of the plurality of signal base stations correspondingly cover the factory. The system includes:

[0039] A matching module, configured to match in real time a target planning graph corresponding to the factory in a preset database, and determine in real time the production area, the public area, and the living area respectively included in the factory according to the target planning graph;

[0040] A detection module, configured to detect in real time the mobile terminal corresponding to each employee in the factory through the signal base station, and create in real time a live monitoring graph corresponding to the factory based on a preset program according to the production area, the public area, and the living area;

[0041] A processing module, configured to position each of the employees inside the live monitoring map through the mobile terminal, so as to form corresponding monitoring points inside the live monitoring map, where one employee corresponds to one monitoring point, and the staying positions of each of the monitoring points are detected in real time in the live monitoring map;

[0042] A judgment module, configured to judge whether a target set formed corresponding to the monitoring point appears in the live monitoring map according to the staying position;

[0043] An execution module, configured to, if it is judged according to the staying position that the target set formed corresponding to the monitoring point appears in the live monitoring map, correspondingly determine that there will be a phenomenon of personnel gathering inside the factory.

[0044] Further, the detection module is specifically configured to:

[0045] When the production area, the public area, and the living area are respectively obtained, call out corresponding blank monitoring templates in the preset program;

[0046] According to the target planning map, the target area sizes corresponding to the production area, the public area, and the living area are detected in real time, and the target template sizes corresponding to the blank monitoring templates are detected in real time;

[0047] Create the live monitoring map according to the target area sizes and the target template sizes, and the blank monitoring template is unique.

[0048] Further, the detection module is specifically configured to:

[0049] When the target area sizes and the target template sizes are respectively obtained, calculate a target reduction factor adapted to the blank monitoring template in real time according to the target area sizes and the target template sizes;

[0050] Map the production area, the public area, and the living area to the inside of the blank monitoring template respectively according to the target reduction factor, so as to generate corresponding initial monitoring maps in real time;

[0051] Create the live monitoring map in real time according to the initial monitoring map, and both the target area sizes and the target template sizes are unique.

[0052] Further, the detection module is specifically configured to:

[0053] Add corresponding first identifiers to the production area in the initial monitoring map in real time, and set a first monitoring threshold adapted to the production area in real time;

[0054] In the initial monitoring map, add the corresponding second identifier to the public area in real time, and set the second monitoring threshold adapted to the production area in real time;

[0055] In the initial monitoring map, add the corresponding third identifier to the living area in real time, and set the third monitoring threshold adapted to the living area in real time, so as to generate the live monitoring map correspondingly, and the live monitoring map will change dynamically.

[0056] Further, the judgment module is specifically used for:

[0057] When a monitoring point corresponding to the employee is detected in the live monitoring map in real time, perform real-time tracking processing on the monitoring point through a preset tracking algorithm to obtain the moving path corresponding to the monitoring point in real time;

[0058] Perform parsing processing on the moving path in real time to detect the starting point and the ending point corresponding to the moving path in real time;

[0059] Judge whether the target set formed by the corresponding monitoring points appears in the live monitoring map according to the starting point and the ending point.

[0060] Further, the judgment module is specifically used for:

[0061] When the ending point of the moving path of the monitoring point is detected in real time, detect the residence time corresponding to the ending point in real time, and judge in real time whether the residence time exceeds the preset time threshold;

[0062] If it is judged in real time that the residence time exceeds the preset time threshold, then determine the ending point as the residence position corresponding to the monitoring point, detect the target area corresponding to the residence position in real time, and judge in real time whether the target set formed by the corresponding monitoring points appears in the target area, and the target area is one of the living area, the production area, and the public area.

[0063] Further, the judgment module is specifically used for:

[0064] When the target area is detected in real time, match the target monitoring threshold corresponding to the target area in real time;

[0065] Statistically count the target quantity corresponding to all the monitoring points in the target area in real time, and judge in real time whether the target quantity is greater than the target monitoring threshold;

[0066] If it is judged in real time that the target quantity is greater than the target monitoring threshold, then determine that the target set formed by the corresponding monitoring points appears in the target area correspondingly, and the target quantity will change dynamically.

[0067] In the third aspect of the embodiments of the present invention, it is proposed that:

[0068] A computer includes a memory, a processor, and a computer program stored on the memory and executable on the processor. Wherein, when the processor executes the computer program, the personnel aggregation prediction method described above is implemented.

[0069] In the fourth aspect of the embodiments of the present invention, it is proposed that:

[0070] A readable storage medium stores a computer program. Wherein, when the program is executed by a processor, the personnel aggregation prediction method described above is implemented.

[0071] The additional aspects and advantages of the present invention will be partially given in the following description, partially become apparent from the following description, or be understood through the practice of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0072] Figure 1 It is a flowchart of the personnel aggregation prediction method provided by the first embodiment of the present invention;

[0073] Figure 2 It is a structural block diagram of the personnel aggregation prediction system provided by the sixth embodiment of the present invention.

[0074] The following specific embodiments will further illustrate the present invention in conjunction with the above-mentioned drawings. SPECIFIC EMBODIMENTS

[0075] For ease of understanding of the present invention, the present invention will be described more comprehensively below with reference to the relevant drawings. Several embodiments of the present invention are given in the drawings. However, the present invention can be implemented in many different forms and is not limited to the embodiments described herein. On the contrary, these embodiments are provided to make the disclosure of the present invention more thorough and comprehensive.

[0076] It should be noted that when an element is referred to as being "fixedly provided on" another element, it can be directly on the other element or there can also be an intermediate element. When an element is considered to be "connected" to another element, it can be directly connected to the other element or there may be an intermediate element at the same time. The terms "vertical", "horizontal", "left", "right" and similar expressions used herein are only for the purpose of illustration.

[0077] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the technical field to which this invention belongs. The terms used in the description of this invention herein are for the purpose of describing specific embodiments only and are not intended to limit the invention. The term "and / or" used herein includes any and all combinations of one or more of the related listed items.

[0078] Please refer to Figure 1 , which shows the personnel aggregation prediction method provided by the first embodiment of the present invention. The personnel aggregation prediction method provided by this embodiment can quickly and effectively predict whether there will be a phenomenon of personnel aggregation in the factory, and at the same time can eliminate the process of manual judgment, corresponding to improving work efficiency.

[0079] Specifically, this embodiment provides:

[0080] A personnel aggregation prediction method is applied to a factory. There are several signal base stations inside the factory, and the detection ranges of the several signal base stations correspondingly cover the factory. The method includes:

[0081] Step S10, in a preset database, a target planning map corresponding to the factory is matched in real time, and based on the target planning map in real time, the production areas, public areas, and living areas respectively included in the factory are determined;

[0082] Step S20, through the signal base stations, the mobile terminals respectively corresponding to each employee in the factory are detected in real time, and based on a preset program, a live monitoring map corresponding to the factory is created in real time according to the production area, the public area, and the living area;

[0083] Step S30, each employee is positioned inside the live monitoring map through the mobile terminal to form corresponding monitoring points inside the live monitoring map, where one employee corresponds to one monitoring point, and the staying positions of each monitoring point are detected in real time in the live monitoring map;

[0084] Step S40, judging whether a target set formed by the monitoring points appears in the live monitoring map according to the staying position;

[0085] Step S50, if it is judged according to the staying position that a target set formed by the monitoring points appears in the live monitoring map, it is correspondingly determined that there will be a phenomenon of personnel aggregation inside the factory.

[0086] Specifically, in this embodiment, it should be noted first that in order to quickly and effectively predict whether there will be a phenomenon of personnel gathering inside the factory, corresponding management needs to be carried out on all employees inside the factory. Among them, it should be noted that for the convenience of implementation, the personnel gathering prediction method provided by the present invention is implemented based on each employee's mobile phone, the existing base station for receiving mobile phone signals, and the server set in the background. Among them, the server set in the background can establish a communication connection with the signal base station, and the signal base station can establish a communication connection with each employee's mobile phone. Based on this, the server can correspondingly complete the detection of each employee's mobile phone for subsequent processing. Specifically, since the areas of existing factories are relatively large, for the convenience of management, in the actual application process, it is necessary to first obtain the detailed information of the current factory. Specifically, the present invention will first match the target planning map corresponding to the current factory in the existing database in real time, that is, the regional planning map of the current factory. Based on this, it is possible to further obtain the production area, public area, and living area included in the current factory. At the same time, the mobile phone signals of each employee will be detected in real time through the signal base stations set inside the factory. Based on this, in order to be able to obtain the dynamics of each employee in real time, that is, to obtain the location of each employee in real time, the present invention will further create a live monitoring map corresponding to the current factory in real time according to the current production area, public area, and living area. Among them, it should be pointed out that the above live monitoring map can be created correspondingly through existing software such as ug or solidworks for subsequent processing.

[0087] Further, after the required real-time monitoring map is obtained through the above steps, in order to effectively complete the real-time monitoring of each employee, it is necessary to project the position of each employee into the current real-time monitoring map. Preferably, the present invention can obtain the positioning information of each employee's mobile phone in real time, and can further convert the positioning information of each employee's mobile phone into corresponding monitoring points in real time. At the same time, the monitoring points can be projected into the above-mentioned real-time monitoring map, so as to obtain the real-time position of each employee inside the current factory. Based on this, it should also be noted that since each area inside the factory can carry a certain number of employees, that is, under normal conditions, a certain number of employees can appear in each of the above-mentioned areas. However, when the number of employees in a certain area exceeds a certain value, the phenomenon of employee aggregation occurs at this time. Based on this, in order to be able to judge in real time whether the phenomenon of employee aggregation will occur, the present invention will further judge whether a target set composed of monitoring points appears inside the above-mentioned real-time monitoring map, that is, judge in real time whether there are more than a preset number of monitoring points in a certain area. Specifically, if so, it can directly indicate that the phenomenon of personnel aggregation has occurred in the current area. Correspondingly, if not, it can directly indicate that the phenomenon of personnel aggregation has not occurred in the current area. Based on this, it is possible to quickly and effectively judge whether personnel aggregation will occur in the factory, corresponding to improving work efficiency.

[0088] Second Embodiment

[0089] Further, the step of creating a real-time monitoring map corresponding to the factory in real time according to the production area, the public area, and the living area based on a preset program includes:

[0090] When the production area, the public area, and the living area are respectively obtained, call out the corresponding blank monitoring template in the preset program;

[0091] According to the target planning map, detect the target area size corresponding to the production area, the public area, and the living area in real time, and detect the target template size corresponding to the blank monitoring template in real time;

[0092] Create the real-time monitoring map according to the target area size and the target template size. The blank monitoring template is unique.

[0093] Further, the step of creating the real-time monitoring map according to the target area size and the target template size includes:

[0094] When the target area size and the target template size are respectively obtained, calculate the target reduction factor adapted to the blank monitoring template in real time according to the target area size and the target template size;

[0095] Map the production area, the public area, and the living area to the inside of the blank monitoring template respectively according to the target reduction factor to generate a corresponding initial monitoring map in real time;

[0096] Create the live monitoring map in real time according to the initial monitoring map. Both the target area size and the target template size are unique.

[0097] Further, the step of creating the live monitoring map in real time according to the initial monitoring map includes:

[0098] Add a corresponding first identifier to the production area in the initial monitoring map in real time, and set a first monitoring threshold adapted to the production area in real time;

[0099] Add a corresponding second identifier to the public area in the initial monitoring map in real time, and set a second monitoring threshold adapted to the production area in real time;

[0100] Add a corresponding third identifier to the living area in the initial monitoring map in real time, and set a third monitoring threshold adapted to the living area in real time to generate the live monitoring map correspondingly. The live monitoring map will change dynamically.

[0101] Further, the step of judging whether the target set formed by the monitoring points appears in the live monitoring map according to the staying position includes:

[0102] When a monitoring point corresponding to the employee is detected in the live monitoring map in real time, perform real-time tracking processing on the monitoring point through a preset tracking algorithm to obtain a moving path corresponding to the monitoring point in real time;

[0103] Perform parsing processing on the moving path in real time to detect the starting point and the ending point corresponding to the moving path in real time;

[0104] Judge whether the target set formed by the monitoring points appears in the live monitoring map according to the starting point and the ending point.

[0105] Further, the step of judging whether the target set formed by the monitoring points appears in the live monitoring map according to the starting point and the ending point includes:

[0106] When the ending point of the moving path of the monitoring point is detected in real time, detect the staying time corresponding to the ending point in real time, and judge whether the staying time exceeds a preset time threshold;

[0107] If it is determined in real time that the residence time exceeds the preset time threshold, the termination point is correspondingly determined as the residence position corresponding to the monitoring point, and the target area corresponding to the residence position is detected in real time, and it is also determined in real time whether the target set formed corresponding to the monitoring point appears in the target area, where the target area is one of the living area, the production area, and the public area.

[0108] Further, the step of determining in real time whether the target set formed corresponding to the monitoring point appears in the target area includes:

[0109] When the target area is detected in real time, the target monitoring threshold corresponding to the target area is matched in real time;

[0110] The total number of targets corresponding to all monitoring points in the target area is statistically calculated in real time, and it is determined in real time whether the number of targets is greater than the target monitoring threshold;

[0111] If it is determined in real time that the number of targets is greater than the target monitoring threshold, it is correspondingly determined that the target set formed corresponding to the monitoring point appears in the target area, and the number of targets will change dynamically.

[0112] In addition, in this embodiment, it should also be noted that after obtaining the required living area, production area, and public area through the above steps respectively, in order to quickly and effectively generate the required live monitoring map at this time, corresponding parsing processing needs to be carried out. Preferably, the present invention will first call out a blank monitoring template adapted to the type of the current factory. It should be noted that this blank monitoring template is a two-dimensional template. Based on this, the present invention will first detect the target area sizes corresponding to the current production area, living area, and public area respectively. Similarly, the present invention will further detect the target template size corresponding to the current blank monitoring template. On this basis, the current target template size will be divided by the current target area size in real time, so as to be able to calculate in real time the target reduction factor adapted to the current blank monitoring template. Based on this, in the actual application process, the present invention will respectively reduce and map the above-mentioned production area, living area, and public area to the inside of the above blank monitoring template in sequence according to the current target reduction factor in real time, so as to be able to form an initial monitoring map, that is, to map the information of the current factory to the inside of the current blank monitoring template. Based on this, in order to be able to independently complete the prediction of each area inside the current initial monitoring map, that is, in order to be able to process each area separately, preferably, the present invention will first carry out corresponding differentiation, that is, add corresponding first identifiers, second identifiers, and third identifiers to the current three areas respectively. At the same time, since the functionality of each area is different, the number of people to be monitored correspondingly will also be different. Based on this, the present invention will further add corresponding first monitoring thresholds, second monitoring thresholds, and third monitoring thresholds to the current three areas respectively, so as to be able to realize the separate management of the current three areas correspondingly and facilitate subsequent processing.

[0113] Further, after obtaining the required live monitoring map in real time through the above steps, in order to be able to predict in real time and accurately whether there will be a phenomenon of personnel gathering in the current project, preferably, the present invention maps each employee in the current factory to the inside of the current live monitoring map in the form of monitoring points. It should be noted that when the monitoring points of each employee are detected in real time, the present invention will immediately enable a pre-set tracking algorithm. Based on this, the current monitoring points are tracked in real time through this tracking algorithm, and the movement path corresponding to the current monitoring points can be obtained synchronously. It should be pointed out that the movement path can be regular or irregular, but in either case, there is a corresponding starting point and ending point. Based on this, the present invention will detect in real time the ending point corresponding to the movement path of each current monitoring point. At the same time, it will judge in real time whether the time the current monitoring point stays at the position of the current ending point exceeds a preset time threshold. Specifically, if so, the current ending point can be directly set as the staying position of the current monitoring point. Correspondingly, if not, it is determined that the current monitoring point has not stopped moving and subsequent monitoring is required. Based on this, after detecting the staying positions of each monitoring point in real time through the above method, the total number of monitoring points respectively included in the interiors of the above three regions can be detected correspondingly, and the required target quantity can be counted correspondingly. Based on this, the current target quantity is compared with the corresponding target monitoring threshold in real time to judge in real time whether the target quantity is greater than the target monitoring threshold. Specifically, if so, it can be directly determined that there is a phenomenon of personnel gathering in the current region. Correspondingly, if not, it can be determined that there is no phenomenon of personnel gathering in the current region, so as to quickly and accurately judge whether there will be a phenomenon of personnel gathering in the current factory, and at the same time, manual operations can be saved, corresponding to improving work efficiency.

[0114] Please refer to Figure 2 , the third embodiment of the present invention provides:

[0115] A personnel gathering prediction system, which is applied to a factory. There are several signal base stations inside the factory, and the detection ranges of the several signal base stations correspondingly cover the factory. The system includes:

[0116] A matching module, which is used to match in real time in a preset database the target planning map corresponding to the factory, and determine in real time the production area, public area and living area respectively included in the factory according to the target planning map;

[0117] A detection module, which is used to detect in real time through the signal base stations the mobile terminals respectively corresponding to each employee in the factory, and create in real time a live monitoring map corresponding to the factory based on a preset program according to the production area, the public area and the living area;

[0118] A processing module, configured to respectively locate each of the employees inside the live monitoring map through the mobile terminal, so as to form corresponding monitoring points inside the live monitoring map, where one employee corresponds to one monitoring point, and the staying positions of each of the monitoring points are detected in real time in the live monitoring map;

[0119] A judgment module, configured to judge whether a target set formed corresponding to the monitoring points appears in the live monitoring map according to the staying positions;

[0120] An execution module, configured to, if it is judged according to the staying positions that the target set formed corresponding to the monitoring points appears in the live monitoring map, correspondingly determine that there will be a phenomenon of personnel gathering inside the factory.

[0121] Further, the detection module is specifically configured to:

[0122] When the production area, the public area, and the living area are respectively obtained, call out corresponding blank monitoring templates in the preset program;

[0123] According to the target planning map, the target area sizes corresponding to the production area, the public area, and the living area are detected in real time, and the target template sizes corresponding to the blank monitoring templates are detected in real time;

[0124] Create the live monitoring map according to the target area sizes and the target template sizes, and the blank monitoring template is unique.

[0125] Further, the detection module is specifically configured to:

[0126] When the target area sizes and the target template sizes are respectively obtained, calculate in real time a target reduction factor adapted to the blank monitoring template according to the target area sizes and the target template sizes;

[0127] Map the production area, the public area, and the living area to the inside of the blank monitoring template respectively according to the target reduction factor, so as to generate corresponding initial monitoring maps in real time;

[0128] Create the live monitoring map in real time according to the initial monitoring map, and both the target area sizes and the target template sizes are unique.

[0129] Further, the detection module is specifically configured to:

[0130] Add corresponding first identifiers to the production area in the initial monitoring map in real time, and set a first monitoring threshold adapted to the production area in real time;

[0131] Add the corresponding second identifier to the public area in real time in the initial monitoring map, and set a second monitoring threshold adapted to the production area in real time;

[0132] Add the corresponding third identifier to the living area in real time in the initial monitoring map, and set a third monitoring threshold adapted to the living area in real time to correspondingly generate the live monitoring map, and the live monitoring map will change dynamically.

[0133] Further, the judgment module is specifically used for:

[0134] When a monitoring point corresponding to the employee is detected in real time in the live monitoring map, perform real-time tracking processing on the monitoring point through a preset tracking algorithm to obtain a moving path corresponding to the monitoring point in real time;

[0135] Perform parsing processing on the moving path in real time to detect a starting point and an ending point corresponding to the moving path in real time;

[0136] Judge whether a target set formed by the monitoring points appears in the live monitoring map according to the starting point and the ending point.

[0137] Further, the judgment module is specifically used for:

[0138] When the ending point of the moving path of the monitoring point is detected in real time, detect the residence time corresponding to the ending point in real time, and judge in real time whether the residence time exceeds a preset time threshold;

[0139] If it is judged in real time that the residence time exceeds the preset time threshold, then determine the ending point as the residence position corresponding to the monitoring point, detect the target area corresponding to the residence position in real time, and judge in real time whether a target set formed by the monitoring points appears in the target area, and the target area is one of the living area, the production area and the public area.

[0140] Further, the judgment module is specifically used for:

[0141] When the target area is detected in real time, match the target monitoring threshold corresponding to the target area in real time;

[0142] Statistically count the target quantity corresponding to all monitoring points in the target area in real time, and judge in real time whether the target quantity is greater than the target monitoring threshold;

[0143] If it is determined in real time that the number of targets is greater than the target monitoring threshold, it is determined that a target set corresponding to the monitoring points appears in the target area, and the number of targets will change dynamically.

[0144] A fourth embodiment of the present invention provides a computer, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the personnel gathering prediction method as described above when executing the computer program.

[0145] The fifth embodiment of the present invention provides a readable storage medium having a computer program stored thereon, wherein when the program is executed by a processor, the method for predicting the gathering of people as described above is implemented.

[0146] In summary, the personnel gathering prediction method and system provided by the above embodiments of the present invention can quickly and effectively predict whether personnel gathering will occur in the factory, while eliminating the process of manual judgment, thereby correspondingly improving work efficiency.

[0147] It should be noted that the above modules can be functional modules or program modules, and can be implemented by software or hardware. For modules implemented by hardware, the above modules can be located in the same processor; or the above modules can be located in different processors in any combination.

[0148] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as an ordered list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by an instruction execution system, device or apparatus (such as a computer-based system, a system including a processor, or other system that can fetch instructions from an instruction execution system, device or apparatus and execute instructions), or in conjunction with such instruction execution systems, devices or apparatuses. For the purposes of this specification, "computer-readable medium" can be any device that can contain, store, communicate, propagate or transmit a program for use by an instruction execution system, device or apparatus, or in conjunction with such instruction execution systems, devices or apparatuses.

[0149] More specific examples (a non-exhaustive list) of computer-readable media include the following: electrical connections (electronic devices) having one or more wirings, portable computer diskettes (magnetic devices), random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber devices, and portable compact disc read-only memory (CDROM). Additionally, the computer-readable media can even be paper or other suitable media on which the program can be printed, as the program can be obtained electronically, for example, by optically scanning the paper or other media, followed by editing, interpretation, or otherwise processing as appropriate, and then storing it in a computer memory.

[0150] It should be understood that the various parts of the present invention can be implemented by hardware, software, firmware, or a combination thereof. In the above embodiments, multiple steps or methods can be implemented by software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented by hardware, as in another embodiment, any one or a combination of the following techniques well known in the art can be used: discrete logic circuits having logic gate circuits for implementing logical functions on data signals, application specific integrated circuits having suitable combinational logic gate circuits, programmable gate arrays (PGA), field programmable gate arrays (FPGA), etc.

[0151] In the description of this specification, the description referring to terms such as "one embodiment", "some embodiments", "example", "specific example", or "some examples", etc. means that the specific features, structures, materials, or characteristics described in connection with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials, or characteristics described can be combined in any one or more embodiments or examples in a suitable manner.

[0152] The above-described embodiments merely represent several implementation manners of the present invention, and their descriptions are relatively specific and detailed, but should not be construed as limiting the scope of the present invention. It should be noted that for those of ordinary skill in the art, without departing from the concept of the present invention, several variations and improvements can still be made, and these all belong to the protection scope of the present invention. Therefore, the protection scope of the present invention should be subject to the appended claims.

Claims

1. A method for predicting crowd gathering, characterized in that: Applied to a factory, a plurality of signal base stations are arranged inside the factory, and the detection ranges of the plurality of signal base stations correspond to covering the factory. The method includes: Matching a target planning map corresponding to the factory in a preset database in real time, and determining the production area, public area and living area respectively contained in the factory according to the target planning map in real time; The signal base station detects the mobile terminal corresponding to each employee in the factory in real time, and creates a real-time monitoring map corresponding to the factory according to the production area, the public area and the living area based on a preset program; Using the mobile terminal, each of the employees is located inside the live monitoring map to form a corresponding monitoring point inside the live monitoring map, wherein one employee corresponds to one monitoring point, and the stay position of each monitoring point is detected in real time in the live monitoring map; Judging whether a target set corresponding to the monitoring point appears in the real-time monitoring map according to the stop position; If it is determined that a target set corresponding to the monitoring point appears in the real-time monitoring map based on the stay position, it is determined that a gathering of people will occur inside the factory.

2. The method for predicting crowd gathering according to claim 1, characterized in that: The step of creating a real-time monitoring map corresponding to the factory based on the production area, the public area and the living area in real time based on a preset program includes: When the production area, the public area, and the living area are respectively acquired, calling out corresponding blank monitoring templates in the preset program; According to the target planning map, the target area sizes corresponding to the production area, the public area and the living area are detected in real time, and the target template size corresponding to the blank monitoring template is detected in real time; The real-time monitoring map is created according to the size of the target area and the size of the target template, and the blank monitoring template is unique.

3. The method for predicting crowd gathering according to claim 2, characterized in that: The step of creating the live monitoring map according to the target area size and the target template size includes: When the target area size and the target template size are respectively obtained, a target reduction factor adapted to the blank monitoring template is calculated in real time according to the target area size and the target template size; According to the target reduction factor, the production area, the public area and the living area are respectively mapped to the inside of the blank monitoring template to generate a corresponding initial monitoring map in real time; The live monitoring map is created in real time according to the initial monitoring map, and the target area size and the target template size are both unique.

4. The method for predicting crowd gathering according to claim 3, characterized in that: The step of creating the live monitoring map in real time according to the initial monitoring map comprises: Adding a corresponding first identifier to the production area in the initial monitoring map in real time, and setting a first monitoring threshold adapted to the production area in real time; Adding a corresponding second identifier to the public area in the initial monitoring map in real time, and setting a second monitoring threshold adapted to the production area in real time; In the initial monitoring map, a corresponding third identifier is added to the living area in real time, and a third monitoring threshold adapted to the living area is set in real time to generate the actual monitoring map accordingly, and the actual monitoring map will change dynamically.

5. The method for predicting crowd gathering according to claim 4, characterized in that: The step of judging whether a target set corresponding to the monitoring point appears in the real-time monitoring map according to the stop position comprises: When a monitoring point corresponding to the employee is detected in real time in the live monitoring map, the monitoring point is tracked in real time by a preset tracking algorithm to obtain a moving path corresponding to the monitoring point in real time; Analyzing the moving path in real time to detect the starting point and the ending point corresponding to the moving path in real time; According to the starting point and the ending point, it is determined in the live monitoring map whether a target set corresponding to the monitoring point appears.

6. The method for predicting crowd gathering according to claim 5, characterized in that: The step of judging whether a target set corresponding to the monitoring point appears in the live monitoring map according to the starting point and the ending point comprises: When the end point of the moving path of the monitoring point is detected in real time, the stay time corresponding to the end point is detected in real time, and it is determined in real time whether the stay time exceeds a preset time threshold; If it is determined in real time that the stay time exceeds the preset time threshold, the end point is determined to be the stay position corresponding to the monitoring point, and the target area corresponding to the stay position is detected in real time, and it is determined in real time whether the target set formed by the monitoring point appears in the target area, and the target area is one of the living area, the production area and the public area.

7. The method for predicting crowd gathering according to claim 6, characterized in that: The step of determining in real time whether a target set corresponding to the monitoring point appears in the target area comprises: When the target area is detected in real time, a target monitoring threshold corresponding to the target area is matched in real time; Counting the number of targets corresponding to all monitoring points in the target area in real time, and judging in real time whether the number of targets is greater than the target monitoring threshold; If it is determined in real time that the number of targets is greater than the target monitoring threshold, it is determined that a target set corresponding to the monitoring points appears in the target area, and the number of targets will change dynamically.

8. A personnel gathering prediction system, characterized in that: Applied to a factory, a plurality of signal base stations are arranged inside the factory, and the detection range of the plurality of signal base stations covers the factory accordingly. The system includes: A matching module, used to match a target planning map corresponding to the factory in a preset database in real time, and determine the production area, public area and living area respectively contained in the factory according to the target planning map in real time; A detection module, configured to detect in real time through the signal base station the mobile terminal corresponding to each employee in the factory, and to create in real time a real-time monitoring map corresponding to the factory according to the production area, the public area, and the living area based on a preset program; A processing module, used to locate each of the employees inside the live monitoring map through the mobile terminal to form a corresponding monitoring point inside the live monitoring map, wherein one employee corresponds to one monitoring point, and detect the stop position of each monitoring point in real time in the live monitoring map; A judgment module, used for judging whether a target set corresponding to the monitoring point appears in the real-time monitoring map according to the stop position; The execution module is used to determine that a gathering of people will occur inside the factory if a target set corresponding to the monitoring point is determined to appear in the real-time monitoring map according to the stop position.

9. A computer comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, the method for predicting crowd gathering according to any one of claims 1 to 7 is implemented.

10. A readable storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the method for predicting crowd gathering as described in any one of claims 1 to 7 is implemented.

Images