Early warning methods, systems and devices for use in exhibition halls

Abstract

This invention discloses an early warning method, system, and device for exhibition halls; belonging to the field of exhibition hall technology; when monitoring and issuing early warnings for visitor flow in exhibition halls, the method first combines the monitoring time with the total number of people in the exhibition hall to obtain a flow value. Based on the flow value, an overall analysis of the visitor flow in the exhibition hall is performed to determine whether there is overcrowding. Based on the overall analysis, a flow coefficient is obtained by combining the weight of exhibits with the number of people in the exhibition area. Based on the flow coefficient, the visitor flow situation in different areas is further determined, realizing modular monitoring of visitor flow in exhibition halls and effectively improving the accuracy and comprehensiveness of visitor flow early warning; this invention is used to solve the technical problem of poor overall early warning effect in existing solutions for exhibition halls.

Description

Technical Field

[0001] This invention relates to the field of exhibition technology, and more specifically, to early warning methods, systems and devices applied to exhibitions. Background Technology

[0002] The exhibition hall's early warning system mainly comprises two parts: First, indoor systems: warnings for climbing over artifact fences; warnings for sudden acceleration; attack / fall detection; personnel density detection; alarms for theft of valuables; warnings for personnel leaving important areas; warnings for personnel entering important areas; warnings for suspicious items left in the exhibition hall; warnings for turning lights on / off; warnings for lost video footage, obstructed video footage, and camera movement, etc. Additionally, there is indoor environmental monitoring, including temperature, humidity, and air quality. Second, outdoor systems: perimeter security; warnings for people and vehicles entering restricted areas; warnings for suspicious persons loitering nearby; warnings for suspicious objects; prevention of unauthorized intrusion through the main gate; warnings for lost video footage, obstructed video footage, and camera movement.

[0003] Existing early warning systems for exhibition halls have certain shortcomings: First, they can only monitor the overall visitor flow in the exhibition hall, but cannot provide modular early warnings for visitor flow in different exhibition areas; second, they cannot perform modular monitoring and early warnings for lost items in different areas of the exhibition hall, resulting in poor overall early warning effectiveness for exhibition halls. Summary of the Invention

[0004] In view of the shortcomings of the existing technology, the purpose of this invention is to provide an early warning method, system and device for exhibition halls, so as to solve the technical problem that the overall early warning effect of exhibition halls is not good in the existing solutions.

[0005] The objective of this invention can be achieved through the following technical solutions:

[0006] Early warning methods applied to exhibition halls include:

[0007] The exhibition areas of the exhibition hall are divided and numbered to obtain an exhibition area division set; the exhibition area division set contains several exhibition areas and aisle areas;

[0008] The exhibition area is divided into different exhibition areas and then modularized to obtain an exhibition area module set;

[0009] Monitor the exhibition area modules to obtain pedestrian flow information and image information in different areas of the exhibition area modules;

[0010] Feature extraction was performed on pedestrian flow information and image information respectively to obtain the first extraction set and the second extraction set;

[0011] The first and second extraction sets are calculated separately to obtain the first training set and the second training set;

[0012] Based on the first and second training sets, early warnings and alerts are issued regarding pedestrian traffic and lost items in different areas.

[0013] Furthermore, the specific steps for obtaining the exhibition area module set include:

[0014] The exhibition area is divided into different exhibition areas based on the preset division distance. The exhibition area is divided into a warning area and a safe area. The warning area and the safe area constitute a subset of the exhibition area.

[0015] The warning area and the security area are renumbered according to the exhibition area number, and several subsets of the number are classified and combined according to the exhibition area number to obtain the exhibition area module set.

[0016] Furthermore, the specific steps for feature extraction from pedestrian flow information include:

[0017] Obtain the number of people in several exhibition areas and aisle areas within a preset monitoring time period. Set the number of people in the exhibition areas and aisle areas as the number of people in the exhibition areas Zi and the number of people in the aisle areas Gj, i = 1, 2, 3, ..., n; j = 1, 2, 3, ..., n; where i is the number of exhibition areas and j is the number of aisle areas.

[0018] The number of people in the warning areas of several exhibition areas during the monitoring period is set as the number of people under warning, Zik, k = 1, 2, 3, ..., n; k is the number of warning areas;

[0019] Match the exhibits in several exhibition areas with a preset exhibit weight table to obtain the corresponding exhibit weights QTi;

[0020] The labeled data items are arranged and combined in chronological order to obtain the first extraction set.

[0021] Furthermore, the specific steps for feature extraction from image information include:

[0022] Acquire exhibition area images and aisle images from several exhibition areas and aisle areas before the exhibition hall opens for business, and set them as sample exhibition area images and sample aisle images respectively;

[0023] The grayscale values ​​of all pixels in the sample exhibition area image and the sample aisle image are obtained and combined in a preset order to obtain the grayscale set ZHi1 of the sample exhibition area and the grayscale set GHj1 of the sample aisle.

[0024] Acquire exhibition area images and aisle images from several exhibition areas and aisle areas when the exhibition hall opens for business, and set them as monitored exhibition area images and monitored aisle images respectively;

[0025] Obtain the grayscale values of all pixel points on the monitoring exhibition area image and the monitoring aisle image, and combine them in a preset arrangement order to obtain the monitoring exhibition area grayscale set ZHi2 and the monitoring aisle grayscale set GHj2;

[0026] Arrange and combine the marked data in chronological order to obtain the second extraction set.

[0027] Further, the specific steps for calculating the first extraction set include:

[0028] Obtain the flow value LL of the exhibition hall by calculating the marked data in the first extraction set through the flow monitoring formula. The flow monitoring formula is a1 and a2 are different proportionality coefficients and are both greater than zero; T is the duration of the monitoring time period;

[0029] Match the flow value with the preset flow range [P1, P2];

[0030] If LL < P1, it is determined that the number of people in the exhibition hall is normal and a first flow signal is generated;

[0031] If P1 ≤ LL ≤ P2, it is determined that the number of people in the exhibition hall is partially crowded and a second flow signal is generated;

[0032] If P2 < LL, it is determined that the number of people in the exhibition hall is overall crowded and a third flow signal is generated;

[0033] The flow value and the first flow signal, the second flow signal, and the third flow signal form the first analysis set;

[0034] Monitor and analyze the number of people in several exhibition area regions according to different flow signals in the first analysis set.

[0035] Further, the specific steps for monitoring and analyzing the number of people in several exhibition area regions include: If the first analysis set does not include the first flow signal, obtain the warning number Zik of several exhibition area regions and the exhibit weight QQi corresponding to the exhibition area region; Calculate the warning coefficient JJX through the exhibition area flow formula for the marked data. The exhibition area flow formula is JJX = QQi * (Zik / Zi);

[0036] Match the warning coefficient with the preset warning threshold, and set the exhibition area region corresponding to the warning coefficient greater than the warning threshold as the marked area;

[0037] Count the duration of the marked area. If the duration is not greater than the warning duration, it is determined that the marked area is temporarily crowded and a first warning signal is generated;

[0038] If the duration of congestion exceeds the warning duration, the marked area is determined to be continuously congested and a second warning signal is generated; the warning coefficient, the first warning signal, and the second warning signal constitute the second analysis set; the first analysis set and the second analysis set constitute the first training set.

[0039] Furthermore, the specific steps for calculating the second extraction set include:

[0040] Obtain the grayscale sets ZHi1 (sample exhibition area), GHj1 (sample aisle), ZHi2 (monitoring exhibition area), and GHj2 (monitoring aisle) of the second extraction set. The missing value YS is calculated using an image formula. This image formula is:

[0041]

[0042] b1 and b2 are different proportionality coefficients and 0 <b1<1<b2;

[0043] The lost value is matched with a preset total loss threshold. If the lost value is not greater than the total loss threshold, a first lost signal is generated; if the lost value is greater than the total loss threshold, a second lost signal is generated. The lost value, the first lost signal, and the second lost signal constitute a lost analysis set.

[0044] Based on different loss signals in the loss analysis set, the loss situation in several exhibition areas and aisle areas is monitored and analyzed.

[0045] Furthermore, the specific steps for monitoring and analyzing lost items in several exhibition areas and aisle areas include:

[0046] If the loss analysis set contains a second loss signal, the loss situation of several exhibition areas is monitored based on the second loss signal. The difference between the gray set of the monitored exhibition area and the gray set of the sample exhibition area is obtained and set as the selected difference value. The selected difference value is then matched with the loss score threshold.

[0047] If the difference between the selected values ​​is not greater than the loss score threshold, it is determined that there are no lost items in the exhibition area and a first prompt signal is generated.

[0048] If the difference between the selected values ​​is greater than the loss score threshold, it is determined that there is a lost item in the exhibition area and a second prompt signal is generated.

[0049] If the prompt signals corresponding to several exhibition areas are all the first prompt signal, then it is determined that the lost item is located in the aisle area and a third prompt signal is generated; the first prompt signal, the second prompt signal and the third prompt signal constitute the lost item prompt set; the lost item analysis set and the lost item prompt set constitute the second training set.

[0050] Furthermore, the specific steps for issuing early warnings and alerts regarding pedestrian traffic and lost items in different areas include:

[0051] Obtain the second analysis set from the first training set, and issue early warnings on the flow of people in different exhibition areas based on the first and second warning signals in the second analysis set;

[0052] Obtain the lost item alert set from the second training set, and provide alerts for lost items in different exhibition areas and aisle areas based on the first, second, and third alert signals in the lost item alert set.

[0053] To address the aforementioned problems, the present invention also provides an early warning system for use in exhibition halls, comprising:

[0054] Area Division Module: Used to divide and number the exhibition areas of the exhibition hall, resulting in an exhibition area division set; the exhibition area division set contains several exhibition areas and aisle areas;

[0055] Regional Expansion Module: Used to modularize the different exhibition areas into a set of exhibition area modules;

[0056] Area monitoring module: Used to monitor the exhibition area module set and obtain pedestrian flow information and image information in different areas of the exhibition area module set;

[0057] Information processing module: used to extract features from pedestrian flow information and image information respectively to obtain a first extraction set and a second extraction set; and to perform calculations on the first extraction set and the second extraction set respectively to obtain a first training set and a second training set;

[0058] Early warning module: used to provide early warnings and alerts on pedestrian traffic and lost items in different areas based on the first and second training sets.

[0059] To address the aforementioned problems, the present invention also provides an early warning device for use in exhibition halls, characterized in that it includes at least one processor;

[0060] And a memory communicatively connected to at least one processor; wherein the memory stores a computer program executable by at least one processor, the computer program being executed by at least one processor to enable at least one processor to perform the aforementioned early warning method applied to exhibition halls.

[0061] Compared with existing solutions, the beneficial effects of the present invention are as follows:

[0062] When monitoring and issuing early warnings for visitor flow in exhibition halls, this invention first combines the monitoring time with the total number of people in the exhibition hall to obtain the flow value. Based on the flow value, it performs an overall analysis of the visitor flow in the exhibition hall to determine whether there is overcrowding. Based on the overall analysis, it obtains the flow coefficient by combining the weight of the exhibits with the number of people in the exhibition area. Based on the flow coefficient, it further determines the visitor flow in different areas, realizing modular monitoring of visitor flow in exhibition halls and effectively improving the accuracy and comprehensiveness of visitor flow early warning.

[0063] By analyzing images from different areas within the exhibition hall to obtain loss values, the overall area of ​​the exhibition hall can be analyzed to determine whether lost items exist. Based on the overall analysis, grayscale data from images of different exhibition areas can be obtained to determine whether lost items exist in those areas. This not only further determines the location of lost items but also verifies the overall analysis of lost items, eliminating interference from garbage or other foreign objects in the analysis and effectively improving the accuracy of lost item monitoring and early warning. Attached Figure Description

[0064] Figure 1 This is a flowchart illustrating the early warning method of the present invention applied to exhibition halls.

[0065] Figure 2 This is a schematic diagram of the module of the early warning system of the present invention applied to exhibition halls.

[0066] Figure 3 This is a schematic diagram of the early warning device of the present invention applied to exhibition halls.

[0067] Figure 4 This is a schematic diagram showing the distribution of exhibits in the exhibition hall according to an embodiment of the present invention. Detailed Implementation

[0068] The technical solution of the present invention will be clearly and completely described below with reference to the embodiments. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0069] The terminology used herein is for describing embodiments and is not intended to limit and / or restrict this disclosure; it should be noted that the singular forms “a,” “an,” and “the” include the plural forms as well, unless the context clearly indicates otherwise; and although terms such as “first,” “second,” etc. may be used herein to describe various elements, the elements are not limited by these terms, which are used only to distinguish one element from another.

[0070] Reference Figure 1The diagram shown is a flowchart illustrating an early warning method for exhibition halls provided by an embodiment of the present invention. In this embodiment, unlike existing solutions that can only monitor and warn about visitor flow at the overall level of the exhibition hall and on each floor, and that rely solely on manual observation of lost items in the exhibition area, the present invention achieves more efficient monitoring and early warning. It can monitor visitor flow and lost item detection in different exhibit areas on each floor of the exhibition hall, and promptly issue early warnings for overcrowding and lost items, effectively improving the safety and efficiency of early warning systems for exhibition halls.

[0071] The specific steps of the early warning method applied to exhibition halls include:

[0072] The exhibition areas of the exhibition hall are divided and numbered to obtain an exhibition area division set; the exhibition area division set contains several exhibition areas and aisle areas;

[0073] In this embodiment of the invention, the exhibition hall can be a museum, with several levels of exhibits displayed on each floor. The divided areas can be rectangular. In order to facilitate the monitoring of visitor flow and lost items in exhibition areas of different importance, several exhibition areas are divided and numbered to realize modular monitoring and early warning of the exhibition hall, providing data support for accurate monitoring of different exhibition areas.

[0074] It is worth noting that, since the placement of exhibits is not unique, refer to... Figure 4 As shown, exhibits can be located on the walls of the exhibition hall, in the middle of the exhibition hall, or in a corner of the exhibition hall;

[0075] When an exhibit is located in the center of the exhibition hall, unlike when the exhibit is located on the wall of the exhibition hall, the exhibit, together with the warning area and the safe area, forms a rectangle.

[0076] When an exhibit is located in a corner of the exhibition hall, the exhibits on both sides of the corner share a warning area and a safety area.

[0077] The exhibition area is divided into different zones and then modularized to obtain an exhibition area module set; the specific steps include:

[0078] The system acquires different exhibition area divisions and divides them into warning zones and safe zones according to a preset division distance. The warning zones and safe zones constitute a subset of the exhibition area divisions. The preset division distance can be 0.25m, which is the width of the warning zone, and is set according to the foot length of an adult.

[0079] In this embodiment of the invention, the modular processing method is to divide the rectangular exhibition area into two equal parts. When the exhibit is located on the wall of the exhibition hall, both the warning area and the safe area are rectangular, and the area of ​​the warning area is smaller than the area of ​​the safe area. The warning area is the area close to the exhibit.

[0080] The warning area and the security area are renumbered according to the exhibition area number, and several subsets of the number are classified and combined according to the exhibition area number to obtain the exhibition area module set;

[0081] The purpose of secondary numbering of warning zones and safe zones is to accurately send location information when a warning occurs, so as to handle the situation more efficiently.

[0082] The exhibition area modules are monitored to obtain pedestrian flow information and image information in different areas of the exhibition area modules. The pedestrian flow information and image information in different areas can be obtained by processing the real-time video data of existing cameras. The number of people obtained by processing the real-time video data is the existing conventional solution, and the specific steps are not described here.

[0083] Feature extraction was performed on pedestrian flow information and image information respectively to obtain the first extraction set and the second extraction set;

[0084] The specific steps for feature extraction from pedestrian flow information include:

[0085] Obtain the number of people in several exhibition areas and aisle areas within a preset monitoring time period. Set the number of people in the exhibition areas and aisle areas as the number of people in the exhibition areas Zi and the number of people in the aisle areas Gj, i = 1, 2, 3, ..., n; j = 1, 2, 3, ..., n; where i is the number of exhibition areas and j is the number of aisle areas.

[0086] In this embodiment of the invention, the preset monitoring time period can be 15 seconds. When a person is located between two areas, the area in which the person moves or faces is set as the area for statistics. This special case is the situation when the person is moving.

[0087] The number of people in the warning areas of several exhibition areas during the monitoring period is set as the number of people under warning, Zik, k = 1, 2, 3, ..., n; k is the number of warning areas;

[0088] The exhibits in several exhibition areas are matched with a preset exhibit weight table to obtain the corresponding exhibit weight QTi; when an exhibit is located in a corner of the exhibition hall, the two exhibits share a warning area and the exhibit weights are the same.

[0089] The labeled data items are arranged and combined in chronological order to obtain the first extraction set;

[0090] It should be noted that in this embodiment of the invention, different exhibits correspond to different exhibit weights. Several exhibits and their corresponding exhibition area weights constitute an exhibit weight table. The weight of the area where the exhibit is located can be the same as the exhibit weight. This is used to distinguish the different congestion requirements corresponding to different exhibition areas when calculating. For example, the number of people congested for exhibits with higher levels should be less than the number of people congested for exhibits with lower levels. This realizes differentiated monitoring and early warning for different exhibits and improves the diversity of exhibition hall monitoring.

[0091] The specific steps for feature extraction from image information include:

[0092] Acquire exhibition area images and aisle images from several exhibition areas and aisle areas before the exhibition hall opens for business, and set them as sample exhibition area images and sample aisle images respectively;

[0093] The grayscale values ​​of all pixels in the sample exhibition area image and the sample aisle image are obtained and combined in a preset order to obtain the grayscale set ZHi1 of the sample exhibition area and the grayscale set GHj1 of the sample aisle; wherein, the preset order is from top to bottom and from left to right.

[0094] The system acquires images of several exhibition areas and aisles when the exhibition hall opens for business and sets them as monitoring images for the exhibition areas and aisles respectively; when no one is in the area, the system still acquires images based on camera footage.

[0095] The grayscale values ​​of all pixels in the monitoring exhibition area image and the monitoring aisle image are acquired and combined in a preset order to obtain the grayscale set ZHi2 of the monitoring exhibition area and the grayscale set GHj2 of the monitoring aisle.

[0096] The labeled data items are arranged and combined in chronological order to obtain the second extraction set;

[0097] It should be noted that in this embodiment of the invention, the monitoring of lost items in different areas of the exhibition hall is based on image information of the area at different times. The acquisition of images of several exhibition areas and aisles before the opening of the exhibition hall and the analysis of lost items are used to reduce the interference caused by moving people during image analysis, which can effectively improve the accuracy of lost item analysis.

[0098] The first and second extraction sets are calculated separately to obtain the first training set and the second training set;

[0099] The specific steps for calculating the first extracted set include:

[0100] Obtain the data of each item of the first extraction set, and calculate the flow value LL of the exhibition hall through the flow monitoring formula. The flow monitoring formula is a1 and a2 are different proportionality coefficients and are both greater than zero. a1 can take the value of 0.7954, and a2 can take the value of 0.3618; T is the duration of the monitoring time period, taking the value of 15, and the unit is seconds;

[0101] Match the flow value with the preset flow range [P1, P2];

[0102] If LL < P1, it is determined that the number of people in the exhibition hall is normal and a first flow signal is generated;

[0103] If P1 ≤ LL ≤ P2, it is determined that the number of people in the exhibition hall is partially crowded and a second flow signal is generated;

[0104] If P2 < LL, it is determined that the number of people in the exhibition hall is overall crowded and a third flow signal is generated;

[0105] The flow value, the first flow signal, the second flow signal and the third flow signal constitute the first analysis set;

[0106] Monitor and analyze the number of people in several exhibition area regions according to different flow signals in the first analysis set;

[0107] It should be noted that the flow value is the value obtained by counting all the people in different areas of the exhibition hall to analyze whether the exhibition hall is crowded as a whole; in order to further determine whether there is a crowded situation in different exhibition areas, it needs to be determined according to different flow signals in the first analysis set.

[0108] The specific steps for monitoring and analyzing the number of people in several exhibition area regions include:

[0109] If the first analysis set does not contain the first flow signal, obtain the warning number of people Zik in several exhibition area regions and the exhibition object weight QQi corresponding to the exhibition area region;

[0110] The warning coefficient JJX is calculated through the exhibition area flow formula from the marked data. The exhibition area flow formula is JJX = QQi * (Zik / Zi);

[0111] Match the warning coefficient with the preset warning threshold, and set the exhibition area region corresponding to the warning coefficient greater than the warning threshold as the marked region;

[0112] Count the duration of the marked region. If the duration is not greater than the warning duration, it is determined that the marked region is temporarily crowded and a first warning signal is generated;

[0113] If the duration is greater than the warning duration, it is determined that the marked area is continuously crowded and a second warning signal is generated; the warning coefficient, the first warning signal, and the second warning signal form a second analysis set;

[0114] The first analysis set and the second analysis set form a first training set;

[0115] In the implementation of the present invention, the warning coefficient is a numerical value for modular monitoring and analysis of the pedestrian flow in different exhibition areas. By analyzing the combined duration of the marked areas, the accuracy of pedestrian flow monitoring in different exhibition areas can be effectively improved;

[0116] Among them, the specific steps for calculating the second extraction set include:

[0117] Obtain the grayscale set ZHi1 of the sample exhibition area, the grayscale set GHj1 of the sample aisle, the grayscale set ZHi2 of the monitored exhibition area, and the grayscale set GHj2 of the monitored aisle marked in the second extraction set. The missing value YS is calculated through the image formula for each marked data item;

[0118] The image formula is

[0119]

[0120] b1 and b2 are different proportional coefficients and 0 < b1 < 1 < b2. b1 can take the value of 0.4635, and b2 can take the value of 5.8254;

[0121] Match the missing value with the preset total missing threshold. If the missing value is not greater than the total missing threshold, a first missing signal is generated; the first missing signal indicates that there are no lost items in the exhibition hall;

[0122] If the missing value is greater than the total missing threshold, a second missing signal is generated; the second missing signal indicates that there are lost items in the exhibition hall, but the specific location of the area where the lost items are located needs to be further analyzed and determined;

[0123] The missing value, the first missing signal, and the second missing signal form a missing analysis set;

[0124] Monitor and analyze the lost item situation in several exhibition areas and aisle areas according to different missing signals in the missing analysis set;

[0125] It should be noted that the missing value is a numerical value obtained by processing the image information in different areas at different time periods to comprehensively analyze whether there are lost items in the exhibition hall;

[0126] The specific steps for monitoring and analyzing the lost item situation in several exhibition areas and aisle areas include:

[0127] If the loss analysis set contains a second loss signal, the loss situation of several exhibition areas is monitored based on the second loss signal. The difference between the gray set of the monitored exhibition area and the gray set of the sample exhibition area is obtained and set as the selected difference value. The selected difference value is then matched with the loss score threshold.

[0128] If the difference between the selected values ​​is not greater than the loss score threshold, it is determined that there are no lost items in the exhibition area and a first prompt signal is generated.

[0129] If the difference between the selected values ​​is greater than the loss score threshold, it is determined that there is a lost item in the exhibition area and a second prompt signal is generated.

[0130] If the prompt signals corresponding to several exhibition areas are all the first prompt signal, then it is determined that the lost item is located in the aisle area and a third prompt signal is generated; among them, the analysis based on the selected difference can not only further determine the location of the lost item, but also verify the overall analysis of the lost item, so as to eliminate the interference of garbage or other foreign objects on the analysis of the lost item;

[0131] The first, second, and third prompt signals constitute the lost item prompt set; the lost item analysis set and the lost item prompt set constitute the second training set;

[0132] It should be noted that in this embodiment of the invention, a scheme that performs overall analysis followed by local confirmation, and does not perform local confirmation when the overall analysis finds no lost item, can effectively improve data processing efficiency and save resources compared to a scheme that only performs local confirmation on all areas.

[0133] Based on the first and second training sets, early warnings and alerts are issued regarding pedestrian traffic and lost items in different areas. The specific steps include:

[0134] Obtain the second analysis set from the first training set, and issue early warnings and notify staff about the flow of people in different exhibition areas based on the first and second warning signals in the second analysis set;

[0135] Obtain the lost item alert set from the second training set, and based on the first, second, and third alert signals in the lost item alert set, alert staff to the lost items in different exhibition areas and aisle areas.

[0136] Reference Figure 2 The diagram shown is a schematic representation of a module of an early warning system for exhibition halls provided in an embodiment of the present invention. In this embodiment, the early warning system for exhibition halls includes a region division module, a region expansion module, a region monitoring module, an information processing module, and an early warning notification module.

[0137] Area Division Module: Used to divide and number the exhibition areas of the exhibition hall, resulting in an exhibition area division set; the exhibition area division set contains several exhibition areas and aisle areas;

[0138] Regional Expansion Module: Used to modularize the different exhibition areas into a set of exhibition area modules;

[0139] Area monitoring module: Used to monitor the exhibition area module set and obtain pedestrian flow information and image information in different areas of the exhibition area module set;

[0140] Information processing module: used to extract features from pedestrian flow information and image information respectively to obtain a first extraction set and a second extraction set; and to perform calculations on the first extraction set and the second extraction set respectively to obtain a first training set and a second training set;

[0141] Early warning module: used to provide early warnings and alerts on pedestrian traffic and lost items in different areas based on the first and second training sets.

[0142] Reference Figure 3 The diagram shown is a structural schematic of an early warning device for use in exhibition halls, according to an embodiment of the present invention. In this embodiment, the early warning device for use in exhibition halls may include a processor, a memory, a communication bus, and a communication interface, and may also include a computer program stored in the memory and executable on the processor.

[0143] In some embodiments, the processor can be composed of integrated circuits, such as a single packaged integrated circuit or multiple integrated circuits with the same or different functions, including combinations of one or more central processing units (CPUs), microprocessors, digital processing chips, graphics processors, and various control chips. The processor is the control unit of the electronic device, connecting various components of the device through various interfaces and lines. It executes programs or modules stored in memory (such as early warning programs for exhibitions) and calls data stored in memory to perform various functions and process data within the electronic device.

[0144] The memory includes at least one type of readable storage medium, including flash memory, portable hard drives, multimedia cards, card-type memory (e.g., SD or DX memory), magnetic storage, magnetic disks, optical disks, etc. In some embodiments, the memory can be an internal storage unit of an electronic device, such as a portable hard drive. In other embodiments, the memory can be an external storage device of the electronic device, such as a plug-in portable hard drive, Smart Media Card (SMC), Secure Digital (SD) card, Flash Card, etc. The memory can also include both internal and external storage units of the electronic device. The memory can be used not only to store application software and various types of data installed on the electronic device, such as code for early warning programs used in exhibitions, but also to temporarily store data that has been output or will be output.

[0145] The communication bus can be a Peripheral Component Interconnect (PCI) bus or an Extended Industry Standard Architecture (EISA) bus, etc. This bus can be divided into an address bus, a data bus, a control bus, etc. The bus is configured to enable communication between the memory and at least one processor, etc.

[0146] The communication interface is used for communication between the aforementioned electronic device and other devices, including a network interface and a user interface. Optionally, the network interface may include a wired interface and / or a wireless interface (such as a Wi-Fi interface, Bluetooth interface, etc.), typically used to establish a communication connection between the electronic device and other electronic devices. The user interface may be a display, an input unit (such as a keyboard), and optionally, a standard wired or wireless interface. Optionally, in some embodiments, the display may be an LED display, a liquid crystal display, a touch-sensitive liquid crystal display, or an OLED (Organic Light-Emitting Diode) touchscreen, etc. The display may also be appropriately referred to as a screen or display unit, used to display information processed in the electronic device and to display a visual user interface.

[0147] Figure 3 Only electronic devices with components are shown; it will be understood by those skilled in the art that... Figure 3 The structure shown does not constitute a limitation on the electronic device and may include fewer or more components than shown, or combine certain components, or have different component arrangements.

[0148] For example, although not shown, the electronic device may also include a power supply (such as a battery) to power various components. Preferably, the power supply can be logically connected to at least one processor via a power management device, thereby enabling functions such as charging management, discharging management, and power consumption management. The power supply may also include one or more DC or AC power sources, recharging devices, power fault detection circuits, power converters or inverters, power status indicators, and other arbitrary components. The electronic device may also include various sensors, Bluetooth modules, Wi-Fi modules, etc., which will not be elaborated further here.

[0149] It should be understood that the embodiments described are for illustrative purposes only and are not limited to this structure in the scope of the patent application. The early warning program for exhibitions stored in the memory of the electronic device is a combination of multiple instructions. When run in the processor, it can realize the implementation and operation of each step of the early warning method for exhibitions.

[0150] Specifically, the processor's implementation method for the above instructions can be found in the description of the relevant steps in the corresponding embodiments in the accompanying drawings, and will not be repeated here.

[0151] When modules / units integrated into an electronic device are implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. The computer-readable storage medium can be volatile or non-volatile. For example, a computer-readable medium may include: any entity or device capable of carrying the computer program code, a recording medium, a USB flash drive, a portable hard drive, a magnetic disk, an optical disk, a computer memory, or a read-only memory (ROM).

[0152] In the several embodiments provided by this invention, it should be understood that the disclosed devices, apparatuses, and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for example, the above module division is merely a logical functional division, and other division methods may be used in actual implementation.

[0153] The modules described as separate components may or may not be physically separate. The components shown as modules may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs.

[0154] Furthermore, the functional modules in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or in the form of hardware plus software functional modules.

[0155] It will be apparent to those skilled in the art that the present invention is not limited to the details of the exemplary embodiments described above, and that the present invention can be implemented in other specific forms without departing from the spirit or essential characteristics of the present invention.

[0156] Therefore, the embodiments should be considered exemplary and non-limiting in all respects, and the scope of the invention is defined by the appended claims rather than the foregoing description. Thus, all variations falling within the meaning and scope of equivalents of the claims are intended to be embraced within the invention. No appended diagram markings in the claims should be construed as limiting the scope of the claims.

Claims

1. An early warning method applied to exhibition halls, characterized in that, include: The exhibition areas of the exhibition hall are divided and numbered to obtain an exhibition area division set; the exhibition area division set contains several exhibition areas and aisle areas; The exhibition area is divided into different exhibition areas and then modularized to obtain an exhibition area module set; Monitor the exhibition area modules to obtain pedestrian flow information in different areas of the exhibition area modules; Feature extraction is performed on the pedestrian flow information to obtain the first extraction set; The first extracted set is calculated to obtain the first training set; Based on the first training set, early warnings and alerts are issued for pedestrian traffic in different areas; The specific steps to obtain the exhibition area module set include: The exhibition area is divided into different exhibition areas based on the preset division distance. The exhibition area is divided into a warning area and a safe area. The warning area and the safe area constitute a subset of the exhibition area. The warning area and the security area are renumbered according to the exhibition area number, and several subsets of the number are classified and combined according to the exhibition area number to obtain the exhibition area module set; The specific steps for feature extraction from pedestrian flow information include: Obtain the number of people in several exhibition areas and aisle areas within a preset monitoring time period. Set the number of people in the exhibition areas and aisle areas as the number of people in the exhibition areas Zi and the number of people in the aisle Gj, respectively, i = 1, 2, 3, ..., n; j = 1, 2, 3, ..., n; where i is the number of exhibition areas and j is the number of aisle areas. The number of people in the warning areas of several exhibition areas during the monitoring period is set as the number of people under warning, Zik, k = 1, 2, 3, ..., n; k is the number of warning areas; Match the exhibits in several exhibition areas with a preset exhibit weight table to obtain the corresponding exhibit weights QTi; The labeled data items are arranged and combined in chronological order to obtain the first extraction set; The specific steps for calculating the first extracted set include: The data marked in the first extraction set are used to calculate the exhibition hall's traffic value LL using the traffic monitoring formula, which is: ； a1 and a2 are different proportionality coefficients, both of which are greater than zero; T is the duration of the monitoring period; Match the flow rate value with the preset flow rate range [P1, P2]; If LL < P1, then the visitor flow in the exhibition hall is determined to be normal and the first flow signal is generated; If P1≤LL≤P2, then the exhibition hall is determined to be partially crowded and a second flow signal is generated; If P2 < LL, then the overall crowd in the exhibition hall is determined to be crowded and a third flow signal is generated; The flow rate value, together with the first flow rate signal, the second flow rate signal, and the third flow rate signal, constitutes the first analysis set; Based on the different traffic signals in the first analysis set, the traffic flow in several exhibition areas was monitored and analyzed. The specific steps for monitoring and analyzing the flow of people in several exhibition areas include: if the first analysis set does not contain the first flow signal, then obtain the number of people Zik at the warning level for several exhibition areas and the weight of exhibits QQi corresponding to the exhibition areas; the marked data are used to calculate the warning coefficient JJX through the exhibition area flow formula, which is JJX = QQi * (Zik / Zi). The warning coefficient is matched with the preset warning threshold, and the exhibition area corresponding to the warning coefficient that is greater than the warning threshold is set as the marked area. The duration of the marked area is counted. If the duration is not greater than the warning duration, the marked area is determined to be temporarily congested and a first warning signal is generated. If the duration of congestion exceeds the warning duration, the marked area is determined to be continuously congested and a second warning signal is generated; the warning coefficient, the first warning signal, and the second warning signal constitute the second analysis set; the first analysis set and the second analysis set constitute the first training set.

2. The early warning method for exhibition halls according to claim 1, characterized in that, Also includes: Monitor the exhibition area module set and acquire image information of different areas within the exhibition area module set; Feature extraction is performed on the image information to obtain a second extraction set; The second extracted set is used to calculate the second training set; Based on the second training set, warnings and alerts are provided for lost items in different areas; The specific steps for feature extraction from image information include: Acquire exhibition area images and aisle images from several exhibition areas and aisle areas before the exhibition hall opens for business, and set them as sample exhibition area images and sample aisle images respectively; The grayscale values ​​of all pixels in the sample exhibition area image and the sample aisle image are obtained and combined in a preset order to obtain the grayscale set ZHi1 of the sample exhibition area and the grayscale set GHj1 of the sample aisle. Acquire exhibition area images and aisle images from several exhibition areas and aisle areas when the exhibition hall opens for business, and set them as monitored exhibition area images and monitored aisle images respectively; The grayscale values ​​of all pixels in the monitoring exhibition area image and the monitoring aisle image are acquired and combined in a preset order to obtain the grayscale set ZHi2 of the monitoring exhibition area and the grayscale set GHj2 of the monitoring aisle. The labeled data items are arranged and combined in chronological order to obtain the second extraction set; The specific steps for calculating the second extract set include: Obtain the grayscale sets ZHi1 (sample exhibition area), GHj1 (sample aisle), ZHi2 (monitoring exhibition area), and GHj2 (monitoring aisle) of the second extraction set. The missing value YS is calculated using an image formula: b1 and b2 are different proportionality coefficients and 0 < b1 < 1 < b2; The lost value is matched with a preset total loss threshold. If the lost value is not greater than the total loss threshold, a first lost signal is generated; if the lost value is greater than the total loss threshold, a second lost signal is generated. The lost value, the first lost signal, and the second lost signal constitute a lost analysis set. Based on different loss signals in the loss analysis set, the situation of lost items in several exhibition areas and aisle areas is monitored and analyzed; The specific steps for monitoring and analyzing lost items in several exhibition areas and aisle areas include: If the loss analysis set contains a second loss signal, the loss situation of several exhibition areas is monitored based on the second loss signal. The difference between the gray set of the monitored exhibition area and the gray set of the sample exhibition area is obtained and set as the selected difference value. The selected difference value is then matched with the loss score threshold. If the difference between the selected values ​​is not greater than the loss score threshold, it is determined that there are no lost items in the exhibition area and a first prompt signal is generated. If the difference between the selected values ​​is greater than the loss score threshold, it is determined that there is a lost item in the exhibition area and a second prompt signal is generated. If the prompt signals corresponding to several exhibition areas are all the first prompt signal, then it is determined that the lost item is located in the aisle area and a third prompt signal is generated; the first prompt signal, the second prompt signal and the third prompt signal constitute the lost item prompt set; the lost item analysis set and the lost item prompt set constitute the second training set.

3. An early warning system applied to exhibition halls, wherein the early warning system applies the early warning method described in claim 2, characterized in that, include: Area Division Module: Used to divide and number the exhibition areas of the exhibition hall, resulting in an exhibition area division set; the exhibition area division set contains several exhibition areas and aisle areas; Regional Expansion Module: Used to modularize the different exhibition areas into a set of exhibition area modules; Area monitoring module: Used to monitor the exhibition area module set and obtain pedestrian flow information and image information in different areas of the exhibition area module set; Information processing module: used to extract features from pedestrian flow information and image information respectively to obtain a first extraction set and a second extraction set; and to perform calculations on the first extraction set and the second extraction set respectively to obtain a first training set and a second training set; Early warning module: used to provide early warnings and alerts on pedestrian traffic and lost items in different areas based on the first and second training sets.

4. An early warning device applied to exhibition halls, characterized in that, The device includes at least one processor; And a memory communicatively connected to at least one processor; wherein the memory stores a computer program executable by at least one processor, the computer program being executed by at least one processor to enable at least one processor to perform the early warning method as described in claim 1 or 2.

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