CN111914793A - A kind of early warning method, device and equipment based on area population - Google Patents

Abstract

The embodiment of the specification provides an early warning method, an early warning device and early warning equipment based on the number of regional people, and the early warning method, the early warning device and the early warning equipment can be used in the field of artificial intelligence. The method comprises the following steps: acquiring a shot image corresponding to the target area; the shot image corresponds to a shooting moment; identifying the number of people in the shot image; acquiring the peak value of the number of people in the area within the early warning period after the shooting time by using the change rule of the number of people based on the number of people to be shot and the shooting time; the people number change rule is used for reflecting the people number change trend in the target area at different moments; sending first early warning information under the condition that the peak value of the number of people in the area is greater than a first people early warning threshold value; the first early warning information is used for prompting people in the target area to dredge. By the method, people in the area can be dredged in time according to the number change trend of people in different time periods, and the condition that the waiting time for a user to handle the business is long is avoided.

Description

A kind of early warning method, device and equipment based on area population

technical field

The embodiments of this specification relate to the technical field of artificial intelligence, and in particular, to an early warning method, device, and device based on the number of people in an area.

Background technique

Although the use of terminals to directly handle business online has become more popular, when dealing with some more important businesses, such as businesses that need to obtain people's signatures, fingerprints and other characteristic information, people are more inclined to complete the business processing offline. In practical applications, when handling offline business, certain business handling areas are often divided. The user handles the business in the business handling area or waits for other customers to handle the business.

However, because the resources for handling business are limited, when there are too many people who need to handle the business, a large part of them need to wait in the business handling area, and the people at the end of the team need to wait for a long time. Therefore, when there are too many people in the service handling area, the time of the people in the service handling area will be wasted, and evacuating the people in time can save the waiting time of people who need to handle the service. Therefore, there is an urgent need for a technical solution that can estimate the number of people in a target area in real time and give an early warning based on the estimated number of people.

SUMMARY OF THE INVENTION

The purpose of the embodiments of the present specification is to provide an early warning method, device and equipment based on the number of people in an area, so as to solve the problem of how to divert personnel in real time according to the number of people in the target area.

In order to solve the above-mentioned technical problem, the embodiment of this specification proposes an early warning method based on the number of people in the area, including:

Obtain at least one monitoring sample image corresponding to the target area; the monitoring sample image is marked with the number of people detected; the monitoring sample image corresponds to a monitoring time;

Determine the change rule of the number of people according to the detected number of people and the monitoring time; the change rule of the number of people is used to reflect the change trend of the number of people in the target area at different times;

shooting a shot image corresponding to the target area; the shot image corresponds to a shooting moment;

Identifying the number of people captured in the captured image; the number of people captured includes the number of people in the target area;

Based on the number of people ingested and the shooting time, using the change rule of the number of people to obtain the peak number of people in the area within the early warning period after the shooting time;

In the case that the peak number of people in the area is greater than the first number of people warning threshold, first warning information is sent; the first warning information is used to prompt to guide people in the target area.

The embodiment of this specification also proposes an early warning device based on the number of people in an area, including:

a monitoring sample image acquisition module, configured to acquire at least one monitoring sample image corresponding to the target area; the monitoring sample image is marked with the number of people detected; the monitoring sample image corresponds to a monitoring time;

The number change rule determination module is used to determine the number change rule according to the detected number of people and the corresponding monitoring time; the number of people change rule is used to reflect the change trend of the number of people in the target area at different times;

a captured image capturing module for capturing a captured image corresponding to the target area; the captured image corresponds to a capturing moment;

The number of people taken in recognition module is used to identify the number of people taken in the captured image; the number of people taken includes the number of people in the target area;

a regional population peak obtaining module, configured to obtain the regional population peak value within the early warning period after the shooting time based on the intake population and the shooting time and using the population change rule;

The early warning information issuing module is configured to issue first early warning information when the peak number of people in the area is greater than the first early warning threshold of the number of people; the first early warning information is used to prompt to guide people in the target area.

The embodiment of the present specification also proposes an early warning device based on the number of people in an area, including a memory and a processor; the memory is used to store computer instructions; the processor is used to execute the computer instructions to achieve the following steps: obtaining the corresponding at least one monitoring sample image of the target area; the monitoring sample image is marked with the number of people to be detected; the monitoring sample image corresponds to a monitoring time; the change rule of the number of people is determined according to the number of people detected and the monitoring time; the change rule of the number of people is used to reflect The changing trend of the number of people in the target area at different times; shooting a shot image corresponding to the target area; the shot image corresponds to a shooting time; identifying the number of people taken in the shot image; the number of people taken includes the target The number of people in the area; based on the number of people ingested and the shooting time, the peak number of people in the area in the early warning period after the shooting time is obtained by using the change rule of the number of people; in the case that the peak number of people in the area is greater than the first number of people early warning threshold, First warning information is issued; the first warning information is used to prompt to guide people in the target area.

In order to solve the above-mentioned technical problems, the embodiment of this specification also proposes a method for determining the change rule of the number of people, including:

Obtain at least one monitoring sample image corresponding to the target area; the monitoring sample image is marked with the number of people detected; the monitoring sample image corresponds to a monitoring time;

The change rule of the number of people is determined according to the detected number of people and the monitoring time; the change rule of the number of people is used to reflect the change trend of the number of people in the target area at different times.

The embodiment of this specification also proposes a device for determining the law of changes in the number of people, including:

a monitoring sample image acquisition module, configured to acquire at least one monitoring sample image corresponding to the target area; the monitoring sample image is marked with the number of people detected; the monitoring sample image corresponds to a monitoring time;

The number change rule determining module is used for determining the number change rule according to the detected number of people and the monitoring time; the number change rule is used to reflect the change trend of the number of people in the target area at different times.

The embodiment of the present specification also proposes a device for determining the law of changes in the number of people, including a memory and a processor; the memory is used for storing computer program instructions; the processor is used for executing the computer program instructions to achieve the following steps: obtaining Corresponding to at least one monitoring sample image of the target area; the monitoring sample image is marked with the number of people to be detected; the monitoring sample image corresponds to a monitoring time; the change rule of the number of people is determined according to the detected number of people and the monitoring time; To reflect the changing trend of the number of people in the target area at different times.

It can be seen from the technical solutions provided by the above embodiments of this specification that the embodiment of this specification obtains the variation law of the number of people in the target area corresponding to different times by analyzing the monitoring sample images, so as to capture images for the target area and identify the captured images. After the number of people in the system, the change trend of the number of people in the following period of time can be determined according to the moment when the image was taken, and then the peak number of people in the early warning period can be determined according to the change trend of the number of people. The first warning information is used to guide people in the target area. Through the above method, the number of people in the target area and the change of the number of people can be determined according to the captured images, so that even if there are many people in the target area, an early warning can be issued to guide the personnel to avoid the existence of many people in the target area. At the same time, it also ensures that personnel will not spend a lot of time waiting for the business to be processed, reducing the waste of time.

Description of drawings

In order to more clearly illustrate the technical solutions in the embodiments of the present specification or the prior art, the following briefly introduces the accompanying drawings required in the description of the embodiments or the prior art. Obviously, the accompanying drawings in the following description are only These are some embodiments described in this specification. For those of ordinary skill in the art, other drawings can also be obtained based on these drawings without any creative effort.

Fig. 1 is a flow chart of a method for determining the change rule of the number of people in the embodiment of this specification;

2 is a flow chart of an early warning method based on the number of people in an area according to an embodiment of this specification;

FIG. 3 is a block diagram of a device for determining the law of changes in the number of people according to an embodiment of the present specification;

4 is a block diagram of an early warning device based on the number of people in an area according to an embodiment of the present specification;

FIG. 5 is a structural diagram of a device for determining the change rule of the number of people according to the embodiment of this specification;

FIG. 6 is a structural diagram of an early warning device based on the number of people in an area according to an embodiment of this specification.

Detailed ways

The technical solutions in the embodiments of the present specification will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present specification. Obviously, the described embodiments are only a part of the embodiments of the present specification, rather than all the embodiments. Based on the embodiments in this specification, all other embodiments obtained by persons of ordinary skill in the art without creative efforts shall fall within the protection scope of this specification.

In order to solve the above-mentioned technical problems, an embodiment of a method for determining the change rule of the number of people in this specification will be described below with reference to FIG. 1 . The execution subject of the method may be a device for determining the change rule of the number of people, and the device includes but is not limited to a server, an industrial computer, a PC, and an intelligent terminal device. The method may include the following specific execution steps.

S110: Acquire at least one monitoring sample image corresponding to the target area; the monitoring sample image is marked with the number of people detected; the monitoring sample image corresponds to a monitoring time.

The target area is the area that needs to be identified and evacuated. The target area can be the waiting area in front of the business handling window. If there are many people in the target area, some of them may need to spend a lot of time in queuing and waiting, thus causing a certain amount of time for them. Waste, the time utilization efficiency can be improved by diverting the personnel in the target area; the target area can also be an area for storing valuables or sensitive documents and other items, when there are many people in the target area , the theft of valuables or sensitive documents may be more likely to occur, and people in the target area need to be evacuated in time. In practical applications, the target area is not limited, and the early warning methods in the embodiments of this specification can be applied to other areas that need to control the number of people in the area, which will not be repeated.

The monitoring sample image is an image obtained by photographing the target area. The monitoring sample image may be an image captured by a photographing device disposed near the target area. The photographing equipment includes, but is not limited to, a camera, a photographable mobile phone, a video camera, a monitor, and the like. When photographing the monitoring sample image, the photographing device may only photograph an image corresponding to the target area, or may photograph a larger range of images including the target area, which is not limited.

The monitoring sample image may correspond to a monitoring time. The monitoring time is used to represent the time when the monitoring sample image is taken. Through the monitoring time, the number of people in the target area corresponding to a certain time can be determined.

In some embodiments, in order to ensure that the change rule of the number of people can be clarified in the subsequent steps, a plurality of monitoring sample images at different moments in a long period of time may be obtained. For example, the monitoring sample images may be every half minute during the working period. The collected images avoid the inability to effectively obtain the changes of personnel at different times when the monitoring sample images correspond to a short period of time.

The monitoring sample image is marked with the number of people detected. The detected number of people indicates the number of people in the target area displayed according to the monitoring sample image. The detected number of persons may be the number of persons identified and marked by humans, or may be the number of persons in the target area obtained by identifying persons in the monitoring sample image by using an image recognition model. The specific implementation process of using the image recognition model to recognize the number of people can be set based on the actual application situation, and will not be repeated here.

In some embodiments, in order to ensure that the number of people in the target area can be accurately acquired, multiple photographing devices may be set at different angles, and multiple images can be photographed at the same time, so as to ensure that the target area can be comprehensively photographed. All personnel.

S120: Determine a change rule of the number of people according to the detected number of people and the monitoring time; the change rule of the number of people is used to reflect the change trend of the number of people in the target area at different times.

The change rule of the number of people is used to represent the change trend of the number of people in the target area at different times. After the detected number of people and the corresponding monitoring time are obtained, the change trend of the number of people in the target area at different times can be analyzed.

In the sample data obtained in practical applications, there may be a number of people tested on different dates at the same time, and all data can be fitted to obtain the change rule of the number of people that reflects the basic situation of the change of the number of people. The specific method for obtaining the change rule of the number of people can be adjusted based on the situation in practical application, and will not be repeated here.

Based on the above-mentioned method for determining the change rule of the number of people, an embodiment of an early warning method based on the number of people in a region according to the embodiment of the present specification is introduced. The execution subject of the method may be an early warning device based on the number of people in the area, and the device includes but is not limited to a server, an industrial computer, a PC, and an intelligent terminal device. As shown in FIG. 2 , the method may include the following specific execution steps.

S210: Acquire a photographed image corresponding to the target area; the photographed image corresponds to a photographing moment.

Captured images are images captured for real-time acquisition of the number of people in the target area. The current number of people in the target area can be acquired in real time after the captured image is acquired and the number of people is identified, so as to determine whether the number of people in the target area has met the conditions for early warning. In order to ensure the timeliness of the photographed image, after the photographed image is photographed by the photographing device, the photographed image can be immediately transmitted to the server, and the server can analyze the number of people in the target area in the image, so that the number of people in the target area can be analyzed. When it is about to reach a certain number, it will be detected and dealt with in time.

In order to be able to analyze the number of people according to the change rule of the number of people obtained in step S120, the photographed image may correspond to a photographing moment. The photographing moment is the moment when the photographed image is photographed. According to the shooting time, combined with the change rule of the number of people, the change of the number of people in the target area can be determined.

S220: Identify the number of people captured in the captured image; the number of people captured includes the number of people in the target area.

After the captured image is acquired, the number of people captured in the captured image can be identified, and the number of captured people is the number of people in the target area corresponding to the capturing moment.

In some embodiments, identifying the number of people captured may first use a clustering algorithm to obtain image features corresponding to the monitoring sample images, and then train a number recognition model based on the image features and the detected number of people corresponding to the monitoring sample images. The number recognition model is used to determine the number of persons included in the image according to the image features in the image. Therefore, the number of people captured in the captured image can be obtained after the captured image is input into the population recognition model.

In practical applications, other image recognition methods can also be used to obtain the number of people captured in the captured image, and the specific implementation process can be adjusted according to the actual application situation, which will not be repeated here.

In some embodiments, the captured image may include areas other than the target area, so that the persons included in the captured image may not be all persons in the target area. Therefore, before identifying the number of people, the target area can be determined in the captured image. A specific method for determining the target area may, for example, pre-set image features corresponding to the boundary of the target area, and determine the target area by identifying the corresponding image features in the captured image.

After the target area is determined, the detection personnel in the target area are identified. The detection person is the person located in the target area in the captured image. After all the inspecting personnel are identified, the number of inspecting personnel is counted to obtain the number of captured persons, that is, the number of personnel located in the target area when the photographed image is taken.

S230: Based on the ingested number of people and the shooting time, use the change rule of the number of people to obtain the peak number of people in the area within the early warning period after the shooting time.

After acquiring the number of people ingested and the shooting time, the change in the number of people within a certain period of time can be determined by using the above-mentioned change rule of the number of people. Since the change rule of the number of people can be used to reflect the change trend of the number of people at different times, after the shooting time is obtained, the change trend of the number of people corresponding to the shooting time can be determined, that is, the increase or decrease ratio of the number of people in a certain period of time. Based on the increase or decrease ratio, the change in the number of people in a certain period of time can be roughly determined. The changing situation of the number of people may include the number of people corresponding to several moments in the time period.

Specifically, an early warning period can be pre-determined, and based on the above steps, a change in the number of people in the early warning period after the shooting time is determined, and then the maximum number of people in the change in the number of people is obtained as the regional peak number of people.

Since the personnel changes in the target area may not completely conform to a certain regularity, an appropriate length can be selected when setting the warning period to which it belongs. When the early warning period is too long, the number of people reflected in the early warning period may also lack certain accuracy. Therefore, a shorter early warning period can be set to ensure the accuracy of the early warning.

In some embodiments, in order to realize the real-time early warning based on the number of people, when acquiring the captured image, the captured image corresponding to the target area may be captured at every interval of the image capturing period, and the image capturing period may be a preset time period, For example, one second, five seconds, half a minute, one minute, five minutes, ten minutes, half an hour, etc., there is no restriction on this. In order to ensure that there is no blank period of detection for the early warning of the number of people in the target area, the image acquisition period is set to be no greater than the early warning period, so as to avoid the situation where there are too many people at a certain moment after the early warning period and cannot perform effective early warning. Happening.

S240: When the peak number of people in the area is greater than the first number of people early warning threshold, send first early warning information; the first early warning information is used to prompt to guide people in the target area.

The first number of people warning threshold may be a preset number of people. For example, when the number of people in the target area is 0-16, it is a lower number range; when the number of people in the target area is 17-24, it may be a relatively normal number range; When the number of people in the target area is greater than 24, it is a high number of people, and some people in the target area may need to wait for a long time. At this time, the first warning threshold of the number of people can be set to be 24. When it is detected that the peak number of people in the area within the warning period will exceed 24, the number of people in the target area may be larger, and the first warning message can be issued. Used to prompt the evacuation of people in the target area.

In some embodiments, when the peak number of people in the area is greater than the first warning threshold of the number of people, first warning information may be sent to the area manager. The area manager can be a person who manages the target area, such as a lobby manager. After receiving the first warning information, the area management personnel can evacuate the personnel in the target area, for example, transfer to other business handling areas or notify some personnel to handle the business after a certain delay.

In some embodiments, when the peak number of people in the area is greater than the first warning threshold of the number of people, first warning information may be sent to the resource allocation personnel. Resource allocators are those who manage and control business processing resources. The service handling resources may be operators or terminal devices for handling services. After receiving the first warning information, the resource allocator can increase the business handling resources corresponding to the target area, for example, adding additional business handling windows or assigning additional business handling personnel to process the business, thereby Improve business processing and reduce wait times for people in target areas.

In some embodiments, after obtaining the peak number of people in the area, it can also be determined whether the peak number of people in the area is less than a second early warning threshold of the number of people. The second early warning threshold of the number of people is smaller than the first early warning threshold of the number of people, and the second early warning threshold of the number of people is used to judge whether the number of people in the target area is too small. For example, based on the example in the above embodiment, when the number of people in the target area is 0-16, and the number of people is small, the second early warning threshold of the number of people may be set to 17. When the number of people in the target area is less than the second warning threshold for the number of people, the number of people in the target area may continue to maintain a low level, that is, in the next period of time, the number of people corresponding to the target area The business processing terminal equipment of business processing personnel may be in an idle state. At this time, second early warning information may be issued, and the second early warning information is used to prompt to reduce the business processing resources corresponding to the target area, thereby reducing the idle situation of the business processing resources in the target area.

Specifically, the second early warning information may also be sent to the resource allocation personnel to reduce business processing resources.

The above-mentioned early warning method based on the number of people in the area obtains the change rule of the number of people in the target area corresponding to different times by analyzing the monitoring sample images, so that after taking an image of the target area and identifying the number of people in the captured image, it can be based on the captured image. The time of determining the change trend of the number of people within a period of time, and then determine the peak number of people in the early warning period according to the change trend of the number of people, so that when the peak number of people is higher than the threshold, the first warning information can be issued to detect the number of people in the target area. personnel to evacuate. Through the above method, the number of people in the target area and the change of the number of people can be determined according to the captured images, so that even if there are many people in the target area, an early warning can be issued to guide the personnel to avoid the existence of many people in the target area. At the same time, it also ensures that personnel will not spend a lot of time waiting for the business to be processed, reducing the waste of time.

As shown in FIG. 3 , an embodiment of the present specification further provides an apparatus for determining the change rule of the number of people, the apparatus can be integrated into the apparatus for determining the change rule of the number of people, and the apparatus includes the following modules.

The monitoring sample image acquisition module 310 is configured to acquire at least one monitoring sample image corresponding to the target area; the monitoring sample image is marked with the number of people detected; the monitoring sample image corresponds to a monitoring time;

The number change rule determination module 320 is used to determine the number change rule according to the detected number of people and the monitoring time; the number change rule is used to reflect the change trend of the number of people in the target area at different times.

As shown in FIG. 4 , an embodiment of the present specification further provides an early warning device based on the number of people in an area. The device can be integrated into the early warning device based on the number of people in the area. The device can include the following modules.

A captured image acquisition module 410, configured to capture a captured image corresponding to the target area; the captured image corresponds to a capturing moment;

The number of people taken in recognition module 420 is used to identify the number of people taken in the captured image; the number of people taken includes the number of people in the target area;

The regional population peak obtaining module 430 is configured to obtain the regional population peak value within the early warning period after the shooting time based on the intake population and the shooting time, and using the population change rule;

The early warning information issuing module 440 is configured to issue first early warning information when the peak number of people in the area is greater than the first early warning threshold of the number of people; the first early warning information is used to prompt to guide people in the target area.

As shown in FIG. 5 , an embodiment of the present specification further provides a device for determining the change rule of the number of people. The number change rule determination device may include a memory and a processor.

In this embodiment, the memory may be implemented in any suitable manner. For example, the memory may be a read-only memory, a mechanical hard disk, a solid-state hard disk, or a USB flash drive. The memory may be used to store computer program instructions.

In this embodiment, the processor may be implemented in any suitable manner. For example, a processor may take the form of, for example, a microprocessor or a processor and a computer readable medium storing computer readable program code (eg software or firmware) executable by the (micro)processor, logic gates, switches, application specific integrated circuits ( Application Specific Integrated Circuit, ASIC), programmable logic controller and embedded microcontroller form, etc.

The processor may execute the computer program instructions to achieve the following steps: acquiring at least one monitoring sample image corresponding to the target area; the monitoring sample image is marked with the number of people detected; the monitoring sample image corresponds to a monitoring time; The number of people detected and the monitoring time determine the change rule of the number of people; the change rule of the number of people is used to reflect the change trend of the number of people in the target area at different times.

As shown in FIG. 6 , an embodiment of the present specification further provides an early warning device based on the number of people in an area. The area headcount-based early warning device may include a memory and a processor.

In this embodiment, the memory may be implemented in any suitable manner. For example, the memory may be a read-only memory, a mechanical hard disk, a solid-state hard disk, or a USB flash drive. The memory may be used to store computer program instructions.

In this embodiment, the processor may be implemented in any suitable manner. For example, a processor may take the form of, for example, a microprocessor or a processor and a computer readable medium storing computer readable program code (eg software or firmware) executable by the (micro)processor, logic gates, switches, application specific integrated circuits ( Application Specific Integrated Circuit, ASIC), programmable logic controller and embedded microcontroller form, etc.

The processor can execute the computer program instructions to achieve the following steps: acquiring a shot image corresponding to the target area; the shot image corresponds to a shooting time; identifying the number of people in the shot image; is used to represent the number of people in the target area; based on the number of people taken and the shooting time, the peak number of people in the area within the early warning period after the shooting time is obtained by using the change rule of the number of people; the change rule of the number of people includes at least one sample image. The corresponding detected number of people and the law determined at the monitoring time; the change law of the number of people is used to reflect the change trend of the number of people in the target area at different times; when the peak number of people in the area is greater than the first number of people early warning threshold, the first number of people will be issued. 1. Early warning information; the first early warning information is used to prompt to guide people in the target area.

It should be noted that the early warning method, device and equipment based on the number of people in the area disclosed in the embodiments of this specification can be applied in the field of artificial intelligence technology to evacuate people according to the number of people in the area. Of course, the early warning method based on the number of people in the area , devices and equipment can also be applied to other fields, which are not limited.

In the 1990s, improvements in a technology could be clearly differentiated between improvements in hardware (eg, improvements to circuit structures such as diodes, transistors, switches, etc.) or improvements in software (improvements in method flow). However, with the development of technology, the improvement of many methods and processes today can be regarded as a direct improvement of the hardware circuit structure. Designers almost get the corresponding hardware circuit structure by programming the improved method flow into the hardware circuit. Therefore, it cannot be said that the improvement of a method flow cannot be realized by hardware entity modules. For example, a Programmable Logic Device (PLD) (eg, Field Programmable Gate Array (FPGA)) is an integrated circuit whose logic function is determined by user programming of the device. It is programmed by the designer to "integrate" a digital system on a PLD without having to ask a chip manufacturer to design and manufacture a dedicated integrated circuit chip 2 . And, instead of making integrated circuit chips by hand, these days, much of this programming is done using software called a "logic compiler", which is similar to the software compiler used in program development and writing, but before compiling The original code also has to be written in a specific programming language, which is called Hardware Description Language (HDL), and there is not only one HDL, but many kinds, such as ABEL (Advanced Boolean Expression Language) , AHDL (Altera Hardware Description Language), Confluence, CUPL (Cornell University Programming Language), HDCal, JHDL (Java Hardware Description Language), Lava, Lola, MyHDL, PALASM, RHDL (RubyHardware Description Language), etc. The most commonly used are VHDL (Very-High-Speed Integrated Circuit Hardware Description Language) and Verilog2. It should also be clear to those skilled in the art that a hardware circuit for implementing the logic method process can be easily obtained by simply programming the method process in the above-mentioned several hardware description languages and programming it into the integrated circuit.

The systems, devices, modules or units described in the above embodiments may be specifically implemented by computer chips or entities, or by products with certain functions. A typical implementation device is a computer. Specifically, the computer can be, for example, a personal computer, a laptop computer, a cellular phone, a camera phone, a smart phone, a personal digital assistant, a media player, a navigation device, an email device, a game console, a tablet computer, a wearable device, or A combination of any of these devices.

From the description of the above embodiments, those skilled in the art can clearly understand that this specification can be implemented by means of software plus a necessary general hardware platform. Based on this understanding, the technical solutions of this specification or the parts that make contributions to the prior art can be embodied in the form of software products, and the computer software products can be stored in storage media, such as ROM/RAM, magnetic disks, etc. , CD, etc., including several instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to perform the methods described in various embodiments or some parts of the embodiments in this specification.

Each embodiment in this specification is described in a progressive manner, and the same and similar parts between the various embodiments may be referred to each other, and each embodiment focuses on the differences from other embodiments. In particular, as for the system embodiments, since they are basically similar to the method embodiments, the description is relatively simple, and for related parts, please refer to the partial descriptions of the method embodiments.

This specification can be used in numerous general purpose or special purpose computer system environments or configurations. For example: personal computers, server computers, handheld or portable devices, tablet devices, multiprocessor systems, microprocessor-based systems, set-top boxes, programmable consumer electronics, network PCs, minicomputers, mainframe computers, including A distributed computing environment for any of the above systems or devices, and the like.

This specification may be described in the general context of computer-executable instructions, such as program modules, being executed by a computer. Generally, program modules include routines, programs, objects, components, data structures, etc. that perform particular tasks or implement particular abstract data types. The specification can also be practiced in distributed computing environments where tasks are performed by remote processing devices that are linked through a communications network. In a distributed computing environment, program modules may be located in both local and remote computer storage media including storage devices.

Although this specification has been described by way of examples, those of ordinary skill in the art will recognize that there are many modifications and changes to this specification without departing from the spirit of the specification, and it is intended that the appended claims include such modifications and changes without departing from the spirit of the specification.

Claims (13)

1. An early warning method based on regional population is characterized by comprising the following steps:

acquiring a shot image corresponding to a target area; the shot image corresponds to a shooting moment;

identifying the number of people in the shot image; the number of persons ingested is used to represent the number of persons in the target area;

acquiring the peak value of the number of people in the area within the early warning period after the shooting time by using the change rule of the number of people based on the number of people to be shot and the shooting time; the number of people change rule comprises a rule determined according to the number of detected people corresponding to at least one sample image and the monitoring time; the people number change rule is used for reflecting the people number change trend in the target area at different moments;

sending first early warning information under the condition that the peak value of the number of people in the area is greater than a first people early warning threshold value; the first early warning information is used for prompting people in the target area to dredge.

2. The method of claim 1, wherein said capturing a captured image corresponding to the target area comprises:

capturing a captured image corresponding to the target area every interval image acquisition period; the image acquisition time period is not greater than the early warning time period.

3. The method of claim 1, wherein the identifying the number of ingesters in the captured image comprises:

determining a target area in the shot image;

identifying detection personnel in the target area;

and counting the number of the detection personnel as the number of the persons who take the detection personnel.

4. The method of claim 1, wherein the identifying the number of ingesters in the captured image comprises:

acquiring image characteristics corresponding to the monitoring sample image by using a clustering algorithm;

training a people number recognition model according to the image characteristics and the corresponding number of detected people;

and identifying the number of the people to be shot in the shot image through the people number identification model.

5. The method of claim 1, wherein the obtaining the peak number of people in the region in the early warning period after the shooting time by using the change rule of people based on the number of people to be ingested and the shooting time comprises:

determining the number change condition in the early warning time period after the shooting time by using the number change rule based on the number of people to be shot and the shooting time;

and determining the maximum number of people in the number of people change condition as the peak number of people in the area.

6. The method of claim 1, wherein the issuing a first warning message in the event that the peak number of people in the area is greater than a first people warning threshold comprises:

and under the condition that the peak value of the number of people in the area is greater than a first number of people early warning threshold value, first early warning information is sent to area management personnel, so that the area management personnel dredge the personnel in the target area.

7. The method of claim 1, wherein the issuing a first warning message in the event that the peak number of people in the area is greater than a first people warning threshold comprises:

and under the condition that the peak value of the number of people in the area is greater than a first people early warning threshold value, first early warning information is sent to resource allocation personnel, so that the resource allocation personnel increase business handling resources corresponding to the target area.

8. The method of claim 1, wherein after obtaining the peak number of people in the area within the warning period after the shooting time by using the change rule of people based on the number of people taken and the shooting time, the method further comprises:

judging whether the peak number of people in the area is smaller than a second people number early warning threshold value or not;

sending out second early warning information under the condition that the minimum number of people in the area is smaller than the second early warning threshold number; the second early warning information is used for prompting the reduction of business handling resources corresponding to the target area.

9. The utility model provides a warning device based on regional number of people which characterized in that includes:

a photographed image acquiring module for acquiring a photographed image corresponding to the target area; the shot image corresponds to a shooting moment;

the number of people taken is identified by the number of people taken in the shot image; the number of ingesting people is used to represent the number of people in the target area;

the regional population peak value acquisition module is used for acquiring the regional population peak value in the early warning time period after the shooting time by utilizing the population change rule based on the number of the people to be shot and the shooting time; the number of people change rule comprises a rule determined according to the number of detected people corresponding to at least one sample image and the monitoring time; the people number change rule is used for reflecting the people number change trend in the target area at different moments;

the early warning information sending module is used for sending out first early warning information under the condition that the peak value of the number of people in the area is greater than a first number of people early warning threshold value; the first early warning information is used for prompting people in the target area to dredge.

10. An early warning device based on regional population comprises a memory and a processor;

the memory to store computer program instructions;

the processor, configured to execute the computer program instructions to implement the following steps: acquiring a shot image corresponding to a target area; the shot image corresponds to a shooting moment; identifying the number of people in the shot image; the number of persons ingested is used to represent the number of persons in the target area; acquiring the peak value of the number of people in the area within the early warning period after the shooting time by using the change rule of the number of people based on the number of people to be shot and the shooting time; the number of people change rule comprises a rule determined according to the number of detected people corresponding to at least one sample image and the monitoring time; the people number change rule is used for reflecting the people number change trend in the target area at different moments; sending first early warning information under the condition that the peak value of the number of people in the area is greater than a first people early warning threshold value; the first early warning information is used for prompting people in the target area to dredge.

11. A method for determining the change rule of people number is characterized by comprising the following steps:

acquiring at least one monitoring sample image corresponding to the target area; the number of detected people is marked on the monitoring sample image; the monitoring sample image corresponds to a monitoring moment;

determining the change rule of the number of people according to the number of detected people and the monitoring time; and the people number change rule is used for reflecting the people number change trend in the target area at different moments.

12. A device for determining the change rule of people number is characterized by comprising:

the monitoring sample image acquisition module is used for acquiring at least one monitoring sample image corresponding to the target area; the number of detected people is marked on the monitoring sample image; the monitoring sample image corresponds to a monitoring moment;

the people number change rule determining module is used for determining the people number change rule according to the detected people number and the monitoring time; and the people number change rule is used for reflecting the people number change trend in the target area at different moments.

13. A people number change rule determining device comprises a memory and a processor;

the memory to store computer program instructions;

the processor to execute the computer program instructions to implement the steps of: acquiring at least one monitoring sample image corresponding to the target area; the number of detected people is marked on the monitoring sample image; the monitoring sample image corresponds to a monitoring moment; determining the change rule of the number of people according to the number of detected people and the monitoring time; and the people number change rule is used for reflecting the people number change trend in the target area at different moments.

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