WO2022041905A1

WO2022041905A1 - Data processing method and apparatus, device, and storage medium

Info

Publication number: WO2022041905A1
Application number: PCT/CN2021/097662
Authority: WO
Inventors: 殷磊; 吴海山; 胡万祺; 程善钿; 曾辉
Original assignee: 深圳前海微众银行股份有限公司
Priority date: 2020-08-25
Filing date: 2021-06-01
Publication date: 2022-03-03
Also published as: CN112070463A

Abstract

A data processing method and apparatus, a device, and a storage medium. The method comprises: obtaining positioning data of users in an area to be analyzed, the positioning data comprising positioning data of each workday in a first statistical period before an epidemic situation occurs and positioning data of each workday in a second statistical period after the epidemic situation occurs; according to the obtained positioning data, determining travel intensity of the area before the epidemic situation occurs and travel intensity of the area after the epidemic situation occurs; and determining a work resumption state in the area according to the travel intensity of the area before the epidemic situation occurs and the travel intensity of the area after the epidemic situation occurs. By means of the method, a work resumption state in an area can be calculated in real time and accurately, and efficiency and accuracy of determining the work resumption state are improved.

Description

Data processing method, apparatus, equipment and storage medium

technical field

The present application relates to the field of data processing, and in particular, to a data processing method, apparatus, device and storage medium.

This application claims the priority of the Chinese patent application with the application number 202010865997.2 and the application name "Data Processing Method, Apparatus, Equipment and Storage Medium" filed with the China Patent Office on August 25, 2020, the entire contents of which are incorporated by reference in in this application.

Background technique

Production and business activities are crucial to the development of the region. When the region suffers from the epidemic, the production activities in the region will also be affected, and even stop production. After the epidemic is brought under control, various regions will gradually resume work and production to maintain a stable and orderly development of society. How to determine the resumption status of each region has become a more important issue.

At present, a tool for data analysis and processing is urgently needed to determine the resumption status of each area in time.

SUMMARY OF THE INVENTION

The main purpose of the present application is to provide a data processing method, device, equipment and storage medium, aiming at solving the technical problem that the work resumption status of each area cannot be determined in time.

To achieve the above purpose, the present application provides a data processing method, the data processing method comprising:

Obtain the positioning data of users in the area to be analyzed, the positioning data includes the positioning data of each working day in the first statistical period before the outbreak and the positioning data of each working day in the second statistical period after the outbreak;

According to the obtained positioning data, determine the travel intensity of the area before the outbreak and the travel intensity of the area after the outbreak;

According to the travel intensity of the area before the outbreak and the travel intensity of the area after the outbreak, the work resumption status of the area is determined.

In a possible implementation manner, after determining the work resumption status of the area, the method further includes:

Control the public equipment in the area according to the resumption status of the area;

And/or, sending the indication information corresponding to the work resumption status to the government service platform or the terminal device in the area.

In a possible implementation manner, controlling the public equipment in the area according to the work resumption status of the area, including:

Control the frequency increase or decrease of public transportation equipment in the area according to the resumption status of the area; and/or,

According to the resumption status of the area, some charging piles in the area are instructed to be closed.

In a possible implementation manner, the work resumption status of the area is determined according to the travel intensity of the area before the outbreak and the travel intensity of the area after the outbreak, including:

The travel intensity of each working day after the outbreak of the epidemic is compared with the travel intensity of the working day in the same period of the previous year to determine the work resumption status of the working day.

In a possible implementation manner, according to the obtained positioning data, determine the travel intensity of the area before the outbreak and the travel intensity of the area after the outbreak, including:

Calculate the travel intensity corresponding to each working day according to the obtained positioning data of each working day;

Calculate the normal travel intensity of the area according to the travel intensity on each working day before the outbreak;

Correspondingly, according to the travel intensity of the area before the outbreak and the travel intensity of the area after the outbreak, determine the work resumption status of the area, including:

According to the travel intensity on each working day after the outbreak and the normal travel intensity, determine the resumption status of the area on each working day after the outbreak.

In a possible implementation, the method further includes:

According to the travel intensity of users in the area on at least one holiday, calculate the basic travel intensity required to maintain basic operation in the area;

Correspondingly, according to the travel intensity on each working day after the outbreak and the normal travel intensity, determine the work resumption status of the area on each working day after the outbreak, including:

For each working day after the outbreak of the epidemic, the work resumption status of the working day is determined according to the travel intensity of the working day, the normal travel intensity, and the basic travel intensity.

In a possible implementation manner, according to the obtained positioning data of each working day, the travel intensity corresponding to each working day is calculated, including:

According to the obtained positioning data of users in the area, determine the resident users in the area;

According to the positioning data of each resident user, determine the place of residence of the resident user;

For each working day, the travel intensity of the working day is determined according to the residence location of each resident user in the area and the positioning data of each resident user on the working day.

In a possible implementation manner, the travel intensity of the working day is determined according to the residence location of each resident user in the area and the positioning data of each resident user on the working day, including:

For each resident user in the area, determine whether the resident user has travel behavior on the working day according to the positioning data of the resident user on the working day and the residence location of the resident user ;

The travel intensity of the working day is calculated according to the number of resident users who have travel behavior on the working day and the number of all resident users in the area.

In a possible implementation manner, the obtained positioning data includes the user's mobile phone signaling data collected through the base station;

According to the positioning data of the resident user on the working day and the residence location of the resident user, determine whether the resident user has travel behavior on the working day, including:

If, according to the mobile phone signaling data of the resident user on the working day, it is determined that the resident user is connected to the base station outside the place of residence on the working day and is not connected to the base station outside the area, then determine The resident user has travel behavior on the working day.

In a possible implementation manner, according to the positioning data of the resident user on the working day and the residence location of the resident user, it is determined whether the resident user has travel behavior on the working day, including: :

If, according to the positioning data of the resident user on the working day, it is determined that the resident user has appeared at a place other than the preset distance from the place of residence for a preset period of time, it is determined that the resident user has a presence on the working day. travel behavior.

In a possible implementation manner, according to the travel intensity of the working day, the normal travel intensity and the basic travel intensity, determining the work resumption status of the working day, including:

calculating a first difference between the travel intensity of the working day and the basic travel intensity, and a second difference between the normal travel intensity and the basic travel intensity;

According to the ratio between the first difference and the second difference, a work resumption index of the working day is determined, and the work resumption index is used to reflect the work resumption state.

The present application also provides a data processing device, comprising:

The acquisition module is used to acquire the positioning data of users in the area to be analyzed, the positioning data includes the positioning data of each working day in the first statistical period before the outbreak of the epidemic and the positioning data of each working day in the second statistical period after the outbreak of the epidemic ;

a calculation module, used to determine the travel intensity of the area before the outbreak and the travel intensity of the area after the outbreak according to the obtained positioning data;

The determining module is configured to determine the work resumption status of the area according to the travel intensity of the area before the outbreak and the travel intensity of the area after the outbreak.

In a possible implementation manner, the determining module is further configured to:

In a possible implementation manner, when the determining module controls the public equipment in the area according to the resumption state of the area, it is specifically used to:

According to the work resumption status of the area, control the shift increase or decrease of the public transportation equipment in the area; and/or, according to the work resumption status of the area, instruct some charging piles in the area to be closed.

In a possible implementation manner, when the determining module determines the work resumption state of the area according to the travel intensity of the area before the outbreak of the epidemic and the travel intensity of the area after the outbreak of the epidemic, the determining module is specifically used to:

In a possible implementation manner, the computing module is specifically used for:

Correspondingly, when determining the work resumption status of the area according to the travel intensity of the area before the outbreak and the travel intensity of the area after the outbreak, the determining module is specifically used to:

In a possible implementation manner, when calculating the travel intensity corresponding to each work day according to the obtained positioning data of each work day, the calculation module is specifically used for:

The present application also provides a data processing device, the data processing device comprising: a memory, a processor, and a data processing program stored on the memory and executable on the processor, the data processing program being The processor implements the steps of the data processing method described in any of the foregoing when executed.

The present application also provides a computer-readable storage medium, where a data processing program is stored on the computer-readable storage medium, and when the data processing program is executed by a processor, implements the steps of the data processing method according to any one of the foregoing .

The present application also provides a computer program, including program code, when the computer runs the computer program, the program code executes the method according to any one of the preceding items.

In this application, by obtaining the positioning data of users in the area to be analyzed, the positioning data includes the positioning data of each working day in the first statistical period before the outbreak and the positioning data of each working day in the second statistical period after the outbreak of the epidemic , according to the obtained positioning data, determine the travel intensity of the area before the outbreak and the travel intensity of the area after the outbreak, according to the travel intensity of the area before the outbreak and the travel intensity of the area after the outbreak, The work resumption status of the area can be calculated in real time and accurately, and the efficiency and accuracy of determining the work resumption status can be improved.

Description of drawings

1 is a schematic diagram of an application scenario provided by an embodiment of the present application;

2 is a schematic flowchart of a data processing method provided by an embodiment of the present application;

3 is a schematic flowchart of another data processing method provided by an embodiment of the present application;

FIG. 4 is a schematic diagram of a principle for determining a work resumption index according to an embodiment of the present application;

FIG. 5 is a schematic flowchart of determining a work resumption index after the Spring Festival provided by an embodiment of the present application;

FIG. 6 is a schematic diagram of a change in a work resumption index provided by an embodiment of the present application;

FIG. 7 is a schematic diagram of a comparison of the change of the resumption index in different regions according to an embodiment of the present application;

FIG. 8 is a schematic diagram of a comparison of the changes in the work resumption index in different years provided by the embodiment of the present application;

FIG. 9 is a schematic structural diagram of a data processing apparatus provided by an embodiment of the present application;

FIG. 10 is a schematic structural diagram of a data processing device according to an embodiment of the present application.

The realization, functional characteristics and advantages of the purpose of the present application will be further described with reference to the accompanying drawings in conjunction with the embodiments.

detailed description

Exemplary embodiments of the present application will be described in more detail below with reference to the accompanying drawings. While exemplary embodiments of the present application are shown in the drawings, it should be understood that the present application may be embodied in various forms and should not be limited by the embodiments set forth herein. Rather, these embodiments are provided so that the application will be more thoroughly understood, and will fully convey the scope of the application to those skilled in the art.

After the outbreak of the epidemic, determining the state of work resumption in the region is of great significance to the life and economy of the region. In some schemes, the state of resumption of work in the region can be assessed by visiting local enterprises and collecting information on the resumption of work of the enterprises. However, this solution is time-consuming, labor-intensive, and less accurate.

In order to solve this problem, the embodiment of the present application provides a solution, which can collect the positioning data of users in the area, determine the travel intensity change of the area before and after the epidemic according to the positioning data, and determine the area after the epidemic according to the change of travel intensity. The resumption status can be used to indicate the resumption status of each unit in the area, such as government departments, enterprises and businesses. Since the resumption status is closely related to the user's travel, based on the travel intensity of the area, you can quickly , Accurately realize the calculation of the resumption state, and improve the efficiency and accuracy of determining the resumption state.

FIG. 1 is a schematic diagram of an application scenario provided by an embodiment of the present application. As shown in Figure 1, a user can move with a terminal device such as a mobile phone in daily life, and the base station can obtain the user's positioning data by communicating with the terminal device, and the positioning data can be, for example, the user's mobile phone signaling data. For a specific area, the number of base stations, users and terminal devices in the area may be multiple. Mobile phone signaling data records that a certain user appears in the coverage of a certain base station at a certain time, so as to realize the positioning of the user.

The data processing equipment can be used as a data analysis and processing tool to obtain the user's positioning data from the base station. After the positioning data is obtained, the corresponding work resumption status can be calculated and output through the set program.

In addition, the data processing device can further interact with other devices after obtaining the resumption state. Optionally, the data processing device may be communicatively connected to a terminal device, a government service platform, a public device, and the like.

The data processing device can encapsulate the resumption status in the instruction information and send it to the terminal device or the government service platform, so that the user or the government system can know the resumption status of the area in time, so as to guide life or work according to the resumption status, so as to provide Convenience for users and governments.

Alternatively, it is also possible to send control information to the public equipment in the area according to the work resumption status, so as to control the public equipment, such as adjusting the number of trips of the public transport equipment, so that the scheduling of public transport meets the needs of work resumption and avoids the need for Waste of resources.

Some embodiments of the present application will be described in detail below with reference to the accompanying drawings. The following embodiments and features in the embodiments may be combined with each other without conflict between the embodiments.

FIG. 2 is a schematic flowchart of a data processing method provided by an embodiment of the present application. The execution body of the method in this embodiment may be a data processing device. The data processing device can be any device with data processing functions, such as a computer and the like. The method in this embodiment may be implemented by software, hardware, or a combination of software and hardware. As shown in Figure 2, the method may include:

Step 201: Obtain positioning data of users in the area to be analyzed, where the positioning data includes the positioning data of each working day in the first statistical period before the outbreak and the positioning data of each working day in the second statistical period after the outbreak.

Wherein, the area may refer to any area that needs to be analyzed for the state of resumption of work. Optionally, the area may be a city, or an urban area within a city, or an area divided in any other manner.

The positioning data of the users in the area can be determined in various ways. Optionally, the positioning data may be obtained directly from the base station in the manner shown in FIG. 1 . Alternatively, the base station may send the positioning data to an operator server communicatively connected to the base station, and the data processing device may acquire the positioning data from the operator server.

Optionally, multiple base stations may be set in the area, and by counting the positioning data obtained by all base stations in the area, the positioning data of each user appearing in the area may be determined.

In other optional implementation manners, the positioning data may also be acquired through the positioning module of the terminal device. For example, the terminal device can realize positioning through a GPS (Global Positioning System, global positioning system) module, and the data processing device can obtain the GPS positioning data of each user terminal, and determine the area where the user is located by means of an address fence or the like.

In terms of time dimension, the positioning data may include the positioning data of each working day in the first statistical period before the outbreak of the epidemic and the positioning data of each working day in the second statistical period after the outbreak of the epidemic.

Among them, the start time of the epidemic can be input by the staff. Alternatively, the data processing device can be connected to a platform for epidemic statistics, and the start time of the outbreak can be directly obtained through the platform.

The first statistical period and the second statistical period can be set according to actual needs. The first statistical period may include multiple days, or may include only one day. The first statistical period may be a continuous period or a discontinuous period. The first statistical period may be close to the start time of the epidemic, or may have a certain interval from the start time of the epidemic.

For example, assuming that the epidemic starts on December 1 and the first statistical period is two months, the first statistical period can be from October 1 to November 30, or it can be September 1 31st October. Of course, considering the timeliness of the data, the first statistical period should not be too far apart from the start of the epidemic.

Similarly, the second statistical period may also include multiple days, or may include only one day. When the work resumption status of a certain day or days needs to be counted, the second statistical period may be the corresponding day or days. The second statistical period may also be close to the start time of the epidemic or have a certain time interval from the start of the epidemic.

Step 202 , according to the acquired positioning data, determine the travel intensity of the area before the outbreak and the travel intensity of the area after the outbreak.

Wherein, the travel intensity may be used to indicate what proportion of users travel in the area every day, that is, the ratio of the number of users traveling every day in the area to the total number of users. According to the positioning data of each user every day, it can be determined whether the user has traveled on that day, so as to count the travel intensity of the area.

Step 203: Determine the work resumption status of the area according to the travel intensity of the area before the outbreak and the travel intensity of the area after the outbreak.

Optionally, if the travel intensity of the area on one or more days after the outbreak of the epidemic reaches or is close to the average travel intensity of the area before the outbreak, it can be determined that the area has fully resumed work or is close to complete resumption of work. .

There may be various manifestations of the resumption state. Optionally, the resumption status can be divided into several types: not resumed, resumed; or, not resumed, nearly fully resumed, and fully resumed. By analyzing the travel intensity of the area, it can be determined which of the above-mentioned current work resumption states in the area is, so as to realize a qualitative analysis of the work resumption state.

Alternatively, in order to achieve a more detailed analysis of the state of resumption of work, the resumption of work index can be used to characterize the state of resumption of work. The work resumption index can be a continuously changing value, for example, it can be the ratio of the travel intensity after the outbreak of the epidemic to the travel intensity before the outbreak of the epidemic, and a quantitative analysis of the state of work resumption can be achieved through the work resumption index.

In practical applications, the solution provided in this embodiment may be used to collect positioning data of users in an area, and output the work resumption status of the area by analyzing and processing the positioning data. The state of resumption of work can reflect the economic recovery situation of the area to a certain extent, so that it is possible to realize the evaluation of the economic recovery situation by analyzing the collected data.

The data processing method provided by this embodiment obtains the positioning data of users in the area to be analyzed, the positioning data includes the positioning data of each working day in the first statistical period before the outbreak of the epidemic, and the positioning data of each working day in the second statistical period after the outbreak of the epidemic. The positioning data of working days, according to the obtained positioning data, determine the travel intensity of the area before the outbreak and the travel intensity of the area after the outbreak, according to the travel intensity of the area before the outbreak and after the outbreak. The travel intensity of the area can be calculated in real time and accurately, and the efficiency and accuracy of determining the resumption state can be improved.

On the basis of the technical solutions provided in the above embodiments, optionally, after the work resumption status of the area is determined, it is also possible to: control the public equipment in the area according to the work resumption status of the area; and /or, send the indication information corresponding to the work resumption status to the government service platform or the terminal device in the area.

Optionally, control the public equipment in the area according to the work resumption status of the area, including:

Wherein, the public equipment may include public transportation equipment such as bus, subway, etc., according to the resumption state of the area, the scheduling control of the public transportation equipment can be realized. For example, when the resumption index increases, the public transportation in the area will be increased. The shifts of equipment, when the resumption index decreases, reduce the shifts of public transportation equipment in the area. Alternatively, the public equipment may include other equipment such as charging piles in urban areas. When the work resumption index is low, some charging piles may be instructed to close, no longer provide the charging function, and reduce standby energy consumption.

By controlling the public equipment in the area through the resumption state, the public equipment can be matched with the current resumption state, and the waste of resources can be reduced on the basis of meeting the resumption demand.

In addition, after the work resumption state is determined, the indication information corresponding to the work resumption state may also be sent to the government service platform or the terminal device in the area. The terminal device may be a terminal device of an ordinary user or a terminal device of a company or a merchant. The government service platform may be any platform provided by the government.

The indication information may include the work resumption state, or the indication information may include suggestion information corresponding to the work resumption state, and the like. For example, the instruction information sent to the government service platform can be: the resumption index reaches 80%, restaurants are recommended to open, or, the resumption index reaches 95%, theaters are recommended to open, etc.

After the resumption of work status is determined, the corresponding instruction information is sent to the government service platform or terminal device, so that the government, enterprises, and users can be informed of the current resumption of work in a timely manner, provide convenience for enterprises and users, and ensure the orderly progress of resumption of work and production.

On the basis of the technical solutions provided in the above embodiments, optionally, according to the obtained positioning data, determining the travel intensity of the area before the outbreak and the travel intensity of the area after the outbreak may include: according to the obtained location data According to the location data of each working day that arrives, the travel intensity corresponding to each working day is calculated; according to the travel intensity of each working day before the outbreak, the normal travel intensity of the area is calculated. Correspondingly, according to the travel intensity of the area before the outbreak and the travel intensity of the area after the outbreak, determining the work resumption status of the area may include: according to the travel intensity of each working day after the outbreak and the normal travel Intensity, to determine the resumption status of the said area on working days after the outbreak.

Specifically, for the first statistical period before the outbreak, a normal travel intensity is determined based on the travel intensity of each working day. For the second statistical period after the outbreak, for each working day, the work resumption status corresponding to that working day is calculated separately. Alternatively, the travel intensity of each working day in the second statistical period can also be combined to determine the overall work resumption status of the area in the second statistical period after the outbreak of the epidemic.

Determine the normal travel intensity according to the positioning data before the outbreak, and compare the travel intensity after the outbreak with the normal travel intensity, so as to quickly and accurately determine whether the travel intensity after the outbreak has returned to the level before the outbreak, and improve the efficiency of calculation .

Wherein, the normal travel intensity may be an average value of the travel intensity of each working day in the first statistical period before the outbreak of the epidemic. The specific calculation method of the normal travel intensity will be described in detail in the following embodiments.

In other optional implementation manners, the normal travel intensity may not be calculated. For example, the travel intensity of each working day after the outbreak of the epidemic can be compared with the travel intensity of the working day in the same period of the previous year to determine the travel intensity of the working day. Restoration status.

FIG. 3 is a schematic flowchart of another data processing method provided by an embodiment of the present application. As shown in Figure 3, the method includes:

Step 301: Obtain the positioning data of users in the area to be analyzed, where the positioning data includes the positioning data of each working day in the first statistical period before the outbreak and the positioning data of each working day in the second statistical period after the outbreak.

In this embodiment, for the specific implementation principle and process of step 301, reference may be made to the foregoing embodiments, and details are not repeated here.

Step 302: Calculate the travel intensity corresponding to each work day according to the obtained positioning data of each work day.

The travel intensity may include the ratio of the number of resident users who have travel behavior in the area to the number of all resident users.

Optionally, calculating the travel intensity corresponding to each working day according to the obtained positioning data of each working day, may include: determining the resident users in the said area according to the obtained positioning data of the users in the said area; According to the positioning data of each resident user, the place of residence of the resident user is determined; for each working day, the place of residence of each resident user in the area and the location of each resident user on the working day are determined. data to determine the intensity of travel on the working day.

Specifically, resident users in the area may be determined first according to the positioning data of users in the area, and the resident users may refer to residents of the area and non-residents who live in the area for a long time.

Optionally, the resident user may be a user whose total duration of appearing in the area during the statistical period reaches the residence duration threshold, so that users who temporarily enter the area can be eliminated, thereby improving the accuracy of calculation.

The statistical period may be set according to actual needs. Optionally, the statistical period may include a first statistical period before the outbreak of the epidemic and a second statistical period after the outbreak of the epidemic, so as to use the existing data to calculate the resident users and improve the utilization rate of the data.

After the resident users in the area are determined, the residence location of each resident user, that is, the user's residence, may be further determined. For a single resident user, in the statistical period, the place with the longest occurrence time can be used as the place of residence of the user.

Finally, for each working day, the travel intensity of the working day may be determined based on the residence of each resident user in the area and the positioning data of each resident user on the working day.

Optionally, determining the travel intensity of the working day based on the residence location of each resident user in the area and the positioning data of each resident user on the working day may include: for each resident user in the area. The resident user, according to the positioning data of the resident user on the working day and the residence of the resident user, determine whether the resident user has travel behavior on the working day; The number of behavioral resident users and the number of all resident users in the area are used to calculate the travel intensity of the working day.

In an example, the acquired positioning data may include mobile phone signaling data of the user collected by the base station. Correspondingly, according to the location data of the resident user on the working day and the place of residence of the resident user, determining whether the resident user has travel behavior on the working day may include: if according to the The mobile phone signaling data of the resident user on the working day, if it is determined that the resident user is connected to a base station outside the place of residence on the working day and is not connected to a base station outside the area, then the resident user is determined to be The user travels on the working day.

Specifically, the mobile phone signaling data can indicate which base station the user's mobile phone is connected to at which time, and the user's residence can be the location covered by the base station with the longest mobile phone connection time. If the user's mobile phone is connected to a base station other than the residence , then it can be considered that the user has traveled on that day, so as to easily and quickly realize the judgment of whether the user has traveled. In addition, it can further restrict that the mobile phone is not connected to the base station outside the area, that is, the user does not go out of the area on that day, and it is determined that the user has travel behavior on that day. The travel behavior under this restriction is related to the resumption state, so it can be more accurate. Calculate the return to work status.

Besides, it is also possible to determine whether the user appears at a place other than the place of residence on the working day by using GPS positioning data, etc., so as to determine whether the user has travel behavior.

After obtaining whether each resident user has travel behavior in a certain working day, the ratio of the number of resident users with travel behavior to the number of all resident users can be used as the travel of the area on the working day strength.

Step 303: Calculate the normal travel intensity according to the travel intensity on each working day before the outbreak of the epidemic.

For each working day before and after the outbreak, the travel intensity on that day can be calculated using the method provided in the previous step. According to the travel intensity of each working day before the outbreak, the normal travel intensity can be calculated. The normal travel intensity reflects the normal travel intensity of the area in the absence of an epidemic.

Optionally, the average travel intensity of all working days in the first statistical period before the outbreak of the epidemic may be used as the normal travel intensity. Certainly, some other designs may also be introduced, for example, after removing the too high or too low travel intensity, the remaining travel intensity is averaged, which is not limited in this embodiment.

Step 304: Calculate the basic travel intensity required to maintain basic operation in the area according to the travel intensity of the user in the area on at least one holiday.

In this embodiment, the basic travel intensity may be calculated by the travel intensity of holidays, and the holidays may be some or all of the holidays in the statistical period. The basic travel intensity can reflect the travel level required to maintain basic operation in the area, does not change significantly with time and events, and is a relatively stable value.

When determining the basic travel intensity, the travel intensity corresponding to each day of the holiday may be calculated, and the basic travel intensity may be the average or minimum value of the travel intensity corresponding to each holiday. The method for calculating the travel intensity on holidays is similar to the method for calculating the travel intensity on weekdays. For details, reference may be made to step 303, which will not be repeated here.

Of course, the basic travel intensity can also be calculated in other ways, for example, the basic travel intensity of the area can be determined by a method of manual research. Alternatively, the minimum travel intensity of the region in the previous year before the outbreak of the epidemic can be calculated as the basic travel intensity of the region.

Step 305 , for each working day after the outbreak, according to the travel intensity of the working day, the normal travel intensity, and the basic travel intensity, determine the work resumption status of the working day.

In this embodiment, step 305 can be used to determine the work resumption status of the area on each working day after the outbreak of the epidemic according to the travel intensity of each working day after the outbreak of the epidemic and the normal travel intensity.

As mentioned above, the state of resumption of work can be specifically characterized by the resumption of work index. FIG. 4 is a schematic diagram of a principle for determining a work resumption index according to an embodiment of the present application. As shown in Figure 4, in order to determine the work resumption status of an area, the normal travel intensity of the area can be determined through the location data of the working days before the outbreak, and the location data of the working days after the outbreak can be used to determine the normal travel intensity of the area after the outbreak. Daily travel intensity, through the positioning data of holidays, determine the basic travel intensity of the area.

Determining the work resumption status of the working day according to the travel intensity of the working day, the normal travel intensity and the basic travel intensity may include: calculating the difference between the travel intensity of the working day and the basic travel intensity. the first difference, the second difference between the normal travel intensity and the basic travel intensity; according to the ratio between the first difference and the second difference, determine the resumption of work on the working day index, the work resumption index is used to reflect the work resumption status. The larger the resumption index, the better the resumption of work in the region, and the better the economic recovery in the region accordingly. For details, please refer to the following formula:

S=(D-M)/(A-M) (1)

Among them, S is the work resumption index of the working day, D is the travel intensity of the working day, M is the basic travel intensity of the area, and A is the normal travel intensity of the area. The larger the value of S, the better the resumption of work in the area. If the value of S is 1, it means that the area has fully returned to normal. The above formula can quickly calculate the resumption index and save computing resources.

Optionally, the resumption index can take a value between 0 and 1. If the resumption index calculated by the formula is greater than 1, take the resumption index of the day as 1; if the resumption index calculated by the formula is less than 0, take The resumption index for the day is 0, which limits the resumption index between 0 and 1 for the convenience of users.

The data processing method provided in this embodiment can determine the normal travel intensity of the area through the positioning data of the working days before the outbreak of the epidemic, determine the basic travel intensity of the area through the positioning data of holidays, and determine the basic travel intensity of the area according to the normal travel intensity, The basic travel intensity comprehensively calculates the travel intensity of each working day after the outbreak of the epidemic. Since the basic travel intensity required to maintain basic operations is considered in the calculation, the calculated ratio is more in line with the actual work resumption index, which further improves the accuracy of the results. .

On the basis of the technical solutions provided in the foregoing embodiments, optionally, according to the positioning data of the resident user on the working day and the residence of the resident user, it is determined that the resident user is in the Whether there is a travel behavior on weekdays may include: if it is determined that the resident user has appeared at a place beyond the preset distance from the place of residence for a preset period of time according to the positioning data of the resident user on the working day, determining the The resident user has travel behavior on the working day.

The preset distance and preset duration can be set according to actual needs. Optionally, the preset distance may be 1 km, and the preset time may be half an hour. If a resident user stays at a place 1 km away from the place of residence for half an hour on a certain day, it can be determined that the resident user has travel behavior on that day. Therefore, the effective travel behavior of the user can be quickly detected, and the accuracy of data processing can be improved.

A specific example of calculating the resumption index is given below in combination with the above implementation process. Assuming that the first day of the Spring Festival is the start of the epidemic, in order to combat the epidemic, during the Spring Festival and for a long time after the Spring Festival, various places have stopped work and production, and the whole people have self-isolated. As the epidemic is gradually brought under control, and after orderly preparations for epidemic prevention, various places have begun to resume work and production.

Specifically, the positioning data of N1 working days before the Spring Festival, 7 days after the Spring Festival holiday and N2 working days after the Spring Festival in a certain area can be collected. The positioning data records the presence of a user at a certain base station at a certain moment.

Through the positioning data, the ratio of the number of resident users with travel in the area to the total number of resident users in the area can be calculated once a day, which is defined as the travel intensity of the area. Among them, only users whose total time in the area reaches a certain threshold within (N1+7+N2) days of the statistical period are considered as resident users in this area, so that some users who temporarily enter the area are excluded. For a single user, within the evaluation time range, the place with the longest appearance time is the user's place of residence, and whether the user has traveled is determined by whether each user appears in a place other than the place of residence in one day.

FIG. 5 is a schematic flowchart of determining a work resumption index after the Spring Festival provided by an embodiment of the present application. As shown in Figure 5, the travel intensity of the area for N1 working days before the Spring Festival is taken, the average value is calculated, and it is defined as the normal travel intensity, and this value is used to reflect the normal level of the area before the festival. The average or minimum value of the travel intensity in the area during the 7-day Spring Festival holiday is taken as the basic travel intensity, and this value reflects the travel intensity required for the area to maintain basic operation.

For a day T1 after the Spring Festival holiday, calculate the travel intensity on the day, and then according to the travel intensity on the day and the normal travel intensity and basic travel intensity obtained earlier, the resumption index on the day of T1 can be obtained, thus reflecting the resumption of work in the area described on the day of T1.

For example, assuming that N1=90, N2=60, and there are 10,000 resident users in the area, if 2,000 people out of 10,000 people travel on a certain day, then the travel intensity on that day is 20%. For the 90 working days before the Spring Festival, the daily travel intensity is calculated to obtain the average travel intensity of the first 90 working days, which is recorded as the normal travel intensity, which is assumed to be 50%. For the 7 days of the Spring Festival, the daily travel intensity is calculated, and the minimum value of the travel intensity is obtained, which is recorded as the basic travel intensity, which is assumed to be 20%.

Then, calculate the travel intensity of a certain day or a few days in the 60 working days after the Spring Festival. If the travel intensity reaches 50%, the corresponding work resumption index can be determined to be 1 according to formula (1), then it can be considered that the work resumption status of the area has been Back to normal, if it's only 35%, then it can be considered half back. According to the work resumption index of the area, it is possible to interact with the devices in the area to provide convenience for users and enterprises in the area.

FIG. 6 is a schematic diagram of a change of a work resumption index according to an embodiment of the present application. As shown in Figure 6, the horizontal axis represents time (format: month-day), and the vertical axis represents the resumption of work index. During the Spring Festival (1-26 to 2-2), the resumption of work index reached the lowest level. After the Spring Festival, the resumption of work index showed a The trend of gradually rising, in which the resumption of work index will increase and decrease periodically, because the travel intensity on weekdays will increase, and the travel intensity on weekends will drop. As can be seen from Figure 6, after the Spring Festival, as the epidemic is gradually brought under control, the resumption of work is gradually recovering.

Further, on this basis, a comparison chart of the resumption index of various regions can also be made. FIG. 7 is a schematic diagram of comparison of work resumption index changes in different regions according to an embodiment of the present application. As shown in Figure 7, the dotted line represents the change of the resumption index of city A, and the solid line represents the change of the resumption index of city B. Through the curves shown in the figure, the resumption index between different regions can be visually checked.

In addition, a comparison chart of the resumption index of each year can be made. FIG. 8 is a schematic diagram of a comparison of changes in the work resumption index in different years according to an embodiment of the present application. The vertical axis in the figure represents the resumption index, and the horizontal axis represents time. Since the Gregorian calendar dates corresponding to the Spring Festival in different years are different, the 0 on the horizontal axis in the figure represents the day of the Spring Festival, and the subsequent numbers represent the days after the Spring Festival. The dotted line in the figure represents the change trend of the work resumption index in the years when the epidemic did not occur, and the solid line represents the change trend of the work resumption index in the year when the epidemic occurred. It can be seen from Figure 8 that in the absence of an epidemic, the work resumption index will rapidly increase to 1 after the Spring Festival holiday, while in the case of an epidemic, the work resumption index will rise slowly after the Spring Festival holiday, which intuitively reflects the epidemic situation. Comparison between years and years without outbreaks.

FIG. 9 is a schematic structural diagram of a data processing apparatus according to an embodiment of the present application. As shown in FIG. 9, the data processing apparatus may include:

The acquisition module 901 is used to acquire the positioning data of the users in the area to be analyzed, the positioning data includes the positioning data of each working day in the first statistical period before the outbreak of the epidemic and the positioning of each working day in the second statistical period after the outbreak of the epidemic data;

A calculation module 902, configured to determine, according to the obtained positioning data, the travel intensity of the area before the outbreak and the travel intensity of the area after the outbreak;

The determination module 903 is configured to determine the work resumption state of the area according to the travel intensity of the area before the outbreak and the travel intensity of the area after the outbreak.

The data processing device provided in this embodiment can be used to implement the technical solutions provided by any of the foregoing method embodiments, and its implementation principle and technical effect are similar. All are better.

In a possible implementation manner, the determining module 903 is further configured to:

In a possible implementation manner, when the determining module 903 controls the public equipment in the area according to the work resumption state of the area, it is specifically configured to:

In a possible implementation manner, the determining module 903 is specifically used for determining the work resumption status of the area according to the travel intensity of the area before the outbreak of the epidemic and the travel intensity of the area after the outbreak of the epidemic:

In a possible implementation manner, the computing module 902 is specifically used for:

Correspondingly, when the determining module 903 determines the work resumption status of the area according to the travel intensity of the area before the outbreak of the epidemic and the travel intensity of the area after the outbreak of the epidemic, it is specifically used to:

In a possible implementation manner, the computing module 902 is further configured to:

Correspondingly, when the determining module 903 determines the work resumption status of the area on each working day after the outbreak of the epidemic according to the travel intensity of each working day after the outbreak of the epidemic and the normal travel intensity, it is specifically used to:

In a possible implementation manner, when calculating the travel intensity corresponding to each work day according to the obtained positioning data of each work day, the calculation module 902 is specifically used for:

In a possible implementation manner, the computing module 902 determines the travel intensity of the working day by using the residence location of each resident user in the area and the positioning data of each resident user on the working day. , specifically for:

When determining whether the resident user has travel behavior on the working day according to the positioning data of the resident user on the working day and the place of residence of the resident user, the calculation module 902 is specifically used to: :

In a possible implementation manner, the computing module 902 determines that the resident user is on the working day according to the positioning data of the resident user on the working day and the residence location of the resident user When there is a travel behavior, it is specifically used for:

In a possible implementation manner, when the determining module 903 determines the work resumption state of the working day according to the travel intensity of the working day, the normal travel intensity and the basic travel intensity, the determining module 903 is specifically configured to:

The data processing apparatus provided in any of the foregoing embodiments is used to execute the technical solutions of any of the foregoing method embodiments, and the implementation principles and technical effects thereof are similar, and details are not described herein again.

FIG. 10 is a schematic structural diagram of a data processing device according to an embodiment of the present application. As shown in FIG. 10, the apparatus may include: a memory 1001, a processor 1002, and a data processing program stored on the memory 1001 and executable on the processor 1002, the data processing program being processed by the When the controller 1002 is executed, the steps of the data processing method described in any of the foregoing embodiments are implemented.

Optionally, the memory 1001 may be independent or integrated with the processor 1002 .

For the implementation principle and technical effect of the device provided in this embodiment, reference may be made to the foregoing embodiments, and details are not repeated here.

Embodiments of the present application further provide a computer-readable storage medium, where a data processing program is stored on the computer-readable storage medium, and when the data processing program is executed by a processor, the data processing described in any of the foregoing embodiments is implemented steps of the method.

The embodiment of the present application further provides a computer program, including program code, when the computer runs the computer program, the program code executes the method described in any of the foregoing embodiments.

In the several embodiments provided in this application, it should be understood that the disclosed apparatus and method may be implemented in other manners. For example, the device embodiments described above are only illustrative. For example, the division of the modules is only a logical function division. In actual implementation, there may be other division methods. For example, multiple modules may be combined or integrated. to another system, or some features can be ignored, or not implemented.

The above-mentioned integrated modules implemented in the form of software functional modules may be stored in a computer-readable storage medium. The above-mentioned software function modules are stored in a storage medium, and include several instructions to cause a computer device (which may be a personal computer, a server, or a network device, etc.) or a processor to execute some steps of the methods described in the various embodiments of the present application.

It should be understood that the above-mentioned processor may be a central processing unit (Central Processing Unit, referred to as CPU), or other general-purpose processors, digital signal processors (Digital Signal Processor, referred to as DSP), application specific integrated circuit (Application Specific Integrated Circuit, Referred to as ASIC) and so on. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like. The steps of the method disclosed in conjunction with the invention can be directly embodied as executed by a hardware processor, or executed by a combination of hardware and software modules in the processor.

The memory may include high-speed RAM memory, and may also include non-volatile storage NVM, such as at least one magnetic disk memory, and may also be a U disk, a removable hard disk, a read-only memory, a magnetic disk or an optical disk, and the like.

The above-mentioned storage medium may be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read only memory (EEPROM), erasable Except programmable read only memory (EPROM), programmable read only memory (PROM), read only memory (ROM), magnetic memory, flash memory, magnetic disk or optical disk. A storage medium can be any available medium that can be accessed by a general purpose or special purpose computer.

An exemplary storage medium is coupled to the processor, such that the processor can read information from, and write information to, the storage medium. Of course, the storage medium can also be an integral part of the processor. The processor and the storage medium may be located in Application Specific Integrated Circuits (ASIC for short). Of course, the processor and the storage medium may also exist in the electronic device or the host device as discrete components.

It should be noted that, herein, the terms "comprising", "comprising" or any other variation thereof are intended to encompass non-exclusive inclusion, such that a process, method, article or device comprising a series of elements includes not only those elements, It also includes other elements not expressly listed or inherent to such a process, method, article or apparatus. Without further limitation, an element qualified by the phrase "comprising a..." does not preclude the presence of additional identical elements in a process, method, article or apparatus that includes the element.

The above-mentioned serial numbers of the embodiments of the present application are only for description, and do not represent the advantages or disadvantages of the embodiments.

From the description of the above embodiments, those skilled in the art can clearly understand that the method of the above embodiment can be implemented by means of software plus a necessary general hardware platform, and of course can also be implemented by hardware, but in many cases the former is better implementation. Based on this understanding, the technical solution of the present application can be embodied in the form of a software product in essence or in a part that contributes to the prior art, and the computer software product is stored in a storage medium (such as ROM/RAM, magnetic disk, CD-ROM), including several instructions to make a terminal device (which may be a mobile phone, a computer, a server, an air conditioner, or a network device, etc.) execute the methods described in the various embodiments of this application.

The above are only the preferred embodiments of the present application, and are not intended to limit the patent scope of the present application. Any equivalent structure or equivalent process transformation made by using the contents of the description and drawings of the present application, or directly or indirectly applied in other related technical fields , are similarly included within the scope of patent protection of this application.

Claims

A data processing method, comprising:

Obtain the positioning data of users in the area to be analyzed, the positioning data includes the positioning data of each working day in the first statistical period before the outbreak and the positioning data of each working day in the second statistical period after the outbreak;

According to the obtained positioning data, determine the travel intensity of the area before the outbreak and the travel intensity of the area after the outbreak;

According to the travel intensity of the area before the outbreak and the travel intensity of the area after the outbreak, the work resumption status of the area is determined.
The method according to claim 1, wherein after determining the work resumption status of the area, further comprising:

Control the public equipment in the area according to the resumption status of the area;

And/or, sending the indication information corresponding to the work resumption status to the government service platform or the terminal device in the area.
The method according to claim 2, characterized in that, controlling the public equipment in the area according to the work resumption state of the area, comprising:

Control the frequency increase or decrease of public transportation equipment in the area according to the resumption status of the area; and/or,

According to the resumption status of the area, some charging piles in the area are instructed to be closed.
The method according to any one of claims 1 to 3, wherein determining the work resumption status of the area according to the travel intensity of the area before the outbreak of the epidemic and the travel intensity of the area after the outbreak of the epidemic includes:

The travel intensity of each working day after the outbreak of the epidemic is compared with the travel intensity of the working day in the same period of the previous year to determine the work resumption status of the working day.
The method according to any one of claims 1 to 3, wherein, according to the obtained positioning data, determining the travel intensity of the area before the outbreak and the travel intensity of the area after the outbreak, including:

Calculate the travel intensity corresponding to each working day according to the obtained positioning data of each working day;

Calculate the normal travel intensity of the area according to the travel intensity on each working day before the outbreak;

Correspondingly, according to the travel intensity of the area before the outbreak and the travel intensity of the area after the outbreak, determine the work resumption status of the area, including:

According to the travel intensity on each working day after the outbreak and the normal travel intensity, determine the resumption status of the area on each working day after the outbreak.
The method of claim 5, further comprising:

According to the travel intensity of users in the area on at least one holiday, calculate the basic travel intensity required to maintain basic operation in the area;

Correspondingly, according to the travel intensity on each working day after the outbreak and the normal travel intensity, determine the work resumption status of the area on each working day after the outbreak, including:

For each working day after the outbreak of the epidemic, the work resumption status of the working day is determined according to the travel intensity of the working day, the normal travel intensity, and the basic travel intensity.
The method according to claim 6, wherein calculating the travel intensity corresponding to each working day according to the obtained positioning data of each working day, comprising:

According to the obtained positioning data of users in the area, determine the resident users in the area;

According to the positioning data of each resident user, determine the place of residence of the resident user;

For each working day, the travel intensity of the working day is determined according to the residence location of each resident user in the area and the positioning data of each resident user on the working day.
The method according to claim 7, characterized in that determining the travel intensity on the working day according to the residence location of each resident user in the area and the positioning data of each resident user on the working day, comprising:

For each resident user in the area, determine whether the resident user has travel behavior on the working day according to the positioning data of the resident user on the working day and the residence location of the resident user ;

The travel intensity of the working day is calculated according to the number of resident users who have travel behavior on the working day and the number of all resident users in the area.
The method according to claim 8, wherein the obtained positioning data comprises the user's mobile phone signaling data collected by the base station;

According to the positioning data of the resident user on the working day and the residence location of the resident user, determine whether the resident user has travel behavior on the working day, including:

If, according to the mobile phone signaling data of the resident user on the working day, it is determined that the resident user is connected to the base station outside the place of residence on the working day and is not connected to the base station outside the area, then determine The resident user has travel behavior on the working day.
The method according to claim 8, characterized in that, according to the positioning data of the resident user on the working day and the residence location of the resident user, it is determined whether the resident user has a resident user on the working day travel behavior, including:

If, according to the positioning data of the resident user on the working day, it is determined that the resident user has appeared at a place other than the preset distance from the place of residence for a preset period of time, it is determined that the resident user has a presence on the working day. travel behavior.
The method according to any one of claims 6 to 10, wherein determining the work resumption state on the working day according to the travel intensity on the working day, the normal travel intensity and the basic travel intensity, comprising: :

calculating a first difference between the travel intensity of the working day and the basic travel intensity, and a second difference between the normal travel intensity and the basic travel intensity;

According to the ratio between the first difference and the second difference, a work resumption index of the working day is determined, and the work resumption index is used to reflect the work resumption state.
A data processing device, comprising:

The acquisition module is used to acquire the positioning data of users in the area to be analyzed, the positioning data includes the positioning data of each working day in the first statistical period before the outbreak of the epidemic and the positioning data of each working day in the second statistical period after the outbreak of the epidemic ;

a calculation module, used to determine the travel intensity of the area before the outbreak and the travel intensity of the area after the outbreak according to the obtained positioning data;

The determining module is used to determine the work resumption status of the area according to the travel intensity of the area before the outbreak and the travel intensity of the area after the outbreak.
The apparatus according to claim 12, wherein the determining module is further configured to:

Control the public equipment in the area according to the resumption status of the area;

And/or, sending the indication information corresponding to the work resumption status to the government service platform or the terminal device in the area.
The device according to claim 13, wherein, when the determining module controls the public equipment in the area according to the resumption state of the area, it is specifically used for:

According to the work resumption status of the area, control the shift increase or decrease of the public transportation equipment in the area; and/or, according to the work resumption status of the area, instruct some charging piles in the area to be closed.
The device according to any one of claims 12 to 14, wherein the determining module determines the travel intensity of the area according to the travel intensity of the area before the outbreak of the epidemic and the travel intensity of the area after the outbreak of the epidemic In the state of resumption of work, it is specifically used for:

The travel intensity of each working day after the outbreak of the epidemic is compared with the travel intensity of the working day in the same period of the previous year to determine the work resumption status of the working day.
The device according to any one of claims 12 to 14, wherein the computing module is specifically configured to:

Calculate the travel intensity corresponding to each working day according to the obtained positioning data of each working day;

Calculate the normal travel intensity of the area according to the travel intensity of the working days before the outbreak;

Correspondingly, when determining the work resumption status of the area according to the travel intensity of the area before the outbreak and the travel intensity of the area after the outbreak, the determining module is specifically used to:

According to the travel intensity on each working day after the outbreak of the epidemic and the normal travel intensity, determine the work resumption status of the area on each working day after the outbreak.
The device according to claim 16, wherein when calculating the travel intensity corresponding to each work day according to the obtained positioning data of each work day, the calculation module is specifically used for:

Determine the resident users in the area according to the obtained positioning data of the users in the area;

According to the positioning data of each resident user, determine the place of residence of the resident user;

For each working day, the travel intensity of the working day is determined according to the residence location of each resident user in the area and the positioning data of each resident user on the working day.
A data processing device, characterized in that the data processing device comprises: a memory, a processor, and a data processing program stored on the memory and executable on the processor, the data processing program being The processor implements the steps of the data processing method according to any one of claims 1 to 11 when executed.
A computer-readable storage medium, characterized in that a data processing program is stored on the computer-readable storage medium, and when the data processing program is executed by a processor, the data processing program according to any one of claims 1 to 11 is implemented. The steps of a data processing method.
A computer program, characterized in that it comprises program code, when a computer runs the computer program, the program code executes the method according to any one of claims 1 to 11.