Information processing method, device, equipment and system

Abstract

The present disclosure provides an information processing method, device, equipment and system. When applied to a server, the method includes: obtaining data of multiple dimensions in a target scene, wherein the data of multiple dimensions at least includes text data and video data; processing the data of multiple dimensions to obtain prediction information of the usage of at least one resource in the target scene within a target period; and sending the prediction information to a terminal device.

Description

Technical Field

[0001] The present disclosure relates to the field of computer vision technology, and in particular to an information processing method, device, equipment and system. Background Art

[0002] With the continuous development of cities, the shortage of resources has led to the problem of low efficiency in urban residents' travel and work. For example, in many places in cities, there is a problem of excessive passenger flow and over-concentration, which causes urban residents to spend a lot of time queuing and waiting, affecting their quality of life.

[0003] Therefore, there is an urgent need for an information processing solution to analyze and predict resource occupancy when resources are limited. Summary of the invention

[0004] The present disclosure provides an information processing solution.

[0005] According to one aspect of the present disclosure, an information processing method is proposed, which is applied to a server, and the method includes: obtaining data of multiple dimensions in a target scenario, wherein the data of multiple dimensions include at least text data and video data; processing the data of multiple dimensions to obtain prediction information on the usage of at least one resource in the target scenario within a target time period; and sending the prediction information to a terminal device.

[0006] In combination with any embodiment provided in the present disclosure, the obtaining of data of multiple dimensions in the target scene includes: obtaining video data collected by at least one collection point in the target scene, the video data containing image information of at least one resource corresponding to the collection point; and obtaining text data containing at least one resource information in the target scene.

[0007] In combination with any embodiment provided in the present disclosure, the processing of the data of the multiple dimensions to obtain prediction information on the usage of at least one resource in the target scenario within the target time period includes: inputting the video data into a target recognition model to obtain first usage information of the resource; and obtaining prediction information on the usage of the resource within the target time period based on the first usage information and the resource information in the text data.

[0008] In combination with any embodiment provided by the present disclosure, the method of obtaining predictive information on the usage of the resource within a target time period based on the first usage information and the resource information in the text data includes: obtaining second usage information of the resource based on the resource information in the text data, wherein the first usage information matches the second usage information in time; and inputting the first usage information and the second usage information into a first neural network to obtain predictive information on the usage of the resource within the target time period.

[0009] In combination with any embodiment provided by the present disclosure, the method of obtaining predictive information on the usage of the resource within a target time period based on the first usage information and the resource information in the text data includes: obtaining reference operation information of the resource within the target time period based on the resource information in the text data; inputting the first usage information and the reference operation information into a second neural network to obtain predictive information on the usage of the resource within the target time period.

[0010] In combination with any embodiment provided in the present disclosure, the terminal device includes a device for sending a subscription request, and the method further includes: in response to receiving a subscription request sent by the terminal device, generating recommendation information on the use of the resource for the target user based on location information of the terminal device, at least one item of information of a target user using the terminal device, and predicted information on the use of the resource during the target time period; and sending the predicted information and the recommendation information to the terminal device.

[0011] In combination with any embodiment provided in the present disclosure, the method also includes: generating recommendation information on the use of the resource based on prediction information on the use of the resource within the target time period; and sending at least one of the prediction information and the recommendation information to public equipment within a set range of the target scene.

[0012] In combination with any embodiment provided by the present disclosure, in response to the target scene including a medical place, the prediction information includes the waiting time, and the suggestion information includes the medical recommendation information; and / or, in response to the target scene including a public transportation place, the prediction information includes the waiting time for each entrance of at least some of the entrances, and the suggestion information includes the recommended entrance information; and / or, in response to the target scene including an entry and exit checkpoint, the prediction information includes the traffic status information of at least some of the passage places, and the suggestion information includes the recommended passage places; and / or, in response to the target scene including a first scenic spot, the prediction information includes the waiting time for each place in at least some of the places in the first scenic spot; the suggestion information includes at least one of the recommended items in the first scenic spot and the second scenic spot information.

[0013] According to one aspect of the present disclosure, an information processing method is proposed, which is applied to a terminal device, and the method includes: receiving prediction information sent by a server, the prediction information being obtained by the method described in any embodiment of the present disclosure; and displaying at least the prediction information through a display interface of the terminal device.

[0014] In combination with any embodiment provided by the present disclosure, before receiving the prediction information sent by the server, the method also includes: sending a subscription request to the server; receiving the prediction information sent by the server includes: receiving the prediction information, or the prediction information and suggestion information, sent by the server to the terminal device in response to the subscription request.

[0015] In combination with any implementation manner provided in the present disclosure, displaying at least the prediction information through the display interface of the terminal device includes: displaying the prediction information through the display interface in a first push manner, and displaying the suggestion information in a second push manner.

[0016] According to one aspect of the present disclosure, an information processing device is proposed, which is applied to a server, and includes: an acquisition unit, used to obtain data of multiple dimensions in a target scenario, and the data of multiple dimensions include at least text data and video data; a prediction unit, used to process the data of multiple dimensions to obtain prediction information on the usage of at least one resource in the target scenario within a target time period; and a sending unit, used to send the prediction information to a terminal device.

[0017] In combination with any embodiment provided in the present disclosure, the acquisition unit is specifically used to: acquire video data collected by at least one acquisition point in the target scene, the video data including image information of at least one resource corresponding to the acquisition point; and acquire text data including at least one resource information in the target scene.

[0018] In combination with any embodiment provided in the present disclosure, the prediction unit is specifically used to: input the video data into a target recognition model to obtain first usage information of the resource; and obtain prediction information on the usage of the resource within the target time period based on the first usage information and the resource information in the text data.

[0019] In combination with any embodiment provided in the present disclosure, when the prediction unit is used to obtain prediction information on the usage of the resource within a target time period based on the first usage information and the resource information in the text data, it is specifically used to: obtain second usage information of the resource based on the resource information in the text data, wherein the first usage information matches the second usage information in time; and input the first usage information and the second usage information into a first neural network to obtain prediction information on the usage of the resource within the target time period.

[0020] In combination with any implementation manner provided in the present disclosure, when the prediction unit is used to obtain prediction information of the usage of the resource in the target time period according to the first usage information and the resource information in the text data, it is specifically used to:

[0021] In combination with any implementation manner provided in the present disclosure, reference operation information of the resource within the target time period is obtained based on the resource information in the text data; the first usage information and the reference operation information are input into a second neural network to obtain prediction information on the usage of the resource within the target time period.

[0022] In combination with any embodiment provided in the present disclosure, the terminal device includes a device for sending a subscription request, and the apparatus also includes a first sending unit for generating, in response to receiving a subscription request sent by the terminal device, recommendation information on the use of the resource for the target user based on location information of the terminal device, at least one item of information of a target user using the terminal device, and prediction information on the use of the resource during the target time period; and sending the prediction information and the recommendation information to the terminal device.

[0023] In combination with any embodiment provided in the present disclosure, the device also includes a second sending unit, which is used to generate recommendation information on the use of the resource based on the prediction information of the use of the resource during the target time period; and send at least one of the prediction information and the recommendation information to public equipment within a set range of the target scene.

[0024] In combination with any embodiment provided by the present disclosure, in response to the target scene including a medical place, the prediction information includes the waiting time, and the suggestion information includes the medical recommendation information; and / or, in response to the target scene including a public transportation place, the prediction information includes the waiting time for each entrance of at least some of the entrances, and the suggestion information includes the recommended entrance information; and / or, in response to the target scene including an entry and exit checkpoint, the prediction information includes the traffic status information of at least some of the passage places, and the suggestion information includes the recommended passage places; and / or, in response to the target scene including a first scenic spot, the prediction information includes the waiting time for each place in at least some of the places in the first scenic spot; the suggestion information includes at least one of the recommended items in the first scenic spot and the second scenic spot information.

[0025] According to one aspect of the present disclosure, an information processing device is proposed, which is applied to a terminal device, and the device includes: a receiving unit, used to receive prediction information sent by a server, and the prediction information is obtained by the information processing method described in any embodiment of the present disclosure; and a display unit, used to display at least the prediction information through a display interface of the terminal device.

[0026] In combination with any embodiment provided in the present disclosure, the device also includes a request sending unit for sending a subscription request to the server; the receiving unit is specifically used to: receive the prediction information, or the prediction information and suggestion information, sent by the server to the terminal device in response to the subscription request.

[0027] In combination with any implementation manner provided in the present disclosure, the display unit is specifically configured to: display the prediction information in a first push manner through the display interface, and display the suggestion information in a second push manner.

[0028] According to one aspect of the present disclosure, an information processing system is proposed, the system comprising: a server, used to obtain data of multiple dimensions in a target scenario, the data of multiple dimensions including at least text data and video data; processing the data of multiple dimensions to obtain prediction information on the usage of at least one resource in the target scenario within a target time period; and sending the prediction information to a terminal device; a terminal device, used to receive the prediction information and at least display the prediction information on a display interface.

[0029] According to one aspect of the present disclosure, an information processing device is proposed, the device comprising a memory and a processor, the memory being used to store computer instructions executable on the processor, the processor being used to implement the information processing method described in any embodiment of the present disclosure when executing the computer instructions.

[0030] According to one aspect of the present disclosure, a computer-readable storage medium is provided, on which a computer program is stored, and when the program is executed by a processor, the information processing method described in any embodiment of the present disclosure is implemented.

[0031] The embodiment of the present disclosure obtains data of multiple dimensions including at least text data and video data about the target scene, obtains prediction information of the usage of at least one resource in the target scene within the target time period through processing, and sends the prediction information to the terminal device. In this way, the resource occupancy can be analyzed and predicted, thereby obtaining prediction information. In addition, for users with identities such as visitors and tourists, the technical solution provided by the present disclosure can facilitate users to understand the resource occupancy.

[0032] It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the disclosure. BRIEF DESCRIPTION OF THE DRAWINGS

[0033] The drawings herein are incorporated into the specification and constitute a part of the specification. These drawings illustrate embodiments consistent with the present disclosure and are used to illustrate the technical solutions of the present disclosure together with the specification.

[0034] Figure 1 is a flow chart of an information processing method proposed by at least one embodiment of the present disclosure;

[0035] Figure 2 is a flowchart of another information processing method proposed by at least one embodiment of the present disclosure;

[0036] Figure 3 is a display example of a terminal device in the information processing method proposed in at least one embodiment of the present disclosure;

[0037] Figure 4 is a structural schematic diagram of an information processing device proposed in at least one embodiment of the present disclosure;

[0038] Figure 5 is a structural schematic diagram of another information processing device proposed in at least one embodiment of the present disclosure;

[0039] Figure 6 It is a structural diagram of an information processing device proposed in at least one embodiment of the present disclosure. DETAILED DESCRIPTION

[0040] Exemplary embodiments will be described in detail herein, examples of which are shown in the accompanying drawings. When the following description refers to the drawings, unless otherwise indicated, the same numbers in different drawings represent the same or similar elements. The implementations described in the following exemplary embodiments do not represent all implementations consistent with the present application. Instead, they are merely examples of devices and methods consistent with some aspects of the present application as detailed in the appended claims.

[0041] The terms used in this application are only for the purpose of describing specific embodiments, and are not intended to limit the application. The singular forms of "a", "said" and "the" used in this application and the appended claims are also intended to include plural forms, unless the context clearly indicates other meanings. It should also be understood that the term "and / or" used in this article refers to and includes any or all possible combinations of one or more associated listed items. In addition, the term "at least one" herein represents any combination of at least two of any one or more of a variety of.

[0042] It should be understood that although the terms first, second, third, etc. may be used in the present application to describe various information, these information should not be limited to these terms. These terms are only used to distinguish the same type of information from each other. For example, without departing from the scope of the present application, the first information may also be referred to as the second information, and similarly, the second information may also be referred to as the first information. Depending on the context, the word "if" as used herein may be interpreted as "at the time of" or "when" or "in response to determining".

[0043] In order to enable those skilled in the art to better understand the technical solutions in the embodiments of the present disclosure and to make the above-mentioned purposes, features and advantages of the embodiments of the present disclosure more obvious and understandable, the technical solutions in the embodiments of the present disclosure are further described in detail below in conjunction with the accompanying drawings.

[0044] Figure 1 is a flow chart of an information processing method proposed in at least one embodiment of the present disclosure, wherein the method is applied to a server, and the server may include but is not limited to a cloud, a terminal device, etc. Figure 1 As shown, the method includes steps 101 to 103.

[0045] In step 101, data of multiple dimensions in a target scene is obtained, and the data of multiple dimensions includes at least text data and video data.

[0046] In the disclosed embodiment, the target scene may include one or more of a medical place, a public transportation place, an entry and exit checkpoint, a scenic spot, a government service place, etc.

[0047] For different target scenes, data of corresponding dimensions and types matching the target scenes can be obtained. Among them, video data refers to the video stream collected by acquisition devices such as cameras deployed in the corresponding area of ​​the target scene; text data refers to the text content associated with the target scene.

[0048] The video data may include video data collected from at least one collection point in the target scene, and the video data includes image information of at least one resource corresponding to the collection point. The video data is, for example, historical monitoring data collected by a monitoring camera set at a location corresponding to the resource within any or a specified time period; the text data may include at least one resource information in the target scene, and the resource information includes at least one of the following: information indicating the use of the resource, reference operation information in the target scene, sensor information other than visual information acquired by various sensors, and the like.

[0049] In the embodiments of the present disclosure, the data of multiple dimensions may also include audio information, data streams generated by electronic maps, etc. The present disclosure does not limit the data types contained in addition to the text data and video data. The purpose is to obtain rich data content through more channels and / or to enrich the amount of information contained in the data by obtaining data sources from more angles.

[0050] In step 102, the data of the multiple dimensions are processed to obtain prediction information of usage of at least one resource in the target scenario within a target time period.

[0051] Data of multiple dimensions can be descriptions of the same resource in different dimensions. For example, when the target scene is a public transportation venue, which usually has multiple entrances, for one of the entrances in the public transportation venue, on the one hand, the entry and exit records of the entrance can be obtained, such as the card swiping records of each user, etc., and on the other hand, the monitoring data of the entrance can be obtained. By combining data of multiple dimensions, it is possible to more accurately describe the resource usage and obtain more accurate resource usage information.

[0052] Those skilled in the art should understand that the resource usage information referred to in the present disclosure refers to information on the usage of the resource in a historical period, or in a period from any or a specified historical moment to the current moment.

[0053] According to the resource usage information, or further combined with the resource information contained in the text data, prediction information of the usage of the resource within the target time period can be obtained.

[0054] The target time period may be a time period of a set duration starting from the current time, or a time period of a set duration starting from a set time after the current time. For example, the target time period may be a time period within 12 hours starting from the current time, or an 8-hour time period starting at 8:00 a.m. the next day.

[0055] In step 103, the prediction information is sent to the terminal device.

[0056] The terminal device is a device other than the server. The prediction information can be sent in at least one of a plurality of ways such as text messages, emails, WeChat, and mini-program push interfaces. By sending the prediction information to the terminal device, the target user of the terminal device can understand the possible use of the resource in the target time period in the future, so as to reasonably regulate the use of the resource. By enabling the group to generally understand the possible use of the resource in the future, the optimal allocation of urban resources can be achieved.

[0057] It should be noted that the resources referred to in this disclosure, namely the above-mentioned urban resources, refer to the public human and material resources that provide residents with government services, medical services, travel, tourism and other services. For example, for medical services, the resources may include but are not limited to outpatient service resources, parking service resources in medical facilities, etc.

[0058] In the embodiment of the present disclosure, data of multiple dimensions including at least text data and video data about the target scene are obtained, and prediction information of the usage of at least one resource in the target scene within the target time period is obtained by processing, and the prediction information is sent to the terminal device. In this way, the resource occupancy can be analyzed and predicted, thereby obtaining prediction information. In addition, for users with identities such as visitors and tourists, the technical solution provided by the present disclosure can facilitate users to understand the resource occupancy.

[0059] In some embodiments, for the video data, information related to usage of corresponding resources contained therein may be obtained by performing visual analysis.

[0060] In one example, the video data can be input into a target recognition model, and target recognition processing can be performed on the video data to obtain usage information of the resource. In order to distinguish it from usage information obtained in other ways, the usage information obtained based on the video data is referred to as the first usage information. Taking the target scene as a public transportation place as an example, the video data includes data of surveillance images of each entrance in the public transportation place. By performing target recognition on the surveillance image, the person contained in the image is identified, so that the flow of people passing through the entrance within a set time can be determined. Taking the target place as a medical place as an example, the video data can include surveillance video data of the emergency waiting area, surveillance video data at the entrance of the parking lot of the medical place, and so on.

[0061] In some embodiments, the text data may include resource information in the form of structured data. The structured data is two-dimensional data represented and stored in a relational database. By obtaining resource information in the form of structured data, it is easier to obtain usage information of the resource from the text data.

[0062] Taking the target place as a medical place as an example, the acquired text data may include structured medical data, such as shown below: [patient (desensitization), disease type, expert number, project, time], [XXX, eczema, yes, registration, 20180801-11:20:15], [XXX, eczema, yes, laboratory test, 20180801-11:25:15], [XXX, eczema, yes, examination, 20180801-11:30:15].

[0063] In some embodiments, based on the first usage information corresponding to the same resource in the target scenario and the resource information in the text data, prediction information on the usage of the resource in the target time period can be obtained.

[0064] Since the first usage information and the resource information in the text data corresponding to the same resource are descriptions of the usage of the resource from different dimensions, the first usage information and the resource information are combined to obtain the usage of the resource more comprehensively and accurately. Therefore, the combination of the first usage information and the resource information can provide a more accurate picture of the usage of the resource in the target period.

[0065] According to the resource information in the text data, the usage information of the resource can be obtained. In order to distinguish it from the usage information obtained according to the video data, the usage information obtained according to the text data is referred to as the second usage information.

[0066] In the embodiment of the present disclosure, the first usage information obtained based on the video data and the second usage information obtained based on the text data are matched in time, that is, the first usage information and the second usage information contain usage information of the same historical time period. For example, the first usage information and the second usage information both contain data within a week before the current moment.

[0067] By inputting the first usage information and the second usage information into the first neural network, prediction information of the usage of the resource in the target time period can be obtained. The first neural network may include a time series prediction network, which can predict the usage of the resource in the future time period by learning the law of resource usage in the historical time period, thereby generating prediction information. Those skilled in the art should understand that the first neural network may also include other types of neural networks, and the present disclosure does not limit this.

[0068] Taking the target place as a scenic spot as an example, based on the video surveillance data at the entrance of the scenic spot and the video surveillance data at the entrance of the parking lot, the flow of people waiting to enter the scenic spot in each historical period can be obtained, that is, the first usage information can be obtained; based on the text data related to the scenic spot, the scenic spot entrance records, parking lot sensor records and parking space usage statistics in each period can be obtained, that is, the second usage information can be obtained. Using the first usage information and the second usage information in the same historical period of the first god, the waiting time of the queue at the entrance of the scenic spot can be predicted.

[0069] In the disclosed embodiment, reference operation information of the resource can also be obtained based on the resource information in the text data. The specific data contained in the reference operation information is determined according to the specific target scenario. For example, for public transportation places, the reference operation information may include a train timetable; for scenic spots, the reference operation information may include the opening hours of the scenic spot, or the planned operation time of each project in the scenic spot.

[0070] By inputting the first usage information and reference operation information of the resource into the second neural network, forecast information on the usage of the resource within the target time period can be obtained.

[0071] The reference operation time of the resource can provide a reference for the use of the resource in the target time period. Taking the reference operation information as a train timetable as an example, it can be known from the train timetable in which time periods in the future more passengers will arrive at the public transportation place, thereby assisting in the prediction of the flow of people and queues at each entrance and exit.

[0072] In some embodiments, based on the prediction information of the usage of at least one resource in the target scenario during the target time period, recommendation information for the usage of the at least one resource can be generated to assist the user in making decisions and achieve reasonable scheduling of resources.

[0073] For example, if it is predicted that the number of users of the resource will reach a peak in a certain period of time in the future, and using the resource during this period will consume a lot of queuing time, other resources with similar functions to the resource but with fewer users can be provided during this period, which can shorten the waiting time.

[0074] In the case where the use of the resource is irrelevant to the user's own situation, suggestions for the use of the resource can be sent proactively and non-targetedly. For example, the suggestion information and / or the prediction information is sent to public equipment within the set range of the target scene. In this way, users within the set range of the target scene can view the estimated usage of each resource under the target scene in each future time period through the public equipment, and can also view the usage suggestions for each resource at the same time, so that users can use the resources in the target scene more reasonably, save waiting time, and improve efficiency.

[0075] In the disclosed embodiment, the suggestion information may also be generated in combination with the target user's own information.

[0076] The target user can send a subscription request for the prediction information and suggestion information of each resource in the target scene through a terminal device. The terminal device includes a device for sending a subscription request, and the terminal device can be an electronic device of a personal user such as a mobile phone or a tablet computer, or a public device within the set range of the target scene. The target user can send a subscription request through the device, for example, by at least one of a plurality of methods such as text message, email, WeChat, mini-program request interface, etc. The subscription request can be used to request prediction information of the usage of the target scene, or can be used to request suggestion information of the usage of the target scene, or can be used to request prediction information and suggestion information of the usage of the target scene at the same time.

[0077] In response to receiving a subscription request sent by the target user through the terminal device, recommendation information on the use of the resource for the target user can be generated based on the location information of the terminal device, and / or information of the target user using the terminal device, and predicted information on the use of the resource during the target time period.

[0078] By combining the location of the target user and the target user's own information, more targeted resource usage suggestion information can be generated.

[0079] Taking the target scenario as a medical place as an example, based on the location of the target user, the time when the target user arrives at the medical place can be estimated. Combined with the predicted information on the use of the medical place in the corresponding time period, the target user's consultation time can be recommended more accurately. Based on the target user's own information, such as the type of clinic the target user is going to visit, whether the conditions under the medical package are met, and other dimensions, while giving consultation time recommendations, other medical places that are more suitable for consultation can also be recommended to the user, so that the target user can save consultation time and obtain better medical results, while also achieving optimal allocation of medical resources within the city.

[0080] In some embodiments, the target user can also log in to a public device within the set range of the target scene to enable the public device to obtain its own information, and send a subscription request through the public device to obtain prediction information and / or suggestion information on the usage of each resource in the target scene.

[0081] In one example, in response to the target scenario including a medical facility, the prediction information includes a waiting time, and the suggestion information includes medical recommendation information.

[0082] In one example, in response to the target scene including a public transportation place, the prediction information includes the waiting time of each entrance of at least some entrances, and the suggestion information includes recommended entrance information.

[0083] In one example, in response to the target scenario including an entry / exit checkpoint, the prediction information includes at least part of the traffic status information of each traffic place, and the suggestion information includes recommended traffic places.

[0084] In one example, in response to the target scene including a first scenic spot, the prediction information includes the waiting time for each of at least some of the places in the first scenic spot; the suggestion information includes at least one of the recommended items in the first scenic spot and the second scenic spot information.

[0085] Figure 2 is a flowchart of another information processing method proposed in at least one embodiment of the present disclosure, the method is applied to a terminal device, the terminal device may include but is not limited to a mobile phone, a tablet computer, etc., and the present disclosure does not limit the form of the terminal device. Figure 2 As shown, the method includes steps 201-202.

[0086] In step 201, prediction information sent by a server is received, wherein the prediction information may be prediction information sent by the information processing method described in any embodiment of the present disclosure.

[0087] In step 202, at least the prediction information is displayed through the display interface of the terminal device.

[0088] Figure 3 It is a display schematic diagram of a terminal device in an information processing method proposed in at least one embodiment of the present disclosure.

[0089] like Figure 3 As shown, the area 301 above the display interface of the terminal device shows a local area map containing the target scenic spot, and the area 302 below the local area map shows the specific type of prediction information, which is the queuing situation of the scenic spot in this example. Below is area 303, which shows the prediction of the queuing time of the scenic spot represented by a bar graph, which indicates the estimated queuing time at multiple moments within the target time period. The area 304 at the bottom of the display area shows the density measurement of the flow of people represented by a curve graph, which indicates the flow of people at various moments on the day of arriving at the scenic spot. Among them, the target time period corresponding to the prediction information can be set by selecting the estimated arrival time, or by manually entering a specific time. In this example, you can jump to the page for setting the target time period by clicking on the scenic area 302. Those skilled in the art should understand that the display page can also include other types of prediction information, or only include one of the prediction information, such as only including the prediction of the queuing time of the scenic spot, or only including the density measurement of the flow of people, and the display form of the prediction information can be set, for example, the prediction of the queuing time of the scenic spot can also be represented in the form of a curve. Figure 3 This is only an example, and the present disclosure does not limit the specific display form of the display interface. The display form refers to the content of the prediction information and / or suggestion information, the presentation method of each content, etc. For example, the arrangement of each part of the content, whether there is a corresponding animation effect during the display process, etc.

[0090] In some embodiments, the terminal device sends a subscription request to the server, wherein the subscription request includes a set target time period; and the terminal device receives the prediction information, or the prediction information and suggestion information, sent by the server to the terminal device in response to the subscription request.

[0091] In response to receiving the prediction information, the prediction information may be displayed in a corresponding page format according to the target scenario corresponding to the prediction information.

[0092] For example, in response to receiving the queue time prediction information and the crowd density measurement information of the scenic spot, Figure 3 The page format shown displays the above forecast information.

[0093] In response to receiving the prediction information and the suggestion information, the prediction information and the suggestion information can be displayed in the form of corresponding pages through the display interface of the terminal device according to the target scene corresponding to the prediction information and / or the suggestion information. For example, the prediction information can be displayed in a first push mode, and the suggestion information can be displayed in a second push mode. Among them, the push mode indicates the display mode of the corresponding information, and the first push mode and the second push mode can be the same, partially the same, or completely different.

[0094] In one example, the prediction information and the suggestion information may be displayed through the same display interface. For example, the prediction information and the suggestion information may be displayed separately in multiple windows included in the display interface; or the prediction information and the suggestion information may be displayed separately through the formation of a split screen.

[0095] In one example, the prediction information and the suggestion information may be displayed through different display interfaces. For example, the display interface may be swiped up and down or left and right to switch from a display interface displaying the prediction information to another display interface displaying the suggestion information, so that the above two types of information may be viewed through different display interfaces.

[0096] In one example, the prediction information and the suggested information displayed on the current display page may be switched according to the user's operation so as to facilitate the user's viewing.

[0097] In one example, the prediction information and the suggestion information may be pushed in a loop, and a transition may be made between the presentation of the two types of information through a set animation effect.

[0098] Figure 4 An information processing device provided for at least one embodiment of the present disclosure, the device is applied to a server, and the device includes: an acquisition unit 401, used to obtain data of multiple dimensions in a target scenario, the data of multiple dimensions at least including text data and video data; a prediction unit 402, used to process the data of multiple dimensions to obtain prediction information of usage of at least one resource in the target scenario within a target time period; a sending unit 403, used to send the prediction information to a terminal device.

[0099] In some embodiments, the acquisition unit is specifically used to: acquire video data acquired by at least one acquisition point in the target scene, the video data including image information of at least one resource corresponding to the acquisition point; acquire text data including at least one resource information in the target scene.

[0100] In some embodiments, the prediction unit is specifically used to: input the video data into a target recognition model to obtain first usage information of the resource; and obtain prediction information on the usage of the resource within the target time period based on the first usage information and the resource information in the text data.

[0101] In some embodiments, when the prediction unit is used to obtain prediction information on the usage of the resource within a target time period based on the first usage information and the resource information in the text data, it is specifically used to: obtain second usage information of the resource based on the resource information in the text data, wherein the first usage information matches the second usage information in time; and input the first usage information and the second usage information into a first neural network to obtain prediction information on the usage of the resource within the target time period.

[0102] In some embodiments, when the prediction unit is used to obtain prediction information of the usage of the resource in the target time period according to the first usage information and the resource information in the text data, it is specifically used to:

[0103] In some embodiments, based on the resource information in the text data, reference operation information of the resource within the target time period is obtained; the first usage information and the reference operation information are input into a second neural network to obtain prediction information on the usage of the resource within the target time period.

[0104] In some embodiments, the terminal device includes a device for sending a subscription request, and the apparatus also includes a first sending unit for generating, in response to receiving a subscription request sent by the terminal device, recommendation information on the use of the resource for the target user based on location information of the terminal device, at least one item of information of a target user using the terminal device, and prediction information on the use of the resource during the target time period; and sending the prediction information and the recommendation information to the terminal device.

[0105] In some embodiments, the device also includes a second sending unit, which is used to generate recommendation information on the use of the resource based on prediction information on the use of the resource during the target time period; and send at least one of the prediction information and the recommendation information to public equipment within a set range of the target scene.

[0106] In some embodiments, in response to the target scene including a medical facility, the prediction information includes the waiting time, and the suggestion information includes the medical recommendation information; and / or, in response to the target scene including a public transportation facility, the prediction information includes the waiting time for each of at least some of the entrances, and the suggestion information includes recommended entrance information; and / or, in response to the target scene including an entry and exit checkpoint, the prediction information includes the traffic status information of at least some of the passage places, and the suggestion information includes recommended passage places; and / or, in response to the target scene including a first scenic spot, the prediction information includes the waiting time for each of at least some of the places in the first scenic spot; the suggestion information includes at least one of the recommended items in the first scenic spot and the second scenic spot information.

[0107] Figure 5 An information processing device is provided for at least one embodiment of the present disclosure. An information processing device is proposed, which is applied to a terminal device, and the device includes: a receiving unit 501, used to receive prediction information sent by a server, and the prediction information is obtained by the information processing method described in any embodiment of the present disclosure; a display unit 502, used to display at least the prediction information through a display interface of the terminal device.

[0108] In some embodiments, the apparatus further includes a request sending unit for sending a subscription request to the server; the receiving unit is specifically used to receive the prediction information, or the prediction information and suggestion information, sent by the server to the terminal device in response to the subscription request.

[0109] In some embodiments, the display unit is specifically used to: display the prediction information through the display interface in a first push manner, and display the suggestion information in a second push manner.

[0110] Figure 6 An electronic device provided for at least one embodiment of the present disclosure includes a memory and a processor, wherein the memory is used to store computer instructions that can be executed on the processor, and the processor is used to implement the information processing method described in any embodiment of the present disclosure when executing the computer instructions.

[0111] At least one embodiment of the present disclosure further provides a computer-readable storage medium having a computer program stored thereon, and when the program is executed by a processor, the information processing method described in any embodiment of the present disclosure is implemented.

[0112] In some embodiments, the functions or modules included in the device provided by the embodiments of the present disclosure can be used to execute the method described in the above method embodiments. The specific implementation can refer to the description of the above method embodiments, and for the sake of brevity, it will not be repeated here.

[0113] The device embodiments described above are merely illustrative, wherein the modules described as separate components may or may not be physically separated, and the components displayed as modules may or may not be physical modules, that is, they may be located in one place, or they may be distributed on multiple network modules. Some or all of the modules may be selected according to actual needs to achieve the purpose of the scheme of this specification. Those of ordinary skill in the art may understand and implement it without creative work.

[0114] The embodiments of the device of this specification can be applied to computer equipment, such as servers or terminal devices. The device embodiments can be implemented by software, hardware, or a combination of software and hardware. Taking software implementation as an example, as a device in a logical sense, it is formed by the processor of the file processing in which it is located reading the corresponding computer program instructions in the non-volatile memory into the memory for execution. From the hardware level, it is a hardware structure diagram of the computer device where the device of this specification is located. In addition to the processor, memory, network interface, and non-volatile memory, the server or electronic device where the device in the embodiment is located may also include other hardware, usually according to the actual function of the computer device, which will not be described in detail.

[0115] The present disclosure may take the form of a computer program product implemented on one or more storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing program code. Computer-usable storage media include permanent and non-permanent, removable and non-removable media, and information storage can be achieved by any method or technology. Information can be computer-readable commands, data structures, modules of programs, or other data. Examples of computer storage media include but are not limited to: phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technology, read-only compact disk read-only memory (CD-ROM), digital versatile disk (DVD) or other optical storage, magnetic cassettes, magnetic tape magnetic disk storage or other magnetic storage devices or any other non-transmission media that can be used to store information that can be accessed by a computing device.

[0116] Those skilled in the art will readily appreciate other embodiments of the present disclosure after considering the specification and practicing the specification disclosed herein. The present disclosure is intended to cover any variations, uses or adaptations of the present disclosure that follow the general principles of the present disclosure and include common knowledge or customary techniques in the art that are not disclosed in the present disclosure. The description and examples are to be considered exemplary only, and the true scope and spirit of the present disclosure are indicated by the following claims.

[0117] It should be understood that the present disclosure is not limited to the exact structures that have been described above and shown in the drawings, and that various modifications and changes may be made without departing from the scope thereof. The scope of the present disclosure is limited only by the appended claims.

[0118] The above description is only a preferred embodiment of the present disclosure and is not intended to limit the present disclosure. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present disclosure shall be included in the scope of protection of the present disclosure.

[0119] The above description of various embodiments tends to emphasize the differences between the various embodiments. The same or similar aspects can be referenced to each other, and for the sake of brevity, they will not be repeated herein.

Claims

1. An information processing method, characterized in that: The method is applied to a server, and the method comprises: Obtaining data of multiple dimensions in a target scene, wherein the data of multiple dimensions includes at least text data and video data. When the target scene is a public transportation place, the text data is an entry and exit record of one of the entrances of the public transportation place; Inputting the video data into a target recognition model to obtain first usage information of a resource; Obtaining prediction information of the usage of the resource in the target time period according to the first usage information and the resource information in the text data, including obtaining second usage information of the resource according to the resource information in the text data, inputting the first usage information and the second usage information into a first neural network, and obtaining prediction information of the usage of the resource in the target time period, wherein the first usage information matches the second usage information in time; The prediction information is sent to the terminal device.

2. The method according to claim 1, characterized in that: The obtaining of data of multiple dimensions in the target scene includes: Acquire video data collected by at least one collection point in a target scene, wherein the video data includes image information of at least one resource corresponding to the collection point; Acquire text data containing at least one type of resource information in the target scenario.

3. The method according to claim 1, characterized in that The obtaining, according to the first usage information and the resource information in the text data, prediction information of the usage of the resource in the target time period includes: According to the resource information in the text data, obtaining reference operation information of the resource within the target time period; The first usage information and the reference operation information are input into a second neural network to obtain prediction information on the usage of the resource within a target time period.

4. The method according to claim 1, characterized in that: The terminal device includes a device for sending a subscription request, and the method further includes: In response to receiving a subscription request sent by the terminal device, generating suggestion information on the use of the resource for the target user according to at least one of the location information of the terminal device, the information of the target user using the terminal device, and the prediction information on the use of the resource in the target time period; The prediction information and the suggestion information are sent to the terminal device.

5. The method according to claim 1, characterized in that The method further comprises: generating suggestion information for use of the resource based on the prediction information of the use of the resource in the target time period; At least one of the prediction information and the suggestion information is sent to public devices within a set range of the target scene.

6. The method according to claim 5, characterized in that In response to the target scenario including a medical site, the prediction information includes a waiting time, and the suggestion information includes a medical recommendation information; and / or, in response to the target scene including a public transportation place, the prediction information includes a waiting time for each entrance of at least some of the entrances, and the suggestion information includes recommended entrance information; and / or, in response to the target scene including an entry / exit checkpoint, the prediction information includes at least part of the traffic status information of each traffic place, and the suggestion information includes a recommended traffic place; And / or, in response to the target scene including a first scenic spot, the prediction information includes the waiting time for each place in at least some places in the first scenic spot; the suggestion information includes at least one of the recommended items in the first scenic spot and the second scenic spot information.

7. An information processing method, characterized in that: The method is applied to a terminal device, and the method comprises: Receiving prediction information sent by a server, wherein the prediction information is obtained by the method according to any one of claims 1 to 6; At least the prediction information is displayed through the display interface of the terminal device.

8. The method according to claim 7, characterized in that Before receiving the prediction information sent by the server, the method further includes: Sending a subscription request to the server; The receiving server sends prediction information, including: The prediction information, or the prediction information and the suggestion information, is received by the server in response to the subscription request to the terminal device.

9. The method according to claim 8, characterized in that The displaying at least the prediction information through the display interface of the terminal device includes: The prediction information is displayed through the display interface in a first push manner, and the suggestion information is displayed in a second push manner.

10. An information processing device, characterized in that: The device is applied to a server, and comprises: An acquisition unit, configured to acquire data of multiple dimensions in a target scene, wherein the data of multiple dimensions at least includes text data and video data. When the target scene is a public transportation place, the text data is an entry and exit record of one of the entrances of the public transportation place; A prediction unit, configured to input the video data into a target recognition model to obtain first usage information of a resource; obtain prediction information of usage of the resource in the target time period according to the first usage information and the resource information in the text data, including obtaining second usage information of the resource according to the resource information in the text data, inputting the first usage information and the second usage information into a first neural network, and obtaining prediction information of usage of the resource in the target time period, wherein the first usage information matches the second usage information in time; A sending unit is used to send the prediction information to a terminal device.

11. An information processing device, characterized in that: The device is applied to a terminal device, and the device includes: A receiving unit, configured to receive prediction information sent by a server, wherein the prediction information is obtained by the method according to any one of claims 1 to 6; A display unit is used to display at least the prediction information through the display interface of the terminal device.

12. An information processing system, characterized in that: The system comprises: The server is used to obtain data of multiple dimensions in a target scene, wherein the data of multiple dimensions includes at least text data and video data. When the target scene is a public transportation place, the text data is an entry and exit record of one of the entrances of the public transportation place; input the video data into a target recognition model to obtain first usage information of a resource; obtain prediction information of usage of the resource in the target time period according to the first usage information and the resource information in the text data, including obtaining second usage information of the resource according to the resource information in the text data, inputting the first usage information and the second usage information into a first neural network to obtain prediction information of usage of the resource in the target time period, wherein the first usage information matches the second usage information in time; and sending the prediction information to a terminal device; The terminal device is used to receive the prediction information and at least display the prediction information on a display interface.

13. An information processing device, characterized in that: The device comprises a memory and a processor, wherein the memory is used to store computer instructions executable on the processor, and the processor is used to implement the method according to any one of claims 1 to 9 when executing the computer instructions.

14. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the method according to any one of claims 1 to 9 is implemented.

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