CN111831853A - Information processing method, device, equipment and system - Google Patents
Information processing method, device, equipment and system Download PDFInfo
- Publication number
- CN111831853A CN111831853A CN202010688723.0A CN202010688723A CN111831853A CN 111831853 A CN111831853 A CN 111831853A CN 202010688723 A CN202010688723 A CN 202010688723A CN 111831853 A CN111831853 A CN 111831853A
- Authority
- CN
- China
- Prior art keywords
- information
- resource
- prediction information
- target
- prediction
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
- 230000010365 information processing Effects 0.000 title claims abstract description 37
- 238000003672 processing method Methods 0.000 title claims abstract description 21
- 238000000034 method Methods 0.000 claims abstract description 40
- 238000012545 processing Methods 0.000 claims abstract description 15
- 230000004044 response Effects 0.000 claims description 34
- 238000013528 artificial neural network Methods 0.000 claims description 13
- 238000004590 computer program Methods 0.000 claims description 5
- 238000012544 monitoring process Methods 0.000 description 9
- 238000010586 diagram Methods 0.000 description 5
- 201000004624 Dermatitis Diseases 0.000 description 3
- 208000010668 atopic eczema Diseases 0.000 description 3
- 238000005516 engineering process Methods 0.000 description 3
- 230000006870 function Effects 0.000 description 3
- 230000000694 effects Effects 0.000 description 2
- 230000004048 modification Effects 0.000 description 2
- 238000012986 modification Methods 0.000 description 2
- 230000003287 optical effect Effects 0.000 description 2
- 230000008569 process Effects 0.000 description 2
- 230000000007 visual effect Effects 0.000 description 2
- 230000006978 adaptation Effects 0.000 description 1
- 238000003556 assay Methods 0.000 description 1
- 230000005540 biological transmission Effects 0.000 description 1
- 230000015572 biosynthetic process Effects 0.000 description 1
- 230000008859 change Effects 0.000 description 1
- 238000001739 density measurement Methods 0.000 description 1
- 238000000586 desensitisation Methods 0.000 description 1
- 238000011161 development Methods 0.000 description 1
- 201000010099 disease Diseases 0.000 description 1
- 208000037265 diseases, disorders, signs and symptoms Diseases 0.000 description 1
- 230000006872 improvement Effects 0.000 description 1
- 230000007721 medicinal effect Effects 0.000 description 1
- 230000001105 regulatory effect Effects 0.000 description 1
- 230000003068 static effect Effects 0.000 description 1
- 230000008685 targeting Effects 0.000 description 1
- 230000007704 transition Effects 0.000 description 1
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/70—Information retrieval; Database structures therefor; File system structures therefor of video data
- G06F16/78—Retrieval characterised by using metadata, e.g. metadata not derived from the content or metadata generated manually
- G06F16/783—Retrieval characterised by using metadata, e.g. metadata not derived from the content or metadata generated manually using metadata automatically derived from the content
- G06F16/7844—Retrieval characterised by using metadata, e.g. metadata not derived from the content or metadata generated manually using metadata automatically derived from the content using original textual content or text extracted from visual content or transcript of audio data
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/70—Information retrieval; Database structures therefor; File system structures therefor of video data
- G06F16/73—Querying
- G06F16/735—Filtering based on additional data, e.g. user or group profiles
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N3/00—Computing arrangements based on biological models
- G06N3/02—Neural networks
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/04—Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem"
Landscapes
- Engineering & Computer Science (AREA)
- Theoretical Computer Science (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- General Engineering & Computer Science (AREA)
- Data Mining & Analysis (AREA)
- Multimedia (AREA)
- Business, Economics & Management (AREA)
- Databases & Information Systems (AREA)
- Human Resources & Organizations (AREA)
- Library & Information Science (AREA)
- Computational Linguistics (AREA)
- Economics (AREA)
- Strategic Management (AREA)
- Operations Research (AREA)
- Biomedical Technology (AREA)
- Entrepreneurship & Innovation (AREA)
- Marketing (AREA)
- Development Economics (AREA)
- Quality & Reliability (AREA)
- Tourism & Hospitality (AREA)
- General Business, Economics & Management (AREA)
- Health & Medical Sciences (AREA)
- Life Sciences & Earth Sciences (AREA)
- Artificial Intelligence (AREA)
- Game Theory and Decision Science (AREA)
- Biophysics (AREA)
- Evolutionary Computation (AREA)
- General Health & Medical Sciences (AREA)
- Molecular Biology (AREA)
- Computing Systems (AREA)
- Mathematical Physics (AREA)
- Software Systems (AREA)
- Management, Administration, Business Operations System, And Electronic Commerce (AREA)
- Information Transfer Between Computers (AREA)
- Information Retrieval, Db Structures And Fs Structures Therefor (AREA)
Abstract
The disclosure provides an information processing method, device, equipment and system. In case of application to a server, the method comprises: obtaining data of multiple dimensions in a target scene, wherein the data of the multiple dimensions at least comprises text data and video data; processing the data of the multiple dimensions to obtain the prediction information of the use condition of at least one resource in the target time interval under the target scene; and sending the prediction information to the terminal equipment.
Description
Technical Field
The present disclosure relates to the field of computer vision technologies, and in particular, to an information processing method, apparatus, device, and system.
Background
With the continuous development of cities, the problems of low trip and working efficiency of urban residents are caused due to the shortage of resources. For example, in urban life, the problem of overlarge and over-centralized passenger flow is easily caused in various places, so that a great amount of time is spent on queuing and waiting by urban residents, and the quality of life is influenced.
Therefore, there is a need for an information processing scheme to analyze and predict the resource occupation situation under the condition of limited resources.
Disclosure of Invention
The present disclosure provides an information processing scheme.
According to an aspect of the present disclosure, an information processing method is provided, where the method is applied to a server, and the method includes: obtaining data of multiple dimensions in a target scene, wherein the data of the multiple dimensions at least comprises text data and video data; processing the data of the multiple dimensions to obtain the prediction information of the use condition of at least one resource in the target time interval under the target scene; and sending the prediction information to the terminal equipment.
In combination with any one of the embodiments provided by the present disclosure, the obtaining data of multiple dimensions in a target scene includes: acquiring video data acquired by at least one acquisition point in a target scene, wherein the video data comprises image information of at least one resource corresponding to the acquisition point; and acquiring text data containing at least one resource information in the target scene.
With reference to any embodiment provided by the present disclosure, the processing the data of the multiple dimensions to obtain the prediction information of the usage of at least one resource in the target time period in the target scene includes: inputting the video data to a target recognition model to obtain first usage information of the resource; and obtaining the prediction information of the use condition of the resource in the target time interval according to the first use information and the resource information in the text data.
In combination with any embodiment provided by the present disclosure, the obtaining, according to the first usage information and resource information in the text data, prediction information of a usage situation of the resource in a target time period includes: obtaining second use information of the resource according to resource information in the text data, wherein the first use information is matched with the second use information in time; and inputting the first use information and the second use information into a first neural network to obtain the prediction information of the use condition of the resource in a target time period.
In combination with any embodiment provided by the present disclosure, the obtaining, according to the first usage information and resource information in the text data, prediction information of a usage situation of the resource in a target time period includes: acquiring reference operation information of the resources in the target time period according to the resource information in the text data; and inputting the first use information and the reference operation information into a second neural network to obtain the prediction information of the use condition of the resource in a target time period.
In combination with any one of the embodiments provided by the present disclosure, the terminal device includes a device that sends a subscription request, and the method further includes: in response to receiving a subscription request sent by the terminal device, generating recommendation information for the use of the resource of a target user according to at least one of position information of the terminal device, information of the target user using the terminal device, and prediction information of the use condition of the resource in the target period; and sending the prediction information and the suggestion information to the terminal equipment.
In combination with any embodiment provided by the present disclosure, the method further comprises: generating recommendation information of the use of the resource based on the prediction information of the use condition of the resource in the target time period; and sending at least one of the prediction information and the suggestion information to public equipment within a set range of the target scene.
In combination with any one of the embodiments provided by the present disclosure, in response to the target scene including a medical place, the prediction information includes a waiting duration, and the recommendation information includes visit recommendation information; and/or, in response to the target scene comprising a public transportation location, the prediction information comprises a waiting duration for each of at least some of the entrances, and the recommendation information comprises recommended entrance information; and/or, in response to the target scene comprising an entry/exit gateway, the prediction information comprises traffic state information of at least part of each traffic place, and the advice information comprises recommended traffic places; and/or, in response to the target scene comprising a first scenic spot, the prediction information comprises a waiting duration for each of at least some of the venues within the first scenic spot; the recommendation information includes at least one of the first scenic spot recommended item and second scenic spot information.
According to an aspect of the present disclosure, an information processing method is provided, where the method is applied to a terminal device, and the method includes: receiving prediction information sent by a server, wherein the prediction information is obtained by the method of any one of the embodiments of the present disclosure; and displaying at least the prediction information through a display interface of the terminal equipment.
In combination with any embodiment provided by the present disclosure, before the receiving the prediction information sent by the server, the method further includes: sending a subscription request to the server; the receiving of the prediction information sent by the server includes: and receiving the prediction information or the prediction information and suggestion information sent by the server to the terminal equipment in response to the subscription request.
In combination with any one of the embodiments provided by the present disclosure, the displaying at least the prediction information through the display interface of the terminal device includes: and displaying the prediction information in a first pushing mode and displaying the suggestion information in a second pushing mode through the display interface.
According to an aspect of the present disclosure, an information processing apparatus applied to a server is provided, the apparatus including: the device comprises an acquisition unit, a processing unit and a display unit, wherein the acquisition unit is used for acquiring data of multiple dimensions in a target scene, and the data of the multiple dimensions at least comprise text data and video data; the prediction unit is used for processing the data of the multiple dimensions to obtain prediction information of the use condition of at least one resource in a target time interval under the target scene; and the sending unit is used for sending the prediction information to the terminal equipment.
In combination with any one of the embodiments provided by the present disclosure, the obtaining unit is specifically configured to: acquiring video data acquired by at least one acquisition point in a target scene, wherein the video data comprises image information of at least one resource corresponding to the acquisition point; and acquiring text data containing at least one resource information in the target scene.
In combination with any one of the embodiments provided by the present disclosure, the prediction unit is specifically configured to: inputting the video data to a target recognition model to obtain first usage information of the resource; and obtaining the prediction information of the use condition of the resource in the target time interval according to the first use information and the resource information in the text data.
In combination with any embodiment provided by the present disclosure, the prediction unit, when configured to obtain, according to the first usage information and resource information in the text data, prediction information of a usage situation of the resource in a target period, is specifically configured to: obtaining second use information of the resource according to resource information in the text data, wherein the first use information is matched with the second use information in time; and inputting the first use information and the second use information into a first neural network to obtain the prediction information of the use condition of the resource in a target time period.
In combination with any embodiment provided by the present disclosure, the prediction unit, when configured to obtain, according to the first usage information and resource information in the text data, prediction information of a usage situation of the resource in a target period, is specifically configured to:
in combination with any embodiment provided by the present disclosure, according to resource information in the text data, obtaining reference operation information of the resource in the target time period; and inputting the first use information and the reference operation information into a second neural network to obtain the prediction information of the use condition of the resource in a target time period.
In connection with any embodiment provided by the present disclosure, the terminal device includes a device that sends a subscription request, and the apparatus further includes a first sending unit, configured to, in response to receiving the subscription request sent by the terminal device, generate recommendation information for use of the resource by the target user according to at least one of location information of the terminal device, information of a target user that uses the terminal device, and prediction information of a usage situation of the resource in the target period; and sending the prediction information and the suggestion information to the terminal equipment.
In combination with any embodiment provided by the present disclosure, the apparatus further includes a second sending unit, configured to generate recommendation information for use of the resource based on the predicted information of the usage of the resource in the target time period; and sending at least one of the prediction information and the suggestion information to public equipment within a set range of the target scene.
In combination with any one of the embodiments provided by the present disclosure, in response to the target scene including a medical place, the prediction information includes a waiting duration, and the recommendation information includes visit recommendation information; and/or, in response to the target scene comprising a public transportation location, the prediction information comprises a waiting duration for each of at least some of the entrances, and the recommendation information comprises recommended entrance information; and/or, in response to the target scene comprising an entry/exit gateway, the prediction information comprises traffic state information of at least part of each traffic place, and the advice information comprises recommended traffic places; and/or, in response to the target scene comprising a first scenic spot, the prediction information comprises a waiting duration for each of at least some of the venues within the first scenic spot; the recommendation information includes at least one of the first scenic spot recommended item and second scenic spot information.
According to an aspect of the present disclosure, an information processing apparatus applied to a terminal device is provided, the apparatus including: a receiving unit, configured to receive prediction information sent by a server, where the prediction information is obtained by using the information processing method according to any embodiment of the present disclosure; and the display unit is used for displaying at least the prediction information through a display interface of the terminal equipment.
In combination with any embodiment provided by the present disclosure, the apparatus further includes a request sending unit, configured to send a subscription request to the server; the receiving unit is specifically configured to: and receiving the prediction information or the prediction information and suggestion information sent by the server to the terminal equipment in response to the subscription request.
In combination with any one of the embodiments provided by the present disclosure, the display unit is specifically configured to: and displaying the prediction information in a first pushing mode and displaying the suggestion information in a second pushing mode through the display interface.
According to an aspect of the present disclosure, an information processing system is provided, the system including: the server is used for obtaining data of multiple dimensions in a target scene, wherein the data of the multiple dimensions at least comprise text data and video data; processing the data of the multiple dimensions to obtain the prediction information of the use condition of at least one resource in the target time interval under the target scene; and sending the prediction information to the terminal device; and the terminal equipment is used for receiving the prediction information and at least displaying the prediction information on a display interface.
According to an aspect of the present disclosure, an information processing apparatus is provided, which includes a memory for storing computer instructions executable on a processor, and the processor is configured to implement the information processing method according to any one of the embodiments of the present disclosure when executing the computer instructions.
According to an aspect of the present disclosure, a computer-readable storage medium is provided, on which a computer program is stored, the program, when executed by a processor, implementing the information processing method according to any one of the embodiments of the present disclosure
The method and the device for predicting the use condition of the resources in the target time period acquire data at least comprising text data and video data of a target scene, acquire prediction information of the use condition of at least one resource in the target scene in the target time period through processing, and send the prediction information to the terminal device. Therefore, the resource occupation condition can be analyzed and predicted, and the prediction information can be obtained. In addition, for users with identities such as visitors and tourists, the technical scheme provided by the disclosure can facilitate the users to know the resource occupation condition.
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.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present disclosure and, together with the description, serve to explain the principles of the disclosure.
Fig. 1 is a flowchart of an information processing method according to at least one embodiment of the present disclosure;
fig. 2 is a flowchart of another information processing method according to at least one embodiment of the disclosure;
fig. 3 is a display example of a terminal device in an information processing method according to at least one embodiment of the present disclosure;
fig. 4 is a schematic structural diagram of an information processing apparatus according to at least one embodiment of the present disclosure;
fig. 5 is a schematic structural diagram of another information processing apparatus according to at least one embodiment of the present disclosure;
fig. 6 is a block diagram of an information processing apparatus according to at least one embodiment of the present disclosure.
Detailed Description
Reference will now be made in detail to the exemplary embodiments, examples of which are illustrated in the accompanying drawings. When the following description refers to the accompanying drawings, like numbers in different drawings represent the same or similar elements unless otherwise indicated. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with the present application. Rather, they are merely examples of apparatus and methods consistent with certain aspects of the present application, as detailed in the appended claims.
The terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the application. As used in this application and the appended claims, the singular forms "a", "an", and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise. It should also be understood that the term "and/or" as used herein refers to and encompasses any and all possible combinations of one or more of the associated listed items. In addition, the term "at least one" herein means any one of a plurality or any combination of at least two of a plurality.
It is to be understood that although the terms first, second, third, etc. may be used herein to describe various information, such information should not be limited to these terms. These terms are only used to distinguish one type of information from another. For example, first information may also be referred to as second information, and similarly, second information may also be referred to as first information, without departing from the scope of the present application. The word "if" as used herein may be interpreted as "at … …" or "when … …" or "in response to a determination", depending on the context.
In order to make the technical solutions in the embodiments of the present disclosure better understood and make the above objects, features and advantages of the embodiments of the present disclosure more comprehensible, the technical solutions in the embodiments of the present disclosure are described in further detail below with reference to the accompanying drawings.
Fig. 1 is a flowchart of an information processing method according to at least one embodiment of the present disclosure, where the method is applied to a server, which may include, but is not limited to, a cloud, a terminal device, and the like. As shown in FIG. 1, the method comprises steps 101-103.
In step 101, data of multiple dimensions in a target scene are obtained, where the data of multiple dimensions at least include text data and video data.
In the disclosed embodiment, the target scene may include one or more of a medical place, a public transportation place, an entrance/exit gateway, a scenic spot, a government affairs service place, and the like.
For different target scenes, corresponding dimensions, corresponding types of data matching the target scene may be obtained. The video data refers to a video stream acquired by an acquisition device such as a camera deployed in the corresponding area of the target scene; the text data refers to text content associated with a target scene.
The video data may comprise video data acquired from at least one acquisition point in the target scene, the video data containing image information of at least one resource corresponding to the acquisition point. The video data is, for example, historical monitoring data collected by a monitoring camera arranged at a position corresponding to the resource within any or a specified time period; the text data may include at least one resource information under the target scene, the resource information including at least one of: information indicating the resource usage, reference operation information in the target scene, sensing information other than visual information acquired by various sensors, and the like.
In the embodiment of the present disclosure, the data of the plurality of dimensions may further include audio information, a data stream generated by an electronic map, and the like, and the present disclosure does not limit the type of data included in addition to the text data and the video data. The method aims to acquire rich data contents through more channels and/or enrich the information content of data by acquiring more angle data sources.
In step 102, the data of the multiple dimensions are processed to obtain the prediction information of the usage of at least one resource in the target time period in the target scene.
Data of multiple dimensions may be descriptions on different dimensions for the same resource. For example, in the case that the target scene is a public transportation location, usually the public transportation location has a plurality of entrances, and for one of the entrances in the public transportation location, on one hand, an entry and exit station record of the entrance, such as a card-swiping record of each user, and the like, can be obtained, and on the other hand, monitoring data of the entrance can be obtained. By combining data of multiple dimensions, the resource use condition can be more accurately described, and more accurate resource use information can be obtained.
It will be understood by those skilled in the art that reference in this disclosure to resource usage information refers to information regarding the usage of the resource over a historical period of time, or a period of time from any or a specified historical time to the current time.
According to the resource usage information, or further in combination with the resource information contained in the text data, the prediction information of the usage of the resource in the target time period can be obtained.
The target time period may be a time period of a set time length from the current time, or may be a time period of a set time length from a certain set time after the current time. For example, the target period may be a period within 12 hours from the current time, or may be an 8-hour period from eight hours in the next morning.
In step 103, the prediction information is sent to the terminal device.
The terminal equipment is equipment except the server. The prediction information can be sent in at least one of a plurality of modes such as short message, mail, WeChat, small program push interface and the like. By sending the prediction information to the terminal device, the target user of the terminal device can know the possible use condition of the resource in the future target time period, so that the use of the resource can be reasonably regulated. By enabling the group to generally support the possible use condition of the resource at a future moment, the optimal configuration of the urban resource can be realized.
It should be noted that the resource referred to in the present disclosure, i.e., the above-mentioned urban resource, refers to public human and material resources providing services in various aspects such as government affairs service, medical treatment, trip, and travel for residents. For example, for medical services, the resources may include, but are not limited to, outpatient service resources, parking service resources in a medical facility, and the like.
In the embodiment of the disclosure, data at least comprising text data and multiple dimensions of video data about a target scene are acquired, prediction information of the use condition of at least one resource in a target period in the target scene is obtained through processing, and the prediction information is sent to a terminal device. Therefore, the resource occupation condition can be analyzed and predicted, and the prediction information can be obtained. In addition, for users with identities such as visitors and tourists, the technical scheme provided by the disclosure can facilitate the users to know the resource occupation condition.
In some embodiments, for the video data, the contained information related to the usage of the corresponding resource may be obtained by performing visual parsing.
In one example, the video data may be input to a target recognition model, and target recognition processing may be performed on the video data to obtain the usage information of the resource. In order to distinguish from usage information obtained in other ways, usage information obtained from the video data is referred to herein as first usage information. Taking a target scene as an example of an open traffic place, the video data includes data of monitoring images for each entrance in the public traffic place, and people included in the images are identified by performing target identification on the monitoring images, so that the flow of people passing through the entrance within a set time can be determined. Taking the target site as a medical site as an example, the video data may include monitoring video data of an emergency waiting area, monitoring video data at an entrance of a parking lot of the medical site, and the like.
In some embodiments, the textual data may include resource information in the form of structured data. The structured data is two-dimensional form data which is represented and stored by a relational database, and the use information of the resources can be more easily acquired from the text data by acquiring the resource information in the form of the structured data.
Taking the target site as a medical site as an example, the acquired text data may include structured medical data, such as the following: [ patient (desensitization), disease type, expert number, project, time ], [ XXX, eczema, yes, registry, 20180801-11:20:15], [ XXX, eczema, yes, assay, 20180801-11:25:15], [ XXX, eczema, yes, check, 20180801-11:30:15 ].
In some embodiments, according to the first usage information corresponding to the same resource in the target scene and the resource information in the text data, the prediction information of the usage of the resource in the target time period may be obtained.
Because the first use information corresponding to the same resource and the resource information in the text data are descriptions of the use condition of the resource from different dimensions, the use condition of the resource can be acquired more comprehensively and more accurately by combining the first use information and the resource information. Therefore, through the combination of the first usage information and the resource information, the usage of the resource in the target period is more accurate.
From the resource information in the text data, usage information for the resource may be obtained. In order to distinguish from the usage information acquired from the video data, the usage information acquired from the text data is referred to as second usage information herein.
In the embodiment of the present disclosure, the first usage information obtained from the video data is matched with the second usage information obtained from the text data in time, that is, the first usage information and the second usage information contain usage information of the same history period. For example, the first usage information and the second usage information both include data within a week before the current time.
By inputting the first usage information and the second usage information to the first neural network, prediction information of usage of the resource over a target period may be obtained. The first neural network can comprise a time sequence prediction network, and the use condition of the resource in a future period can be predicted by learning the use rule of the resource in a historical period, so that the prediction information is generated. It will be appreciated by those skilled in the art that the first neural network may also comprise other types of neural networks, and the present disclosure is not limited thereto.
Taking the target site as a scenic spot as an example, according to the video monitoring data at the entrance of the scenic spot and the video monitoring data at the entrance of the parking lot, the flow of people to enter the scenic spot in each historical time period can be obtained, namely first use information is obtained; according to the text data related to the scenic spot, entrance records of the scenic spot, parking lot sensor records and parking space use condition statistical data in each time period can be obtained, and second use information can be obtained. And predicting the queuing waiting time of the entrance of the scenic spot by using the first use information and the second use information in the same historical period by using the first spirit.
In the embodiment of the present disclosure, according to the resource information in the text data, the reference operation information of the resource may also be obtained. The specific data included in the reference operation information is determined according to a specific target scene, for example, for an open transportation location, the reference operation information may include a train schedule; for a scenic spot, the reference operation information may include an open time of the scenic spot or a planned operation time of each project within the scenic spot.
By inputting the first usage information and the reference operation information of the resource to the second neural network, prediction information of the usage of the resource within a target period can be obtained.
The reference operation time of the resource may provide a reference for the usage of the resource in the target time period. Taking the reference operation information as a train schedule as an example, the method can know in which time periods in the future, more passengers will arrive at the public transportation place according to the train schedule, so that the prediction of the pedestrian volume and the queuing condition of each entrance and each exit can be assisted.
In some embodiments, according to the predicted information of the usage of at least one resource in the target scene in the target time period, the recommendation information of the usage of the at least one resource can be generated to assist the user in making a decision and achieve reasonable scheduling of the resource.
For example, if it is predicted that the user of the resource will peak in a certain period of time in the future, and using the resource in this period will consume a large amount of waiting time in line, it is possible to give other resources that have similar functions to the resource but fewer users and can shorten the waiting time in this period.
In case the usage of the resource is not related to the user's own situation, the usage proposal of the resource may be actively transmitted without targeting. For example, the recommendation information and/or the prediction information are sent to public devices within a set range of the target scene. By the mode, the user in the set range of the target scene can check the use condition estimation of each resource in each future time period in the target scene through the public equipment and can check the use suggestions of each resource simultaneously, so that the user can use the resource in the target scene more reasonably, the waiting time is saved, and the efficiency is improved.
In the embodiment of the present disclosure, the suggestion information may also be generated in combination with the self information of the target user.
The target user can send subscription requests for the prediction information and the suggestion information of each resource in the target scene through the terminal equipment. The terminal device includes a device for sending a subscription request, and the terminal device may be an electronic device of a personal user such as a mobile phone and a tablet computer, or may be a public device within a set range of a target scene. The target user may send the subscription request through the device, for example, the subscription request may be sent in at least one of a plurality of manners, such as a short message, a mail, a WeChat, an applet request interface, and the like. The subscription request may be used to request predicted information of the usage of the target scenario, may also be used to request suggested information of the usage of the target scenario, or may be used to request both the predicted information and the suggested information of the usage of the target scenario.
In response to receiving the subscription request sent by the target user through the terminal device, the recommendation information of the use of the resource for the target user can be generated according to the position information of the terminal device, and/or the information of the target user using the terminal device, and the prediction information of the use condition of the resource in the target time period.
And generating recommendation information for more targeted resource use by combining the position of the target user and the self information of the target user.
Taking the target scene as a medical place as an example, according to the position of the target user, the time of the target user arriving at the medical place can be estimated, and by combining with the prediction information of the use condition of the medical place in the corresponding time period, the suggestion of the visit time of the target user can be more accurately given; according to the self information of the target user, for example, the type of the outpatient service to be visited by the target user, whether the outpatient service has multiple dimensions such as medical kit conditions and the like, the time suggestion of the visit is given, and other medical places more suitable for the visit can be recommended to the user, so that the target user can save the time of the visit, obtain better medical effect, and simultaneously realize the optimized allocation of medical resources in cities.
In some embodiments, the target user may further log in the public device in the set range of the target scene, so that the public device can obtain information of the public device, and send a subscription request through the public device, so as to obtain predicted information and/or suggested information of each resource usage in the target scene.
In one example, in response to the target scenario including a medical site, the prediction information includes a waiting duration, and the recommendation information includes visit recommendation information.
In one example, in response to the target scenario including a public transportation location, the prediction information includes a wait duration for each of at least some of the entrances, and the recommendation information includes recommended entrance information.
In one example, in response to the target scenario including an entry-exit gateway, the predictive information includes traffic status information for each of at least a portion of the traffic locations, and the advice information includes recommended traffic locations.
In one example, in response to the target scene comprising a first scenic spot, the predictive information comprises a wait duration for each of at least some of the venues within the first scenic spot; the recommendation information includes at least one of the first scenic spot recommended item and second scenic spot information.
Fig. 2 is a flowchart of another information processing method proposed in at least one embodiment of the present disclosure, where the method is applied to a terminal device, where the terminal device may include, but is not limited to, a mobile phone, a tablet computer, and the like, and the present disclosure is not limited to the form of the terminal device. As shown in FIG. 2, the method includes steps 201-202.
In step 201, prediction information sent by a server is received, wherein the prediction information may be prediction information sent by an information processing method according to any embodiment of the present disclosure.
In step 202, at least the prediction information is displayed through a display interface of the terminal device.
Fig. 3 is a schematic display diagram of a terminal device in an information processing method according to at least one embodiment of the present disclosure.
As shown in fig. 3, an area 301 above the display interface of the terminal device shows a local area map containing a target scenic spot, and an area 302 below the local area map shows a specific type of prediction information, in this example, a scenic spot queuing situation. Further below is region 303 which illustrates the inclusion of a histogram plot of the scene queuing time prediction indicating the estimated queuing time at a plurality of times within the target time period. The lowermost region 304 of the display area shows a curvy-plot-shown traffic density measure indicating traffic at various times of the day of arrival at the scenic spot. The target time interval corresponding to the prediction information may be set by selecting the expected arrival time, or may be set by manually inputting a specific time. In this example, it is possible to jump to a page where target period setting is made by clicking the scene area 302. It should be understood by those skilled in the art that the display page may also include other types of prediction information, or may only include one of the prediction information, such as only the scenic spot queuing time prediction, or only the people stream density measurement, and the display form of the prediction information may be set, for example, the scenic spot queuing time prediction may also be represented in a curve form. Fig. 3 is only an example, and the present disclosure does not limit the specific display form of the display interface. The presentation form refers to the content of the prediction information and/or the recommendation information, the presentation mode of each item of content, and the like. For example, the arrangement form of each part of content, whether the display process has a corresponding animation effect, and the like.
In some embodiments, the terminal device sends a subscription request to the server, where the subscription request includes the 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.
In response to receiving the prediction information, the prediction information may be displayed in a corresponding page form according to a target scene corresponding to the prediction information.
For example, in response to receiving the scenic spot queuing time period prediction information and the people stream density estimation information, the prediction information may be presented in the form of a page as shown in fig. 3.
In response to receiving the prediction information and the suggestion information, the prediction information and the suggestion information can be displayed in a corresponding page form through a display interface of the terminal device according to the prediction information or/and a target scene corresponding to the suggestion information. For example, the prediction information may be displayed in a first push manner, and the recommendation information may be displayed in a second push manner. The first pushing mode and the second pushing mode can be the same, partially the same or completely different.
In one example, the predictive information and the advisory information may be presented through the same display interface. For example, the prediction information and the suggestion information are respectively displayed in a plurality of windows contained in the display interface; alternatively, the prediction information and the advice information may be separately displayed through the formation of split screens.
In one example, the predictive information and the advisory information may be presented through different display interfaces. For example, the display interface may be slid up and down or left and right to switch from the display interface displaying the predicted information to another display interface displaying the suggested information, so that the two kinds of information may be viewed through different display interfaces.
In one example, the prediction information and the definition information presented on the current display page may be switched according to the operation of the user, so that the user can view the information.
In one example, the predicted information and the suggested information can be pushed circularly, and transition is carried out on the presentation of the two information through a set animation effect.
Fig. 4 is an information processing apparatus provided in at least one embodiment of the present disclosure, where the apparatus is applied to a server, and the apparatus includes: an obtaining unit 401, configured to obtain data of multiple dimensions in a target scene, where the data of multiple dimensions at least includes text data and video data; a prediction unit 402, configured to process the data of the multiple dimensions, and obtain prediction information of a usage situation of at least one resource in a target time period in the target scene; a sending unit 403, configured to send the prediction information to a terminal device.
In some embodiments, the obtaining unit is specifically configured to: acquiring video data acquired by at least one acquisition point in a target scene, wherein the video data comprises image information of at least one resource corresponding to the acquisition point; and acquiring text data containing at least one resource information in the target scene.
In some embodiments, the prediction unit is specifically configured to: inputting the video data to a target recognition model to obtain first usage information of the resource; and obtaining the prediction information of the use condition of the resource in the target time interval according to the first use information and the resource information in the text data.
In some embodiments, the prediction unit, when configured to obtain the 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, is specifically configured to: obtaining second use information of the resource according to resource information in the text data, wherein the first use information is matched with the second use information in time; and inputting the first use information and the second use information into a first neural network to obtain the prediction information of the use condition of the resource in a target time period.
In some embodiments, the prediction unit, when configured to obtain the 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, is specifically configured to:
in some embodiments, reference operation information of the resource in the target time period is obtained according to resource information in the text data; and inputting the first use information and the reference operation information into a second neural network to obtain the prediction information of the use condition of the resource in a target time period.
In some embodiments, the terminal device includes a device that sends a subscription request, and the apparatus further includes a first sending unit, configured to generate, in response to receiving the subscription request sent by the terminal device, recommendation information for use of the resource by a target user according to at least one of location information of the terminal device, information of the target user using the terminal device, and prediction information of use of the resource in the target period; and sending the prediction information and the suggestion information to the terminal equipment.
In some embodiments, the apparatus further includes a second sending unit configured to generate recommendation information for use of the resource based on the predicted information of the usage of the resource in the target time period; and sending at least one of the prediction information and the suggestion information to public equipment within a set range of the target scene.
In some embodiments, in response to the target scenario comprising a medical site, the prediction information comprises a waiting duration, and the recommendation information comprises a visit recommendation information; and/or, in response to the target scene comprising a public transportation location, the prediction information comprises a waiting duration for each of at least some of the entrances, and the recommendation information comprises recommended entrance information; and/or, in response to the target scene comprising an entry/exit gateway, the prediction information comprises traffic state information of at least part of each traffic place, and the advice information comprises recommended traffic places; and/or, in response to the target scene comprising a first scenic spot, the prediction information comprises a waiting duration for each of at least some of the venues within the first scenic spot; the recommendation information includes at least one of the first scenic spot recommended item and second scenic spot information.
Fig. 5 is an information processing apparatus provided in at least one embodiment of the present disclosure, and an information processing apparatus is provided, where the apparatus is applied to a terminal device, and the apparatus includes: a receiving unit 501, configured to receive prediction information sent by a server, where the prediction information is obtained by using an information processing method according to any embodiment of the present disclosure; a display unit 502, configured to display at least the prediction information through a display interface of the terminal device.
In some embodiments, the apparatus further comprises a request sending unit configured to send a subscription request to the server; the receiving unit is specifically configured to: and receiving the prediction information or the prediction information and suggestion information sent by the server to the terminal equipment in response to the subscription request.
In some embodiments, the presentation unit is specifically configured to: and displaying the prediction information in a first pushing mode and displaying the suggestion information in a second pushing mode through the display interface.
Fig. 6 is an electronic device provided in at least one embodiment of the present disclosure, and the device includes a memory for storing computer instructions executable on a processor, and the processor is configured to implement the information processing method according to any one of the embodiments of the present disclosure when executing the computer instructions.
At least one embodiment of the present disclosure also provides a computer-readable storage medium on which a computer program is stored, the program, when executed by a processor, implementing the information processing method according to any one of the embodiments of the present disclosure.
In some embodiments, functions of or modules included in the apparatus provided in the embodiments of the present disclosure may be used to execute the method described in the above method embodiments, and specific implementation thereof may refer to the description of the above method embodiments, and for brevity, will not be described again here.
The above-described embodiments of the apparatus are merely illustrative, wherein the modules described as separate parts may or may not be physically separate, and the parts displayed as modules may or may not be physical modules, may be located in one place, or may be distributed on a plurality of network modules. Some or all of the modules can be selected according to actual needs to achieve the purpose of the solution in the specification. One of ordinary skill in the art can understand and implement it without inventive effort.
The embodiments of the apparatus of the present specification can be applied to a computer device, such as a server or a terminal device. The device embodiments may be implemented by software, or by hardware, or by a combination of hardware and software. The software implementation is taken as an example, and as a logical device, the device is formed by reading corresponding computer program instructions in the nonvolatile memory into the memory for operation through the processor in which the file processing is located. In terms of hardware, a hardware structure diagram of a computer device in which the apparatus of this specification is located, except for a processor, a memory, a network interface, and a nonvolatile memory, a server or an electronic device in which the apparatus is located in an embodiment may also include other hardware according to an actual function of the computer device, which is not described again.
The present disclosure may take the form of a computer program product embodied on one or more storage media including, but not limited to, disk storage, CD-ROM, optical storage, and the like, having program code embodied therein. Computer-usable storage media include permanent and non-permanent, removable and non-removable media, and information storage may be implemented by any method or technology. The information may be computer readable commands, data structures, modules of a program, or other data. Examples of the storage medium of the computer 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 technologies, compact disc read only memory (CD-ROM), Digital Versatile Discs (DVD) or other optical storage, magnetic tape storage or other magnetic storage devices, or any other non-transmission medium, may be used to store information that may be accessed by a computing device.
Other embodiments of the disclosure will be apparent to those skilled in the art from consideration of the specification and practice of the disclosure disclosed herein. This disclosure is intended to cover any variations, uses, or adaptations of the disclosure following, in general, the principles of the disclosure and including such departures from the present disclosure as come within known or customary practice within the art to which the disclosure pertains. It is intended that the specification and examples be considered as exemplary only, with a true scope and spirit of the disclosure being indicated by the following claims.
It will be understood that the present disclosure is not limited to the precise arrangements 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.
The above description is only exemplary of the present disclosure and should not be taken as limiting the disclosure, as any modification, equivalent replacement, or improvement made within the spirit and principle of the present disclosure should be included in the scope of the present disclosure.
The foregoing description of the various embodiments is intended to highlight various differences between the embodiments, and the same or similar parts may be referred to each other, and for brevity, will not be described again herein.
Claims (16)
1. An information processing method, applied to a server, the method comprising:
obtaining data of multiple dimensions in a target scene, wherein the data of the multiple dimensions at least comprises text data and video data;
processing the data of the multiple dimensions to obtain the prediction information of the use condition of at least one resource in the target time interval under the target scene;
and sending the prediction information to the terminal equipment.
2. The method of claim 1, wherein obtaining data for multiple dimensions in a target scene comprises:
acquiring video data acquired by at least one acquisition point in a target scene, wherein the video data comprises image information of at least one resource corresponding to the acquisition point;
and acquiring text data containing at least one resource information in the target scene.
3. The method according to claim 1 or 2, wherein the processing the data of the plurality of dimensions to obtain the prediction information of the usage of at least one resource in the target scene in the target time period comprises:
inputting the video data to a target recognition model to obtain first usage information of the resource;
and obtaining the prediction information of the use condition of the resource in the target time interval according to the first use information and the resource information in the text data.
4. The method of claim 3, wherein obtaining the predicted 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 comprises:
obtaining second use information of the resource according to resource information in the text data, wherein the first use information is matched with the second use information in time;
and inputting the first use information and the second use information into a first neural network to obtain the prediction information of the use condition of the resource in a target time period.
5. The method of claim 3, wherein obtaining the predicted 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 comprises:
acquiring reference operation information of the resources in the target time period according to the resource information in the text data;
and inputting the first use information and the reference operation information into a second neural network to obtain the prediction information of the use condition of the resource in a target time period.
6. The method according to any of claims 1 to 5, wherein the terminal device comprises a device sending a subscription request, the method further comprising:
in response to receiving a subscription request sent by the terminal device, generating recommendation information for the use of the resource of a target user according to at least one of position information of the terminal device, information of the target user using the terminal device, and prediction information of the use condition of the resource in the target period;
and sending the prediction information and the suggestion information to the terminal equipment.
7. The method according to any one of claims 1 to 5, further comprising:
generating recommendation information of the use of the resource based on the prediction information of the use condition of the resource in the target time period;
and sending at least one of the prediction information and the suggestion information to public equipment within a set range of the target scene.
8. The method of any of claims 1 to 7, wherein in response to the target scenario comprising a medical facility, the prediction information comprises a waiting period, and the recommendation information comprises a visit recommendation information;
and/or, in response to the target scene comprising a public transportation location, the prediction information comprises a waiting duration for each of at least some of the entrances, and the recommendation information comprises recommended entrance information;
and/or, in response to the target scene comprising an entry/exit gateway, the prediction information comprises traffic state information of at least part of each traffic place, and the advice information comprises recommended traffic places;
and/or, in response to the target scene comprising a first scenic spot, the prediction information comprises a waiting duration for each of at least some of the venues within the first scenic spot; the recommendation information includes at least one of the first scenic spot recommended item and second scenic spot information.
9. An information processing method, which is applied to a terminal device, the method comprising:
receiving prediction information sent by a server, wherein the prediction information is obtained by the method of any one of claims 1 to 8;
and displaying at least the prediction information through a display interface of the terminal equipment.
10. The method of claim 9, wherein prior to receiving the prediction information sent by the server, the method further comprises:
sending a subscription request to the server;
the receiving of the prediction information sent by the server includes:
and receiving the prediction information or the prediction information and suggestion information sent by the server to the terminal equipment in response to the subscription request.
11. The method of claim 10, wherein the presenting at least the predictive information via a display interface of the terminal device comprises:
and displaying the prediction information in a first pushing mode and displaying the suggestion information in a second pushing mode through the display interface.
12. An information processing apparatus, characterized in that the apparatus is applied to a server, the apparatus comprising:
the device comprises an acquisition unit, a processing unit and a display unit, wherein the acquisition unit is used for acquiring data of multiple dimensions in a target scene, and the data of the multiple dimensions at least comprise text data and video data;
the prediction unit is used for processing the data of the multiple dimensions to obtain prediction information of the use condition of at least one resource in a target time interval under the target scene;
and the sending unit is used for sending the prediction information to the terminal equipment.
13. An information processing apparatus, characterized in that the apparatus is applied to a terminal device, the apparatus comprising:
a receiving unit, configured to receive prediction information sent by a server, where the prediction information is obtained by the method according to any one of claims 1 to 8;
and the display unit is used for displaying at least the prediction information through a display interface of the terminal equipment.
14. An information processing system, the system comprising:
the server is used for obtaining data of multiple dimensions in a target scene, wherein the data of the multiple dimensions at least comprise text data and video data; processing the data of the multiple dimensions to obtain the prediction information of the use condition of at least one resource in the target time interval under the target scene; and sending the prediction information to the terminal device;
and the terminal equipment is used for receiving the prediction information and at least displaying the prediction information on a display interface.
15. An information processing apparatus, characterized in that the apparatus comprises a memory for storing computer instructions executable on a processor for implementing the method of any one of claims 1 to 11 when executing the computer instructions, a processor.
16. A computer-readable storage medium, on which a computer program is stored, which, when being executed by a processor, carries out the method of any one of claims 1 to 11.
Priority Applications (4)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN202010688723.0A CN111831853A (en) | 2020-07-16 | 2020-07-16 | Information processing method, device, equipment and system |
PCT/CN2021/099840 WO2022012241A1 (en) | 2020-07-16 | 2021-06-11 | Information processing method, apparatus, device and system |
JP2022520045A JP2022550192A (en) | 2020-07-16 | 2021-06-11 | Information processing method, device, equipment, system, storage medium and computer program |
KR1020227010846A KR20220051012A (en) | 2020-07-16 | 2021-06-11 | Information processing methods, devices, devices and systems |
Applications Claiming Priority (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN202010688723.0A CN111831853A (en) | 2020-07-16 | 2020-07-16 | Information processing method, device, equipment and system |
Publications (1)
Publication Number | Publication Date |
---|---|
CN111831853A true CN111831853A (en) | 2020-10-27 |
Family
ID=72923560
Family Applications (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
CN202010688723.0A Pending CN111831853A (en) | 2020-07-16 | 2020-07-16 | Information processing method, device, equipment and system |
Country Status (4)
Country | Link |
---|---|
JP (1) | JP2022550192A (en) |
KR (1) | KR20220051012A (en) |
CN (1) | CN111831853A (en) |
WO (1) | WO2022012241A1 (en) |
Cited By (1)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
WO2022012241A1 (en) * | 2020-07-16 | 2022-01-20 | 深圳市商汤科技有限公司 | Information processing method, apparatus, device and system |
Citations (17)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
GB201313880D0 (en) * | 2013-08-02 | 2013-09-18 | Barclays Bank Plc | Location-based navigation |
CN105405291A (en) * | 2015-12-09 | 2016-03-16 | 清华大学 | Traffic data acquisition and active prevention and control system |
CN106297274A (en) * | 2016-10-09 | 2017-01-04 | 上海五零盛同信息科技有限公司 | Wisdom lamp stand and urban traffic situation Forecasting Methodology |
CN108460497A (en) * | 2018-03-28 | 2018-08-28 | 中国民航大学 | A kind of departure hall queueing message reminding method |
CN108769924A (en) * | 2018-04-28 | 2018-11-06 | 哈尔滨工业大学 | A kind of scenic spot tourist chain type trip service system and method |
CN109754621A (en) * | 2019-03-01 | 2019-05-14 | 苏州星奥达科技有限公司 | A kind of video analysis method based on Freeway Conditions situation |
CN109767619A (en) * | 2018-12-29 | 2019-05-17 | 江苏大学 | A kind of intelligent network connection pure electric automobile driving cycle prediction technique |
CN109801474A (en) * | 2019-02-22 | 2019-05-24 | 北京启安智慧科技有限公司 | A kind of the Regional Risk analysis method and system of urban safety |
CN109816976A (en) * | 2019-01-21 | 2019-05-28 | 平安科技(深圳)有限公司 | A kind of traffic management method and system |
CN109872535A (en) * | 2019-03-27 | 2019-06-11 | 深圳市中电数通智慧安全科技股份有限公司 | A kind of current prediction technique of wisdom traffic, device and server |
CN109995799A (en) * | 2017-12-29 | 2019-07-09 | 广东欧珀移动通信有限公司 | Information-pushing method, device, terminal and storage medium |
CN110059668A (en) * | 2019-04-29 | 2019-07-26 | 中国民用航空总局第二研究所 | Behavior prediction processing method, device and electronic equipment |
CN110164128A (en) * | 2019-04-23 | 2019-08-23 | 银江股份有限公司 | A kind of City-level intelligent transportation analogue system |
CN110399905A (en) * | 2019-07-03 | 2019-11-01 | 常州大学 | The detection and description method of safety cap wear condition in scene of constructing |
CN110503833A (en) * | 2019-08-29 | 2019-11-26 | 桂林电子科技大学 | A kind of Entrance ramp inter-linked controlling method based on depth residual error network model |
CN110942353A (en) * | 2019-12-11 | 2020-03-31 | 广州点动信息科技股份有限公司 | Big data based operation analysis method |
CN111044045A (en) * | 2019-12-09 | 2020-04-21 | 中国科学院深圳先进技术研究院 | Navigation method and device based on neural network and terminal equipment |
Family Cites Families (5)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN106777384A (en) * | 2017-02-14 | 2017-05-31 | 广东睿盟计算机科技有限公司 | A kind of method of data display and interaction based on indoor map |
CN108234672B (en) * | 2018-02-10 | 2019-12-27 | 广州小享科技有限公司 | Data pushing method, device and system based on flight information |
CN109739842A (en) * | 2018-12-18 | 2019-05-10 | 河南华景乐游电子科技有限公司 | A kind of smart travel big data platform |
CN110458350A (en) * | 2019-08-06 | 2019-11-15 | 中国铁道科学研究院集团有限公司电子计算技术研究所 | Infrastructure service platform construction method, device and the electronic equipment of railway traffic system |
CN111831853A (en) * | 2020-07-16 | 2020-10-27 | 深圳市商汤科技有限公司 | Information processing method, device, equipment and system |
-
2020
- 2020-07-16 CN CN202010688723.0A patent/CN111831853A/en active Pending
-
2021
- 2021-06-11 KR KR1020227010846A patent/KR20220051012A/en not_active Application Discontinuation
- 2021-06-11 JP JP2022520045A patent/JP2022550192A/en not_active Withdrawn
- 2021-06-11 WO PCT/CN2021/099840 patent/WO2022012241A1/en active Application Filing
Patent Citations (17)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
GB201313880D0 (en) * | 2013-08-02 | 2013-09-18 | Barclays Bank Plc | Location-based navigation |
CN105405291A (en) * | 2015-12-09 | 2016-03-16 | 清华大学 | Traffic data acquisition and active prevention and control system |
CN106297274A (en) * | 2016-10-09 | 2017-01-04 | 上海五零盛同信息科技有限公司 | Wisdom lamp stand and urban traffic situation Forecasting Methodology |
CN109995799A (en) * | 2017-12-29 | 2019-07-09 | 广东欧珀移动通信有限公司 | Information-pushing method, device, terminal and storage medium |
CN108460497A (en) * | 2018-03-28 | 2018-08-28 | 中国民航大学 | A kind of departure hall queueing message reminding method |
CN108769924A (en) * | 2018-04-28 | 2018-11-06 | 哈尔滨工业大学 | A kind of scenic spot tourist chain type trip service system and method |
CN109767619A (en) * | 2018-12-29 | 2019-05-17 | 江苏大学 | A kind of intelligent network connection pure electric automobile driving cycle prediction technique |
CN109816976A (en) * | 2019-01-21 | 2019-05-28 | 平安科技(深圳)有限公司 | A kind of traffic management method and system |
CN109801474A (en) * | 2019-02-22 | 2019-05-24 | 北京启安智慧科技有限公司 | A kind of the Regional Risk analysis method and system of urban safety |
CN109754621A (en) * | 2019-03-01 | 2019-05-14 | 苏州星奥达科技有限公司 | A kind of video analysis method based on Freeway Conditions situation |
CN109872535A (en) * | 2019-03-27 | 2019-06-11 | 深圳市中电数通智慧安全科技股份有限公司 | A kind of current prediction technique of wisdom traffic, device and server |
CN110164128A (en) * | 2019-04-23 | 2019-08-23 | 银江股份有限公司 | A kind of City-level intelligent transportation analogue system |
CN110059668A (en) * | 2019-04-29 | 2019-07-26 | 中国民用航空总局第二研究所 | Behavior prediction processing method, device and electronic equipment |
CN110399905A (en) * | 2019-07-03 | 2019-11-01 | 常州大学 | The detection and description method of safety cap wear condition in scene of constructing |
CN110503833A (en) * | 2019-08-29 | 2019-11-26 | 桂林电子科技大学 | A kind of Entrance ramp inter-linked controlling method based on depth residual error network model |
CN111044045A (en) * | 2019-12-09 | 2020-04-21 | 中国科学院深圳先进技术研究院 | Navigation method and device based on neural network and terminal equipment |
CN110942353A (en) * | 2019-12-11 | 2020-03-31 | 广州点动信息科技股份有限公司 | Big data based operation analysis method |
Non-Patent Citations (1)
Title |
---|
王硕,张健钦: "基于高精激光设备的客流监测及预警系统研究", 《城市勘测》, no. 6, 31 December 2017 (2017-12-31), pages 10 - 15 * |
Cited By (1)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
WO2022012241A1 (en) * | 2020-07-16 | 2022-01-20 | 深圳市商汤科技有限公司 | Information processing method, apparatus, device and system |
Also Published As
Publication number | Publication date |
---|---|
KR20220051012A (en) | 2022-04-25 |
WO2022012241A1 (en) | 2022-01-20 |
JP2022550192A (en) | 2022-11-30 |
Similar Documents
Publication | Publication Date | Title |
---|---|---|
CN112749825B (en) | Method and device for predicting destination of vehicle | |
DE112019002896T5 (en) | INFORMATION PROCESSING DEVICE, INFORMATION PROCESSING METHOD AND PROGRAM | |
CN116431923B (en) | Traffic travel prediction method, equipment and medium for urban road | |
CN116757348A (en) | Travel information intelligent planning management system and method based on artificial intelligence | |
CN111831853A (en) | Information processing method, device, equipment and system | |
CN110046535B (en) | Intelligent travel time prediction system, method and storage medium based on machine learning | |
CN111695009B (en) | Information display method and device | |
JP2010217976A (en) | Information distribution device and information distribution method | |
Saki et al. | Cruising for parking again: Measuring the ground truth and using survival analysis to reveal the determinants of the duration | |
Yang et al. | Dynamic vehicle routing with parking probability under connected environment | |
JP7160763B2 (en) | Information processing device, information processing system, information processing method, program, and application program | |
CN110717352B (en) | Platform passenger flow volume statistical method, server and image acquisition equipment | |
Cokro et al. | Designing Smart Parking System through the Use of IoT and Big Data | |
CN110188965A (en) | For the method and device of the recommendation get-off stop of tourist | |
JP6843662B2 (en) | Mobility data processing equipment, mobility data processing methods, and mobility data processing systems | |
CN110826870A (en) | Scenic spot consumption management method and system and computer readable storage medium | |
WO2024161606A1 (en) | Information processing device, user terminal, and information processing method | |
Nie | Preparing small urban areas for shared mobility with autonomous vehicles: a case study of college town | |
CN111368610A (en) | Violation reminding method and system | |
CN114090717B (en) | Travel note generation method and device and computer equipment | |
US11299167B2 (en) | System and method for improving real-time estimates of visitor volume to places | |
CN118392206B (en) | Travel departure time recommendation method, system, electronic equipment and storage medium | |
Cummings et al. | Simulating large-scale events as a network of heterogeneous queues: framework and application | |
JP7258667B2 (en) | Information providing device, information providing system, and information providing method | |
CN113722614B (en) | Method and device for determining boarding location and server |
Legal Events
Date | Code | Title | Description |
---|---|---|---|
PB01 | Publication | ||
PB01 | Publication | ||
SE01 | Entry into force of request for substantive examination | ||
SE01 | Entry into force of request for substantive examination | ||
REG | Reference to a national code |
Ref country code: HK Ref legal event code: DE Ref document number: 40037853 Country of ref document: HK |