CN111457935A

CN111457935A - Data processing method, device, equipment and machine readable medium

Info

Publication number: CN111457935A
Application number: CN201910059263.2A
Authority: CN
Inventors: 高靖; 张亚楠; 胡明森; 王迅
Original assignee: Alibaba Group Holding Ltd
Current assignee: Banma Zhixing Network Hongkong Co Ltd
Priority date: 2019-01-22
Filing date: 2019-01-22
Publication date: 2020-07-28

Abstract

The embodiment of the application provides a data processing method, a device, equipment and a machine readable medium, wherein the method comprises the following steps: receiving a request of the intelligent device; determining a target vehicle corresponding to the request; determining state information corresponding to the target vehicle according to the track data corresponding to the target vehicle and the destination information; the trajectory data is used to characterize data relating to the travel of the target vehicle; and determining a feedback result corresponding to the request according to the state information, and outputting the feedback result. The embodiment of the application can overcome the limitation of the electronic map to a certain extent, increase the application range of the scheme and further improve the user experience.

Description

Data processing method, device, equipment and machine readable medium

Technical Field

The present application relates to the field of computer technologies, and in particular, to a data processing method, a data processing apparatus, a device, and a machine-readable medium.

Background

With the progress of urbanization and the popularization of vehicles, services related to vehicles have come up. The navigation service is a common service, which can provide a user with a route guidance and route selection service based on an optimal driving route, and thus can improve the convenience of travel of the user.

Current navigation services are typically implemented by smart devices, which may include: a mobile device or a vehicle-mounted device, etc. A method of providing a navigation service may include: determining and displaying a driving route on an electronic map according to a destination input by a user for the user to check and select; and then navigating according to the driving route selected by the user.

The method provides the information of the driving route through the electronic map, which easily limits the application range of the method. For example, some users do not have the ability to read an electronic map, and thus cannot obtain desired information from a driving route displayed on the electronic map. For another example, in some scenarios, it is inconvenient for the user to operate the smart device, for example, after the user wakes up in the morning, the user wants to know the current day's work traffic, but is inconvenient to operate the mobile phone. The providing method cannot meet the information requirement of a specific user, or the providing method cannot meet the information requirement under a specific scene.

Disclosure of Invention

The technical problem to be solved by the embodiment of the application is to provide a data processing method, which can overcome the limitation of an electronic map to a certain extent, increase the application range of a scheme and further improve the user experience.

Correspondingly, the embodiment of the application also provides a data processing device, equipment and a machine readable medium, which are used for ensuring the realization and the application of the method.

In order to solve the above problem, an embodiment of the present application discloses a data processing method, including:

receiving a request of the intelligent device;

determining a target vehicle corresponding to the request;

determining state information corresponding to the target vehicle according to the track data corresponding to the target vehicle and the destination information; the trajectory data is used to characterize data relating to the travel of the target vehicle;

and determining a feedback result corresponding to the request according to the state information, and outputting the feedback result.

receiving a request in voice form;

obtaining a feedback result corresponding to the request from the server; the feedback result is obtained according to state information corresponding to a target vehicle, and the state information is obtained according to track data corresponding to the target vehicle and destination information;

and outputting the feedback result in a voice form.

On the other hand, the embodiment of the present application further discloses a data processing apparatus, including:

the request receiving module is used for receiving a request of the intelligent equipment;

the first determination module is used for determining a target vehicle corresponding to the request;

the second determining module is used for determining the state information corresponding to the target vehicle according to the track data corresponding to the target vehicle and the destination information; the trajectory data is used to characterize data relating to the travel of the target vehicle; and

and the first feedback result output module is used for determining a feedback result corresponding to the request according to the state information and outputting the feedback result.

In another aspect, an embodiment of the present application further discloses an apparatus, including:

one or more processors; and

one or more machine-readable media having instructions stored thereon that, when executed by the one or more processors, cause the apparatus to perform one or more of the methods described above.

In yet another aspect, embodiments of the present application disclose one or more machine-readable media having instructions stored thereon, which when executed by one or more processors, cause an apparatus to perform one or more of the methods described above.

Compared with the prior art, the embodiment of the application has the following advantages:

in the embodiment of the application, the feedback result corresponding to the request can be obtained according to the state information corresponding to the target vehicle, and the output mode of the feedback result can be independent of the electronic map, so that the limitation of the electronic map can be overcome to a certain extent, the application range of the scheme is enlarged, and the user experience can be improved.

For example, the output mode of the feedback result may include: text mode, or voice mode, etc. The feedback result is output through the text information, and the information requirement of the user without the ability of reading the electronic map can be met. The feedback result is output in a voice mode, so that the information requirement of a user who does not have the ability of reading the electronic map can be met, and the information requirement of the user who is not convenient to operate the intelligent device can be met.

The state information is obtained from the trajectory data corresponding to the target vehicle and the destination information, and the trajectory data can represent data related to the traveling of the target vehicle, so that the matching degree between the state information and the target vehicle can be improved.

Drawings

FIG. 1 is an illustration of an application environment for a data processing method of the present application;

FIG. 2 is a flow chart of steps of a first embodiment of a data processing method of the present application;

FIG. 3 is a flowchart illustrating steps of a second embodiment of a data processing method according to the present application;

FIG. 4 is a flowchart of the steps of a third embodiment of a data processing method of the present application;

FIG. 5 is a schematic illustration of a data interaction of an embodiment of the present application;

FIG. 6 is a schematic illustration of a data interaction of an embodiment of the present application;

FIG. 7 is a block diagram of an embodiment of a data processing apparatus of the present application;

FIG. 8 is a block diagram of an embodiment of a data processing apparatus of the present application; and

fig. 9 is a schematic structural diagram of an apparatus according to an embodiment of the present application.

Detailed Description

In order to make the aforementioned objects, features and advantages of the present application more comprehensible, the present application is described in further detail with reference to the accompanying drawings and the detailed description.

The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are only a part of the embodiments of the present application, and not all of the embodiments. All other embodiments that can be derived from the embodiments given herein by a person of ordinary skill in the art are intended to be within the scope of the present disclosure.

While the concepts of the present application are susceptible to various modifications and alternative forms, specific embodiments thereof have been shown by way of example in the drawings and will herein be described in detail. It should be understood, however, that the description above is not intended to limit the application to the particular forms disclosed, but on the contrary, the intention is to cover all modifications, equivalents, and alternatives falling within the spirit and scope of the application.

Reference in the specification to "one embodiment," "an embodiment," "a particular embodiment," or the like, means that the embodiment described may include a particular feature, structure, or characteristic, but every embodiment may or may not necessarily include the particular feature, structure, or characteristic. Moreover, such phrases are not necessarily referring to the same embodiment. Further, where a particular feature, structure, or characteristic is described in connection with an embodiment, it is submitted that it is within the knowledge of one skilled in the art to affect such feature, structure, or characteristic in connection with other embodiments whether or not explicitly described. In addition, it should be understood that items in the list included in the form "at least one of a, B, and C" may include the following possible items: (A) (ii) a (B) (ii) a (C) (ii) a (A and B); (A and C); (B and C); or (A, B and C). Likewise, a listing of items in the form of "at least one of a, B, or C" may mean (a); (B) (ii) a (C) (ii) a (A and B); (A and C); (B and C); or (A, B and C).

In some cases, the disclosed embodiments may be implemented as hardware, firmware, software, or any combination thereof. The disclosed embodiments may also be implemented as instructions carried or stored on one or more transitory or non-transitory machine-readable (e.g., computer-readable) storage media, which may be executed by one or more processors. A machine-readable storage medium may be implemented as a storage device, mechanism, or other physical structure (e.g., a volatile or non-volatile memory, a media disk, or other media other physical structure device) for storing or transmitting information in a form readable by a machine.

In the drawings, some structural or methodical features may be shown in a particular arrangement and/or ordering. Preferably, however, such specific arrangement and/or ordering is not necessary. Rather, in some embodiments, such features may be arranged in different ways and/or orders than as shown in the figures. Moreover, the inclusion of structural or methodical features in particular figures is not meant to imply that such features are required in all embodiments and that, in some embodiments, such features may not be included or may be combined with other features.

An embodiment of the present application provides a data processing scheme, which may specifically include: receiving a request of the intelligent device; determining a target vehicle corresponding to the request; determining state information corresponding to the target vehicle according to the track data corresponding to the target vehicle and the destination information; the trajectory data is used to characterize the data relating to the travel of the target vehicle; and determining a feedback result corresponding to the request according to the state information, and outputting the feedback result.

The embodiment of the application can provide the information service corresponding to the vehicle. Specifically, a request of the intelligent device may be received, and a feedback result corresponding to the request may be provided to the user.

The applicable scenes of the embodiment of the invention can comprise: conversation scenarios, search scenarios, etc. The dialog scene may be an intelligent dialog scene or a common dialog scene. The intelligent dialogue scene can be used for generating natural seamless butt-joint dialogue between people and computers, the request in the intelligent dialogue scene can be a request sent by a user, and the request in the common dialogue scene can be a request sent by a communication opposite terminal. The request in the search scenario may be a search word input by the user, for example, a question posted by the user at a question and answer website, as well as a search word input by the user in an input box of a search engine. It is to be understood that the request in the embodiment of the present invention may be a request in any scenario, and the embodiment of the present invention does not limit specific scenarios and requests.

The data processing method provided by the embodiment of the present application can be applied to the application environment shown in fig. 1, as shown in fig. 1, the client 100 and the server 200 are located in a wired or wireless network, and the client 100 and the server 200 perform data interaction through the wired or wireless network.

Optionally, the client may run on the device, for example, the client may be an APP running on the device, such as an instant messaging APP, a vehicle service APP, a conversation APP, a voice assistant APP, or an APP carried by an operating system, and the embodiment of the present application does not limit a specific APP corresponding to the client.

Optionally, the above devices may specifically include, but are not limited to, a smart phone, a tablet computer, an e-book reader, an MP3 (Moving Picture Experts Group Audio L layer iii) player, an MP4 (Moving Picture Experts Group Audio L layer IV) player, a laptop computer, a vehicle-mounted device, a desktop computer, a set-top box, a smart television, a wearable device, a smart Audio, and the like.

Optionally, the apparatus may include: and (4) intelligent equipment. The intelligent equipment is a science and technology concept behind the smart phone, and is transformed from the traditional equipment in a mode of combining software and hardware, so that the intelligent equipment has an intelligent function. After the intelligent operation, the hardware has the connection capability, the loading of the internet service is realized, a typical architecture of 'cloud + end' is formed, and the intelligent operation system has additional values of big data and the like.

The retrofit objects may be electronic devices, such as wearable devices for watches, televisions, stereos, and other appliances; it may also be a device that has not been previously electronized, such as a door lock, a cup, a car or even a house. The field of smart devices may include: wearable equipment extends to fields such as intelligent TV, intelligent stereo set, intelligent house, intelligent car, medical health, intelligent toy, robot.

When the embodiment of the application is applied to the intelligent device, the intelligent device can have an intelligent conversation function, receive the request in the voice form, analyze the request, determine the feedback result according to the analysis result, and output the feedback result in the voice form to the user. The intelligent conversation function can realize the conversation between the equipment and the user in a voice mode, and the user does not need to perform specific operations such as touch operation, reading operation and the like, so that the information requirement of the user who is inconvenient to operate the equipment can be met.

For example, an elderly user may not operate a smartphone, but may have a conversation with a smart tv to obtain feedback results in the form of speech. As another example, a user lying in bed, running, or cooking may not be able to operate the smartphone easily, but may have a conversation with the smart tv to obtain feedback results in the form of speech.

Method embodiment one

Referring to fig. 2, a flowchart illustrating steps of a first embodiment of a data processing method according to the present application is shown, which may specifically include the following steps:

step 201, receiving a request of an intelligent device;

step 202, determining a target vehicle corresponding to the request;

step 203, determining state information corresponding to the target vehicle according to the track data corresponding to the target vehicle and the destination information; the trajectory data is used to characterize the data relating to the travel of the target vehicle;

and step 204, determining a feedback result corresponding to the request according to the state information, and outputting the feedback result.

At least one step of the embodiment shown in fig. 2 may be performed by a server and/or a client, and of course, the embodiment of the present invention does not limit the specific execution subject of each step.

In step 201, the client on the smart device side may receive a request input by a user through an input method such as a voice input method and a keyboard input method. Or, the client may receive information sent by the correspondent node, and obtain the request according to the information. It is to be understood that embodiments of the present invention are not limited to the particular requests.

Embodiments of the present invention may assume that the request is presented in text form. For requests that are presented in a non-textual form, the non-textual form of the request may be converted to a textual form of the request. For example, a request in speech form may be converted to a request in text form by speech recognition techniques. As another example, OCR (Optical Character Recognition) may be performed on the request in the form of a picture to obtain the request in the form of text.

In step 202, optionally, the request originates from a client corresponding to the smart device side, and an identifier corresponding to the client is associated with the target vehicle.

According to one embodiment, the corresponding identification of the client may include: and (4) identifying the user. Then, according to the user identifier, the mapping relationship between the user and the vehicle can be searched to obtain the target vehicle corresponding to the request.

According to another embodiment, the identification corresponding to the client may include: the device identifier of the intelligent device can be searched in the mapping relationship between the device and the vehicle according to the device identifier, so as to obtain the target vehicle corresponding to the request.

The user identification may be: the contact information of the user (such as a mailbox, a mobile phone number and the like), or the account registered by the user and the like. The device identification may be used to uniquely identify the device, and may include: MAC (Media access control) Address, International Mobile Equipment Identity (IMEI), SN (Serial Number), and the like.

In practical applications, the vehicle may be characterized by a vehicle identification. The vehicle identification may have uniqueness, and the vehicle identification may include: license plate number, model number + user identification, etc. Thus, according to yet another embodiment, the request may correspond to a vehicle identification, and the target vehicle to which the request corresponds may be determined based on the vehicle identification.

In step 203, the destination may refer to a place to be reached. The destination corresponding to the target vehicle may refer to a place to which the target vehicle intends to arrive.

In this embodiment of the application, optionally, the destination may include:

obtaining a place according to the position of the intelligent equipment; such as a destination in the case where the location of the smart device is the departure point, or a location of the smart device is a point a and the destination is a parking lot near the point a.

Alternatively, the destination may include: and the commuting place corresponding to the target vehicle. Commuting refers to the process of going to and from the work site from home. Thus, the commute location may include: home or work place.

Trajectory data is used to characterize the data relating to the travel of the target vehicle. A trajectory may refer to a pattern formed by the moving points that meet certain conditions. For example, the trajectory may include: the pattern formed by the continuous moving points can be irregular lines and the like. Optionally, the embodiment of the present application may determine the trajectory according to the continuity of the trajectory points in terms of position and time.

Optionally, the trajectory data may include: historical track, or current track, or future track. The historical trajectory may refer to a trajectory that has ended, while the current trajectory may refer to a trajectory that is traveling, has not ended, and the future trajectory may refer to a trajectory that is at rest, has not started, etc. Optionally, the different trajectories are not continuous in position or not continuous in time for the same target vehicle.

Optionally, the trajectory data may include: road condition information of the track. For example, the traffic information corresponding to at least one road segment in the commuting track of the target vehicle may include: congestion or clear, etc.

In an optional embodiment of the present application, the trajectory data may include: a historical track;

the destination corresponding to the target vehicle may be determined by: and determining a destination corresponding to the target vehicle from end points in a historical track corresponding to the target vehicle according to the request, and/or time information corresponding to the target vehicle, and/or first position information corresponding to the target vehicle, and/or second position information corresponding to the intelligent device.

Endpoints in the historical track may include: a starting point and an end point. The track scene corresponding to the target vehicle is usually regular. The trajectory scene may include: the scene of going to work, the scene of shopping, or body-building scene, connect children scene, send children scene, scene of arriving at home, etc. Wherein, for two different track scenes, at least one different endpoint exists in the two track scenes.

According to the method and the device, the historical track of the user can be analyzed, so that the track scene corresponding to the historical track and the characteristics corresponding to the track scene can be obtained. The corresponding features of the track scene may include: second keyword, date, or time period, etc.

The end points of the historical track may also become the end points of the current track or the future track. Therefore, the destination corresponding to the target vehicle can be determined from the end points in the historical track corresponding to the target vehicle.

According to one embodiment, determining the basis for the destination corresponding to the target vehicle may include: and (6) requesting. Optionally, the first keyword included in the request may be matched with the second keyword of the track scene, and the destination may be determined according to the endpoint of the target track scene successfully matched.

For example, the request is "how long the vehicle has arrived home" or "how long the user a has arrived home", the user a may be a family, such as a couple, a child, or the like, and it can be found through matching that the first keyword "to home" included in the request is successfully matched with the scene of arriving home, and thus it can be determined that the destination is "home".

For another example, the request is "work road condition", and it can be found through matching that the first keyword "work" included in the request is successfully matched with the work scene, so that the destination can be determined to be "unit".

According to another embodiment, determining the basis of the destination corresponding to the target vehicle may include: and time information corresponding to the target vehicle. The time information may include: date and time period. According to the method and the device, the date and the time period corresponding to the target vehicle can be matched with the date and the time period of the track scene, and the destination can be determined according to the end point of the target track scene which is successfully matched.

For example, in the morning of a workday, the target trajectory scene is a work scene and the destination is "unit". In the afternoon of a workday, the target track scene is the next-shift scene and the destination is "home". For another example, in the morning of the holiday, the target track scene is a shopping scene, and the destination is "shopping mall", etc.

According to yet another embodiment, determining the basis for the destination corresponding to the target vehicle may include: and first position information corresponding to the target vehicle. Since the first position information corresponding to the target vehicle has real-time performance and generally corresponds to the starting point or the middle point of the track, the first position information corresponding to the target vehicle can be matched with the first end point of the historical track, and if the matching is successful, the second end point of the historical track can be used as a candidate destination. Further, the destination can be determined from the candidate destinations according to the request and/or the time information corresponding to the target vehicle.

Optionally, the first position information corresponding to the target vehicle may be obtained by communicating with an on-board device on the target vehicle, and it is understood that the embodiment of the present application is not limited to a specific determination manner of the position information. In this case, the server may use the position information last acquired by the vehicle-mounted device as the first position information corresponding to the target vehicle.

The second position information corresponding to the intelligent device can represent the position of the user, and therefore can be used as a basis for determining the target track scene. In practical application, the second position information and the request corresponding to the intelligent device can be combined to obtain the target track scene.

For example, the request is "how long the car has arrived home", and it can be found through matching that the first keyword "arrive home" included in the request is successfully matched with the scene of arriving home, so that the destination can be determined to be "home". And the second location information corresponding to the smart device may be used as the location information of "home".

For another example, the request is "work road condition", and it can be found through matching that the first keyword "work" included in the request is successfully matched with the work scene, so that the destination can be determined to be "unit". In this case, the second location information corresponding to the smart device may also be used as a starting point.

In an optional embodiment of the present application, the destination may include: a first destination and a second destination;

the first destination may be an end point of a first historical track and a start point of a second historical track, the second destination may be an end point of the second track, and a time difference between the first historical track and the second historical track does not exceed a time threshold.

According to the information service method and the information service device, the first historical track and the second historical track with the time difference value not exceeding the time threshold can be determined from the historical tracks, and the first destination and the second destination can be determined according to the first historical track and the second historical track, so that the information requirements of users who continuously execute the two tracks can be met, and the intelligence of the information service can be improved.

In one example, the track scenario of user a in the noon on weekdays includes, in order: the child sending scene and the working scene are respectively a home and a school, and the starting point and the end point of the working scene are respectively a school and a unit. In the case that the request sent by the user a in the morning is "road conditions", the embodiment of the present application may automatically determine the first destination "school" and the second destination "unit" for the user a.

In one example, the track scenario of user a in afternoon weekdays includes in order: the method comprises a child receiving scene and a home arriving scene, wherein the starting point and the end point of the child receiving scene are respectively a unit and a school, and the starting point and the end point of the home arriving scene are respectively a school and a home. In the case that the request sent by the user a in the afternoon is "road condition", the embodiment of the present application may automatically determine the first destination "school" and the second destination "home" for the user a.

In this embodiment of the application, optionally, the state information may include:

time-consuming information of the target vehicle to reach the destination; and/or

Distance information of the target vehicle to the destination; and/or

And the target vehicle reaches the road condition information of the destination.

In an optional embodiment of the present application, the trajectory data may include: a plurality of historical tracks corresponding to the destination;

determining the state information corresponding to the target vehicle according to the trajectory data corresponding to the target vehicle and the destination information may specifically include: determining a target historical track from a plurality of historical tracks corresponding to the destination according to the driving restriction attribute corresponding to the target vehicle and/or the occurrence information of one historical track in the plurality of historical tracks; and determining the state information corresponding to the target vehicle according to the target historical track.

The restricted driving attribute may refer to a restricted driving attribute corresponding to the license plate number of the target vehicle. The restriction attributes may include: the restricted time, the restricted range, etc. According to the method and the device, the target historical track can be determined according to the driving restriction attribute corresponding to the target vehicle, so that the target historical track is consistent with the track which does not violate rules.

The occurrence information of one historical track in the plurality of historical tracks can reflect the use probability of a user for one historical track, so that the use probability of the target historical track is the highest and accords with the habit of the user.

According to the method and the device for predicting the historical track, the most probable target historical track used by the user can be predicted according to the driving restriction attribute corresponding to the target vehicle and/or the occurrence information of one historical track in the plurality of historical tracks, and the state information is determined according to the target historical track, so that the matching degree between the state information and the actual information can be improved.

In an optional embodiment of the application, the determining the state information corresponding to the target vehicle according to the target historical track may specifically include: determining a road section of the target vehicle reaching the destination according to the target historical track and first position information corresponding to the target vehicle; and determining the state information corresponding to the target vehicle according to the road section.

In practical application, a road segment of the target vehicle reaching the destination can be acquired from the target historical track according to the first position information and the destination. For example, the first location information may be a starting point or an intermediate point of the target history track, among others.

Optionally, the determining the state information corresponding to the target vehicle according to the road segment may specifically include: and determining time-consuming information of the target vehicle to reach the destination according to the road condition of the road section.

The road condition may refer to a road condition. The road condition can be used as a basis for determining time-consuming information. Alternatively, the road condition may include: clear or congested, etc. The time consumption corresponding to unobstructed is less than the time consumption corresponding to congestion.

In an optional embodiment of the present application, the feedback result may include:

a second comparison result between the time-consuming information and historical time-consuming information; and/or

A second comparison result between the traffic information and historical traffic information; and/or

And the recommendation information is determined according to the second comparison result and/or the second comparison result.

In an optional embodiment of the present application, the method may further comprise:

determining a second comparison result between the time-consuming information and historical time-consuming information; the historical time-consuming information may be the shortest one-time historical time-consuming information, or the historical time-consuming information may be a statistical value of the multiple times of historical time-consuming information, and the statistical value may be a variance value or an average value.

Outputting the second comparison result as a feedback result corresponding to the request; and/or determining suggestion information according to the second comparison result, and outputting the suggestion information as a feedback result corresponding to the request.

For example, the second comparison result may be "N minutes more", "take N minutes more than usual", or the like. Alternatively, the road condition and the second comparison result may be used as a feedback result corresponding to the request, for example, "the location a is congested, takes N minutes more than usual" or the like.

The advice information may provide support for traveling of the target vehicle. For example, in the case where the second comparison result is greater than the first comparison result, the advice information may be "congestion of today's road condition, advice you travel ahead". For another example, in the case that the second comparison result is less than the first comparison result, the recommendation information may be "today's road condition is general, please do not need to be urgent".

The advice information may provide effective information to the user. For example, the user is an old person waiting for a child to leave work at home, and in the case that the second comparison result is greater than the first comparison result, the second comparison result may be "congestion of road conditions today, M minutes later than usual", and the advice information may be "advice you to start a meal late"; in the case where the second comparison result is less than this, the advice information "come home earlier than usual today, suggest you to start a meal earlier", and the like.

Optionally, the feedback result may further include: and congestion information of the location, so that the reason why the time consumption information is larger than the historical time consumption information is obtained.

determining a second comparison result between the traffic information and historical traffic information; the historical traffic information may be the latest historical traffic information, or the historical traffic information may be a statistical value of the multiple historical traffic information, and the statistical value may be a variance value or a mean value.

Outputting the second comparison result as a feedback result corresponding to the request; and/or determining first suggestion information according to the second comparison result, and outputting the first suggestion information as a feedback result corresponding to the request.

In step 204, the server may output the status information to the client on the smart device side, or the client may output the status information to the user. The output mode of the state information can be independent of the electronic map, so that the limitation of the electronic map can be overcome to a certain extent, the application range of the scheme is enlarged, and the user experience can be improved.

Optionally, the step 204 of outputting the feedback result may specifically include: outputting the feedback result in a voice form or a text form.

In an optional embodiment of the present application, the state information may be converted into a feedback result in a natural language form, and the natural language form may be a statement form, so that a distance between the feedback result and a user may be shortened, and user experience may be improved. Natural language generally refers to a language that naturally evolves with culture. Chinese, english, chinese, japanese are examples of natural languages.

For example, when the request is "how long the car has been home", P minutes may be converted to "the car estimates that P minutes have been home". Or, the feedback result may also carry the first position information corresponding to the target vehicle, and the obtained feedback result in the natural language form may be "the vehicle is currently at the location B, and P minutes are estimated to arrive at home", and the like.

For example, in the case where the request is "traffic on duty", the obtained feedback result in the natural language form may be "point a is congested and takes N minutes more than usual", or "point a is congested and takes N minutes more than usual, and you are advised to go ahead".

In summary, according to the data processing method provided by the embodiment of the application, the feedback result corresponding to the request can be obtained according to the state information corresponding to the target vehicle, and the output mode of the feedback result can be independent of the electronic map, so that the limitation of the electronic map can be overcome to a certain extent, the application range of the scheme is increased, and the user experience can be further improved.

Method embodiment two

Referring to fig. 3, a flowchart illustrating steps of a second embodiment of the data processing method according to the present application is shown, where the method may specifically include the following steps:

step 301, receiving a request in a voice form;

step 302, obtaining a feedback result corresponding to the request from a server; the feedback result can be obtained according to state information corresponding to a target vehicle, and the state information can be obtained according to trajectory data corresponding to the target vehicle and destination information;

and step 303, outputting the feedback result in the form of voice.

At least one step of the embodiment shown in fig. 3 may be executed by the client, although the embodiment of the present invention does not limit the specific execution subject of each step.

The client side of the embodiment of the application can receive the request in the voice form and output the feedback result in the voice form, can overcome the condition that the user is inconvenient to input the request through a keyboard, and can overcome the condition that the feedback result is inconvenient to check, thereby improving the convenience of the user for obtaining information. Therefore, the embodiment of the application can be applied to the intelligent device side.

In step 302, the request may be sent to a server, so that the server obtains a feedback result corresponding to the request. The server can obtain the feedback result corresponding to the request by utilizing the advantages of abundant operation resources and data resources, so that the obtaining efficiency and accuracy of the feedback result can be improved. For example, the computational resources of the server may include: a cluster of servers, for example, the data resources of a server may include: map data, real-time traffic data, and the like.

In step 303, the feedback result in the form of voice may be played to the user.

Alternatively, a speech synthesis technique may be employed to convert the feedback result in text form into a feedback result in speech form. Speech synthesis technology is a technology for generating artificial speech by a mechanical, electronic method. TTS (Text To Speech) is a Speech synthesis technology, which converts Text information generated by a computer or inputted from the outside into intelligible and fluent spoken chinese language and outputs the spoken Text.

Distance information of the target vehicle to the destination; and/or

In this embodiment of the application, optionally, the feedback result may include:

In this embodiment of the application, optionally, the destination may include:

obtaining a place according to the position of the intelligent equipment; or

And the commuting place corresponding to the target vehicle.

In this embodiment of the application, optionally, the destination may include: a first destination and a second destination;

the first destination is an end point of a first historical track corresponding to the target vehicle and is a starting point of a second historical track corresponding to the target vehicle, the second destination is an end point of the second track, and a time difference value between the first historical track and the second historical track does not exceed a time threshold value.

In summary, the data processing method of the embodiment of the present application may receive a request in a voice format, output a feedback result in the voice format, overcome a situation that a user is not convenient to input the request through a keyboard, and overcome a situation that the feedback result is not convenient to view, thereby improving convenience of obtaining information for the user.

Method embodiment three

Referring to fig. 4, a flowchart illustrating steps of a third embodiment of a data processing method according to the present application is shown, where the method may specifically include the following steps:

step 401, the client sends a request in a voice form, second position information corresponding to the intelligent device and an identifier of the client to the server;

step 402, the server determines a target vehicle according to the identification of the client;

step 403, the server determines the destination of the target vehicle according to the request and the second position information corresponding to the intelligent device;

the second location information corresponding to the smart device may be used to characterize the location of the user, and the second location information corresponding to the smart device may correspond to the destination, or the second location information corresponding to the smart device may correspond to the departure location, and thus may be used as a basis for determining the destination.

Step 404, the server determines a target historical track corresponding to the destination according to the track data corresponding to the target vehicle and the destination information;

the target history track may represent a history track most likely to be used by the user, and the state information is determined based on the target history track, whereby the degree of matching between the state information and the actual information may be improved. Taking the state information as the time consumption information as an example, the actual information may refer to information about time actually consumed by the target vehicle.

Step 405, the server determines time-consuming information of the target vehicle reaching the destination according to road conditions of road sections in the target historical track;

the road condition may refer to a real-time traffic condition of the road segment. The road conditions may include: traffic jam degree, jam continuous road sections, jam reasons and the like.

Step 406, the server determines a feedback result corresponding to the request according to the time-consuming information, and outputs the feedback result to the client;

step 407, the client plays the feedback result to the user.

Referring to fig. 5, a data interaction diagram of an embodiment of the present application is shown, in which a user queries at home through a smart device when a family member arrives at home.

In a specific implementation, the vehicle-mounted device on the vehicle may report the first location information to the server in real time. In a case where the user initiates a request to the smart device "how long the vehicle has been home", the smart device may send the request and the second location information to the server. The server can determine time consumption information and distance information of the vehicle from the departure place to the destination according to the track data of the target vehicle by taking the first position information as the departure place and the second position information as the destination, and the time consumption information and the distance information are returned to the intelligent device and broadcasted to the user by the intelligent device. Examples of feedback results may include: "vehicle is currently at location a, estimated to arrive home after P minutes". The point a may be a point between the departure point and the destination.

Referring to fig. 6, a data interaction diagram of an embodiment of the present application is shown, where a user queries an office road condition at home through an intelligent device, the intelligent device reports the office road condition and time consumption information of an arrival unit, and compares the information with historical time consumption information, and if the comparison result is greater than the historical time consumption information, the user is reminded to go out ahead.

In a specific implementation, the user initiates a request of "work traffic condition" to the intelligent device, and the intelligent device sends the request and the second location information to the server. The server can use the first position information as a departure place and the unit corresponding to the request as a destination, determine time-consuming information of the vehicle from the departure place to the destination according to the track data of the target vehicle, return the time-consuming information to the intelligent device, and broadcast the time-consuming information to the user by the intelligent device. Examples of feedback results may include: "place B is congested, takes Q minutes more than usual, advising you to go ahead". The point B may be a point between the departure point and the destination. And comparing the time-consuming information with historical time-consuming information, and broadcasting the comparison result and corresponding suggestion information to the user.

It should be noted that, for simplicity of description, the method embodiments are described as a series of acts or combination of acts, but those skilled in the art will recognize that the embodiments are not limited by the order of acts described, as some steps may occur in other orders or concurrently depending on the embodiments. Further, those skilled in the art will also appreciate that the embodiments described in the specification are presently preferred and that no particular act is required of the embodiments of the application.

The embodiment of the application also provides a data processing device.

Referring to fig. 7, a block diagram of an embodiment of a data processing apparatus according to the present application is shown, where the apparatus may specifically include the following modules:

a request receiving module 701, configured to receive a request of an intelligent device;

a first determining module 702, configured to determine a target vehicle corresponding to the request;

a second determining module 703, configured to determine, according to the trajectory data and the destination information corresponding to the target vehicle, state information corresponding to the target vehicle; the trajectory data is used to characterize the data relating to the travel of the target vehicle; and

a first feedback result output module 704, configured to determine a feedback result corresponding to the request according to the state information, and output the feedback result.

Optionally, the destination may include:

obtaining a place according to the position of the intelligent equipment; or

And the commuting place corresponding to the target vehicle.

Optionally, the destination may include: a first destination and a second destination;

Optionally, the status information may include:

Distance information of the target vehicle to the destination; and/or

Optionally, the trajectory data may include: a plurality of historical tracks corresponding to the destination;

the second determining module may include:

the target historical track determining module is used for determining a target historical track from a plurality of historical tracks corresponding to the destination according to the driving restriction attribute corresponding to the target vehicle and/or the occurrence information of one historical track in the plurality of historical tracks;

and the information determining module is used for determining the state information corresponding to the target vehicle according to the target historical track.

Optionally, the information determining module may include:

the road section determining module is used for determining a road section of the target vehicle reaching the destination according to the target historical track and first position information corresponding to the target vehicle;

and the state information determining module is used for determining the state information corresponding to the target vehicle according to the road section.

Optionally, the status information determining module may include:

and the time consumption determining module is used for determining time consumption information of the target vehicle reaching the destination according to the road condition of the road section.

Optionally, the apparatus may further include:

the comparison result determining module is used for determining a comparison result between the time consumption information and historical time consumption information;

the second feedback result output module is used for outputting the comparison result as a feedback result corresponding to the request; and/or determining suggestion information according to the comparison result, and outputting the suggestion information as a feedback result corresponding to the request.

Optionally, the trajectory data may include: a historical track;

the apparatus may further include:

and the destination determining module is used for determining a destination corresponding to the target vehicle from end points in a historical track corresponding to the target vehicle according to the request, and/or time information corresponding to the target vehicle, and/or first position information corresponding to the target vehicle, and/or second position information corresponding to the intelligent device.

Optionally, the first feedback result output module is specifically configured to output the state information in a speech form or a text form.

Optionally, the form of the feedback result may include:

a speech form, and/or a text form.

Referring to fig. 8, a block diagram of an embodiment of a data processing apparatus according to the present application is shown, where the apparatus may specifically include the following modules:

a receiving module 801, configured to receive a request in a voice form;

a feedback result obtaining module 802, configured to obtain a feedback result corresponding to the request from the server; the feedback result can be obtained according to state information corresponding to a target vehicle, and the state information can be obtained according to trajectory data corresponding to the target vehicle and destination information; and

a feedback result output module 803, configured to output the feedback result in a form of voice.

Optionally, the status information may include:

Distance information of the target vehicle to the destination; and/or

Optionally, the feedback result may include:

For the device embodiment, since it is basically similar to the method embodiment, the description is simple, and for the relevant points, refer to the partial description of the method embodiment.

The embodiments in the present specification are described in a progressive manner, each embodiment focuses on differences from other embodiments, and the same and similar parts among the embodiments are referred to each other.

With regard to the apparatus in the above-described embodiment, the specific manner in which each module performs the operation has been described in detail in the embodiment related to the method, and will not be elaborated here.

Embodiments of the application may be implemented as a system or device using any suitable hardware and/or software for the desired configuration. Fig. 9 schematically illustrates an example device 1300 that can be used to implement various embodiments described herein.

For one embodiment, fig. 9 illustrates an exemplary apparatus 1300, which apparatus 1300 may comprise: one or more processors 1302, a system control module (chipset) 1304 coupled to at least one of the processors 1302, system memory 1306 coupled to the system control module 1304, non-volatile memory (NVM)/storage 1308 coupled to the system control module 1304, one or more input/output devices 1310 coupled to the system control module 1304, and a network interface 1312 coupled to the system control module 1306. The system memory 1306 may include: instruction 1362, the instruction 1362 executable by the one or more processors 1302.

Processor 1302 may include one or more single-core or multi-core processors, and processor 1302 may include any combination of general-purpose processors or special-purpose processors (e.g., graphics processors, application processors, baseband processors, etc.). In some embodiments, the device 1300 can function as a server, a target device, a wireless device, etc., as described in embodiments herein.

In some embodiments, device 1300 may include one or more machine-readable media (e.g., system memory 1306 or NVM/storage 1308) having instructions thereon and one or more processors 1302, which in combination with the one or more machine-readable media, are configured to execute the instructions to implement the modules included in the aforementioned devices to perform the actions described in embodiments of the present application.

System control module 1304 for one embodiment may include any suitable interface controller to provide any suitable interface to at least one of processors 1302 and/or any suitable device or component in communication with system control module 1304.

System control module 1304 for one embodiment may include one or more memory controllers to provide an interface to system memory 1306. The memory controller may be a hardware module, a software module, and/or a firmware module.

System memory 1306 for one embodiment may be used to load and store data and/or instructions 1362. For one embodiment, system memory 1306 may include any suitable volatile memory, such as suitable DRAM (dynamic random access memory). In some embodiments, system memory 1306 may include: double data rate type four synchronous dynamic random access memory (DDR4 SDRAM).

System control module 1304 for one embodiment may include one or more input/output controllers to provide an interface to NVM/storage 1308 and input/output device(s) 1310.

NVM/storage 1308 for one embodiment may be used to store data and/or instructions 1382. NVM/storage 1308 may include any suitable non-volatile memory (e.g., flash memory, etc.) and/or may include any suitable non-volatile storage device(s), e.g., one or more Hard Disk Drives (HDDs), one or more Compact Disc (CD) drives, and/or one or more Digital Versatile Disc (DVD) drives, etc.

NVM/storage 1308 may include storage resources that are physically part of the device on which device 1300 is installed or may be accessible by the device and not necessarily part of the device. For example, the NVM/storage 1308 may be accessed over a network via the network interface 1312 and/or through the input/output devices 1310.

Input/output device(s) 1310 for one embodiment may provide an interface for device 1300 to communicate with any other suitable device, and input/output devices 1310 may include communication components, audio components, sensor components, and so forth.

Network interface 1312 of one embodiment may provide an interface for device 1300 to communicate with one or more networks and/or with any other suitable device, and device 1300 may communicate wirelessly with one or more components of a wireless network according to any of one or more wireless network standards and/or protocols, such as to access a communication standard-based wireless network, such as WiFi, 2G, or 3G, or a combination thereof.

For one embodiment, at least one of the processors 1302 may be packaged together with logic for one or more controllers (e.g., memory controllers) of the system control module 1304. For one embodiment, at least one of the processors 1302 may be packaged together with logic for one or more controllers of the system control module 1304 to form a System In Package (SiP). For one embodiment, at least one of the processors 1302 may be integrated on the same novelty as the logic of one or more controllers of the system control module 1304. For one embodiment, at least one of processors 1302 may be integrated on the same chip with logic for one or more controllers of system control module 1304 to form a system on a chip (SoC).

In various embodiments, device 1300 may include, but is not limited to, a desktop computing device or a computing device such as a mobile computing device (e.g., a laptop computing device, a handheld computing device, a tablet, a netbook, etc.), in various embodiments, device 1300 may have more or fewer components and/or different architectures, for example, in some embodiments, device 1300 may include one or more cameras, a keyboard, a liquid crystal display (L CD) screen (including a touch screen display), a non-volatile memory port, multiple antennas, a graphics chip, an Application Specific Integrated Circuit (ASIC), and a speaker.

Wherein, if the display includes a touch panel, the display screen may be implemented as a touch screen display to receive an input signal from a user. The touch panel includes one or more touch sensors to sense touch, slide, and gestures on the touch panel. The touch sensor may not only sense the boundary of a touch or slide action, but also detect the duration and pressure associated with the touch or slide operation.

The present application also provides a non-transitory readable storage medium, where one or more modules (programs) are stored in the storage medium, and when the one or more modules are applied to a device, the one or more modules may cause the device to execute instructions (instructions) of methods in this application.

Provided in one example is an apparatus comprising: one or more processors; and, instructions in one or more machine-readable media stored thereon, which when executed by the one or more processors, cause the apparatus to perform a method as in embodiments of the present application, which may include: the method shown in fig. 1 or fig. 2 or fig. 3 or fig. 4 or fig. 5 or fig. 6.

One or more machine-readable media are also provided in one example, having instructions stored thereon, which when executed by one or more processors, cause an apparatus to perform a method as in embodiments of the application, which may include: the method shown in fig. 1 or fig. 2 or fig. 3 or fig. 4 or fig. 5 or fig. 6.

The specific manner in which each module performs operations of the apparatus in the above embodiments has been described in detail in the embodiments related to the method, and will not be described in detail here, and reference may be made to part of the description of the method embodiments for relevant points.

Embodiments of the present application are described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the application. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.

These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.

These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.

While preferred embodiments of the present application have been described, additional variations and modifications of these embodiments may occur to those skilled in the art once they learn of the basic inventive concepts. Therefore, it is intended that the appended claims be interpreted as including the preferred embodiment and all such alterations and modifications as fall within the true scope of the embodiments of the application.

Claims

1. A method of data processing, the method comprising:

receiving a request of the intelligent device;

determining a target vehicle corresponding to the request;

2. The method of claim 1, wherein the destination comprises:

obtaining a place according to the position of the intelligent equipment; or

And the commuting place corresponding to the target vehicle.

3. The method of claim 1, wherein the destination comprises: a first destination and a second destination;

4. The method according to any of claims 1 to 3, wherein the status information comprises:

Distance information of the target vehicle to the destination; and/or

5. The method of any of claims 1 to 3, wherein the trajectory data comprises: a plurality of historical tracks corresponding to the destination;

determining state information corresponding to the target vehicle according to the trajectory data corresponding to the target vehicle and the destination information, wherein the determining includes:

determining a target historical track from a plurality of historical tracks corresponding to the destination according to the driving restriction attribute corresponding to the target vehicle and/or the occurrence information of one historical track in the plurality of historical tracks;

and determining the state information corresponding to the target vehicle according to the target historical track.

6. The method of claim 5, wherein determining the corresponding state information of the target vehicle according to the target historical track comprises:

determining a road section of the target vehicle reaching the destination according to the target historical track and first position information corresponding to the target vehicle;

and determining the state information corresponding to the target vehicle according to the road section.

7. The method of claim 6, wherein the determining the corresponding status information of the target vehicle according to the road segment comprises:

and determining time-consuming information of the target vehicle to reach the destination according to the road condition of the road section.

8. The method of claim 4, further comprising:

determining a comparison result between the time consumption information and historical time consumption information;

outputting the comparison result as a feedback result corresponding to the request; and/or determining suggestion information according to the comparison result, and outputting the suggestion information as a feedback result corresponding to the request.

9. The method of any of claims 1 to 3, wherein the trajectory data comprises: a historical track;

determining a destination corresponding to the target vehicle by:

and determining a destination corresponding to the target vehicle from end points in a historical track corresponding to the target vehicle according to the request, and/or time information corresponding to the target vehicle, and/or first position information corresponding to the target vehicle, and/or second position information corresponding to the intelligent device.

10. The method of any one of claims 1 to 3, wherein the form of the feedback result comprises:

a speech form, and/or a text form.

11. A method of data processing, the method comprising:

receiving a request in voice form;

and outputting the feedback result in a voice form.

12. The method of claim 11, wherein the status information comprises:

Distance information of the target vehicle to the destination; and/or

13. The method of claim 12, wherein the feedback comprises:

14. A data processing apparatus, characterized in that the apparatus comprises:

15. A data processing apparatus, characterized in that the apparatus comprises:

a receiving module for receiving a request in a voice form;

a feedback result obtaining module, configured to obtain a feedback result corresponding to the request from the server; the feedback result is obtained according to state information corresponding to a target vehicle, and the state information is obtained according to track data corresponding to the target vehicle and destination information; and

and the feedback result output module is used for outputting the feedback result in a voice form.

16. An apparatus, comprising:

one or more processors; and

one or more machine-readable media having instructions stored thereon that, when executed by the one or more processors, cause the apparatus to perform the method recited by one or more of claims 1-10.

17. One or more machine-readable media having instructions stored thereon, which when executed by one or more processors, cause an apparatus to perform the method recited by one or more of claims 1-10.

18. An apparatus, comprising:

one or more processors; and

one or more machine-readable media having instructions stored thereon that, when executed by the one or more processors, cause the apparatus to perform the method of one or more of claims 11-13.

19. One or more machine-readable media having instructions stored thereon, which when executed by one or more processors, cause an apparatus to perform the method recited by one or more of claims 11-13.