CN114971932A - Artificial intelligence social contact method and system based on apartment house intelligent space - Google Patents
Artificial intelligence social contact method and system based on apartment house intelligent space Download PDFInfo
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Abstract
The invention relates to the technical field of social contact management of apartment residents, and particularly discloses an artificial intelligence social contact method and system based on an intelligent space of an apartment house, wherein the method comprises the steps of generating registration information corresponding to a user; receiving an access request containing account information sent by a user, and comparing and verifying the account information and the registration information; when the account information passes the comparison verification, sending an environment acquisition request to the user, receiving feedback information sent by the user, and determining an environment model according to the feedback information; and establishing a connecting channel among the environment models, acquiring interactive data in real time and transmitting the interactive data based on the connecting channel. The invention identifies the living condition of the user, generates the registration information, filters some irrelevant people, and establishes the connection channel when receiving the social request of the user, thereby building a social platform in a specific group and being convenient for popularization and use.
Description
Technical Field
The invention relates to the technical field of social contact management of apartment residents, in particular to an artificial intelligence social contact method and system based on an intelligent space of an apartment house.
Background
An apartment is a type of apartment, often called a unit building or a residential building, and refers to a living form in which living facilities are equipped but only occupy a part of the building. Generally, the service type apartment is classified into a residential apartment and a service type apartment, and the service type apartment mainly exists in various aspects such as a hotel type apartment, a startup apartment, a youth apartment, a white-collar apartment, and a youth SOHO. The sum of the area of the jacket type building and the area of the jacket type balcony is not more than 60 square meters.
In the current social background, many young tenants in apartments have just graduation and just work, and when the tenants suddenly leave the campus environment, the tenants change from collective life to independent life and often have some social needs; however, the existing younger social needs are mostly realized by means of some apps, the people flow of the apps is large, the human resources are very disordered, it is difficult to build a platform special for students who just graduate, and if any, some false advertisement information is accompanied, so how to provide a safe, convenient and highly directional platform on the existing living framework and meet the social needs of users who just work soon is a technical problem to be solved by the technical scheme of the invention.
Disclosure of Invention
The invention aims to provide an artificial intelligence social method and an artificial intelligence social system based on an apartment house intelligent space, and aims to solve the problems in the background technology.
In order to achieve the purpose, the invention provides the following technical scheme:
an artificial intelligence social method based on an apartment house smart space, the method comprising:
receiving a registration request sent by a user, acquiring the filing information of the user, identifying the filing information, and generating registration information corresponding to the user;
receiving an access request containing account information sent by a user, and comparing and verifying the account information with the registration information;
when the account information passes the comparison verification, sending an environment acquisition request to the user, receiving feedback information sent by the user, and determining an environment model according to the feedback information;
and establishing a connecting channel among the environment models, acquiring interactive data in real time and transmitting the interactive data based on the connecting channel.
As a further scheme of the invention: the step of receiving a registration request sent by a user, acquiring the filing information of the user, identifying the filing information, and generating the registration information corresponding to the user comprises the following steps:
receiving a registration request sent by a user, sending a preset information acquisition template to the user, and acquiring a living class file of the user based on the information acquisition template; the living class file comprises a house purchasing contract and a renting contract;
identifying the content of the living class file, and determining the type of a user according to the content identification result;
and acquiring the identity information of the user according to the user type, and inputting the identity information into the trained registration model to obtain registration information.
As a further scheme of the invention: the step of identifying the content of the residence class file and determining the user type according to the content identification result comprises the following steps:
acquiring label information of the living class file, and acquiring a reference file containing a region mark according to the label information;
comparing the reference file with the living class file, and calculating the utilization rate of the living class file to the reference file;
comparing the utilization rate with a preset utilization rate threshold, and when the utilization rate reaches the preset utilization rate threshold, segmenting the living class file according to the region mark to obtain a sub-region; wherein the sub-region includes a text region and an image region;
and respectively carrying out content identification on the text area and the image area, and determining the user type according to the content identification result.
As a further scheme of the invention: the step of respectively identifying the content of the text area and the image area and determining the user type according to the content identification result comprises the following steps:
carrying out contour recognition on the image area, and calculating parameters of a closed area; the closed area parameters comprise closed area central point position information and closed area size information;
inputting the parameters of the closed area into a trained authenticity verification model to obtain a state label of the living document; the status label includes at least valid and invalid;
when the status label is valid, identifying the content of the text area, and extracting text information;
determining user parameters according to the text information, and determining the user type according to the user parameters; the user parameters comprise user personal information and residence time length information.
As a further scheme of the invention: when the account information passes the comparison verification, sending an environment acquisition request to the user, receiving feedback information sent by the user, and determining an environment model according to the feedback information, wherein the step comprises the following steps of:
when the account information passes the comparison verification, sending an environment acquisition request to a user;
receiving authorization information sent by a user and acquiring environment information; the environment information comprises an environment image and air parameters, the environment image is a panoramic image, and the air parameters at least comprise target gas concentration, wind direction parameters and wind speed parameters; the type of the target gas is a preset limited value;
sending the environment image to a user, receiving a positioning instruction of the user based on the environment image, and determining a target area according to the positioning instruction;
performing content recognition on the target area, and determining the odor type according to the content recognition result and the target gas concentration;
calculating a distance between the target area and a user based on the environment image, determining a scent propagation time according to the distance;
and (5) counting the environmental image, the odor type and the odor propagation time to obtain an environmental model.
As a further scheme of the invention: said calculating a distance between said target area and a user based on said environmental image, the step of determining a scent propagation time from said distance comprising:
carrying out contour recognition on the target area, and determining a feature in the target area;
acquiring the image size and the reference size of the feature, and determining a scale according to the image size and the reference size;
acquiring an image distance between a feature object and a user in the environment image, and calculating an actual distance according to the image distance and the scale;
and reading a wind direction parameter and a wind speed parameter in the air parameters, and calculating the smell propagation time according to the wind speed parameter and the actual distance.
As a further scheme of the invention: the step of establishing a connection channel between the environment models, acquiring interactive data in real time and transmitting the interactive data based on the connection channel comprises the following steps:
receiving a connection request containing connection intention sent by a user, and matching a plurality of users according to the connection intention;
sending a matching success signal to a plurality of users, and receiving connection permission containing a hidden instruction sent by each user;
reading the environment model of each user, and correcting the read environment model based on the hidden command;
and establishing a connection channel between the environment models based on the connection authority, acquiring interactive data in real time and transmitting based on the connection channel.
The technical scheme of the invention also provides an artificial intelligence social system based on the intelligent space of the apartment house, which comprises the following steps:
the registration information generation module is used for receiving a registration request sent by a user, acquiring the record information of the user, identifying the record information and generating registration information corresponding to the user;
the comparison and verification module is used for receiving an access request containing account information sent by a user and comparing and verifying the account information and the registration information;
the environment model acquisition module is used for sending an environment acquisition request to the user when the account information passes the comparison verification, receiving feedback information sent by the user and determining an environment model according to the feedback information;
and the data transmission module is used for establishing a connecting channel between the environment models, acquiring interactive data in real time and transmitting the interactive data based on the connecting channel.
As a further scheme of the invention: the registration information generation module includes:
the file acquisition unit is used for receiving a registration request sent by a user, sending a preset information acquisition template to the user and acquiring the living class file of the user based on the information acquisition template; the living class file comprises a house purchasing contract and a renting contract;
the type determining unit is used for carrying out content identification on the living class file and determining the user type according to the content identification result;
and the information conversion unit is used for acquiring the identity information of the user according to the user type and inputting the identity information into the trained registration model to obtain the registration information.
As a further scheme of the invention: the type determination unit includes:
the reference acquisition subunit is used for acquiring the label information of the living class file and acquiring a reference file containing the area mark according to the label information;
the utilization rate calculating subunit is used for comparing the reference file with the living class file and calculating the utilization rate of the living class file to the reference file;
the file distinguishing subunit is used for comparing the utilization rate with a preset utilization rate threshold, and when the utilization rate reaches the preset utilization rate threshold, segmenting the living type file according to the area mark to obtain a sub-area; wherein the sub-region includes a text region and an image region;
and the processing execution subunit is used for respectively carrying out content identification on the text area and the image area and determining the user type according to the content identification result.
Compared with the prior art, the invention has the beneficial effects that: the invention identifies the living condition of the user, generates the registration information, filters some irrelevant people, and establishes the connection channel when receiving the social request of the user, thereby building a social platform in a specific group and being convenient for popularization and use.
Drawings
In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings used in the description of the embodiments or the prior art will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention.
FIG. 1 is a block flow diagram of an artificial intelligence social method based on an apartment house smart space.
Fig. 2 is a first sub-flow block diagram of an artificial intelligence social method based on an apartment house smart space.
Fig. 3 is a second sub-flow block diagram of an artificial intelligence social method based on an apartment house smart space.
FIG. 4 is a third sub-flow block diagram of an artificial intelligence social method based on an apartment house smart space.
Fig. 5 is a block diagram of a structure of an artificial intelligence social system based on an apartment house smart space.
FIG. 6 is a block diagram of a registration information generation module in an artificial intelligence social system based on an apartment house smart space.
Detailed Description
In order to make the technical problems, technical solutions and advantageous effects to be solved by the present invention more clearly apparent, the present invention is further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
Example 1
Fig. 1 is a block flow diagram of an artificial intelligence social method based on an apartment smart space, and in an embodiment of the present invention, the artificial intelligence social method based on the apartment smart space includes steps S100 to S400:
step S100: receiving a registration request sent by a user, acquiring the record information of the user, identifying the record information, and generating registration information corresponding to the user;
step S100 is a registration process, which is common to most services; the technical scheme of the invention is different in that the requirement on the registration of the user is higher, because the technical scheme of the invention belongs to the social field, the reality is higher than that of the traditional account interaction process, the safety can be effectively ensured by improving the safety, and even if the number of the users is small, the user is not called.
Step S200: receiving an access request containing account information sent by a user, and comparing and verifying the account information and the registration information;
when the registration information is determined and an access request of a user is received, account information needs to be acquired, and whether the account information is correct or not can be judged according to the registration information; this process can be analogized to the traditional account password authentication process.
Step S300: when the account information passes the comparison verification, sending an environment acquisition request to the user, receiving feedback information sent by the user, and determining an environment model according to the feedback information;
when the account information input by the user is correct, an environment acquisition request is sent to the user, the process needs the authority given by the user, the environment acquisition process can be completed by the user, and can also be completed by preset acquisition equipment, wherein the security of the former is higher, and the convenience of the latter is stronger.
Step S400: establishing a connecting channel among the environment models, acquiring interactive data in real time and transmitting the interactive data based on the connecting channel;
each user has an environment model corresponding to the user, and when the user has an interaction demand, the system can establish a connection channel between the environment models only by sending a request, and acquire and transmit interaction data in real time.
Fig. 2 is a block diagram of a first sub-flow of an artificial intelligence social method based on an intelligent space of an apartment house, where the step of receiving a registration request sent by a user, obtaining docketing information of the user, identifying the docketing information, and generating registration information corresponding to the user includes steps S101 to S103:
step S101: receiving a registration request sent by a user, sending a preset information acquisition template to the user, and acquiring a living class file of the user based on the information acquisition template; the living class file comprises a house purchasing contract and a renting contract;
step S102: identifying the content of the living class file, and determining the type of a user according to the content identification result;
step S103: and acquiring the identity information of the user according to the user type, and inputting the identity information into the trained registration model to obtain registration information.
Step S101 to step S103 describe the registration process specifically, first, the living class file of the user needs to be obtained, where the living class file includes a house purchasing contract and a renting contract, and the contracts can guarantee the identity of the user to some extent; then, the type of the user can be determined according to the residence class file, such as a permanent user or a short-renting user; and finally, acquiring the identity information of the user according to the user type, and generating unique registration information according to the identity information.
Further, the step of identifying the content of the housing class file and determining the user type according to the content identification result includes:
acquiring label information of a living class file, and acquiring a reference file containing a region mark according to the label information;
comparing the reference file with the living class file, and calculating the utilization rate of the living class file to the reference file;
comparing the utilization rate with a preset utilization rate threshold, and when the utilization rate reaches the preset utilization rate threshold, segmenting the living class file according to the region mark to obtain a sub-region; wherein the sub-region includes a text region and an image region;
and respectively carrying out content identification on the text area and the image area, and determining the user type according to the content identification result.
The above-mentioned content has described the identification process of the living class file specifically, the living class file mostly has templates, have corresponding reference files, different areas correspond to different content in these reference files, different areas also have special area marks, such as name area, identity information area or stamping area, etc.; the reference file is an unfilled file, and the content in the reference file is mostly included by the living class file, including how much is reflected by the utilization rate; when the utilization rate reaches a preset utilization rate threshold value, the residence file is indicated to have the value of identification, and the residence file is segmented to obtain a text area and an image area; the image area identifies the stamping area, and the text area identifies the character part; wherein the image area may be absent.
Specifically, the step of identifying the content of the text region and the image region respectively and determining the user type according to the content identification result includes:
carrying out contour recognition on the image area, and calculating parameters of a closed area; the closed area parameters comprise closed area central point position information and closed area size information;
inputting the parameters of the closed area into a trained authenticity verification model to obtain a state label of the living document; the status label includes at least valid and invalid;
when the status label is valid, identifying the content of the text area, and extracting text information;
determining user parameters according to the text information, and determining the user type according to the user parameters; the user parameters comprise user personal information and residence time length information.
The above provides a specific identification scheme, the identification process of the image area precedes the identification process of the text information, wherein the parameters of the closed area are the position and the size of the hole in the trademark image. The plurality of holes has a plurality of closed area parameters.
Furthermore, there are many user parameters, and in an example of the technical solution of the present invention, the user parameters mainly include user personal information and living time information, where the user personal information includes age, gender, and the like; the living time information mainly faces the tenant.
Fig. 3 is a second sub-flow block diagram of an artificial intelligence social method based on an apartment house smart space, where when the account information passes comparison and verification, sending an environment acquisition request to a user, receiving feedback information sent by the user, and determining an environment model according to the feedback information includes steps S301 to S306:
step S301: when the account information passes the comparison verification, sending an environment acquisition request to a user;
step S302: receiving authorization information sent by a user and acquiring environment information; the environment information comprises an environment image and air parameters, the environment image is a panoramic image, and the air parameters at least comprise target gas concentration, wind direction parameters and wind speed parameters; the type of the target gas is a preset limited value;
step S303: sending the environment image to a user, receiving a positioning instruction of the user based on the environment image, and determining a target area according to the positioning instruction;
step S304: performing content recognition on the target area, and determining the odor type according to the content recognition result and the target gas concentration;
step S305: calculating a distance between the target area and a user based on the environment image, determining a scent propagation time according to the distance;
step S306: and (5) counting the environmental image, the odor type and the odor propagation time to obtain an environmental model.
The above is the generation process of the environmental model, and it should be noted that the target gas detection process requires related equipment, and is installed on the hardware applied in the present system by default, such as VR equipment; the core of the above content is that related content of odor transmission is added in the traditional image transmission process, a user marks an environment image, the odor is selected, and another party interacting with the user can obtain olfactory experience shared by the user.
Further, the step of calculating a distance between the target area and a user based on the environment image, the step of determining a scent propagation time according to the distance comprises:
carrying out contour recognition on the target area, and determining a feature in the target area;
acquiring the image size and the reference size of the feature, and determining a scale according to the image size and the reference size;
acquiring an image distance between a feature object and a user in the environment image, and calculating an actual distance according to the image distance and the scale;
and reading a wind direction parameter and a wind speed parameter in the air parameters, and calculating the smell propagation time according to the wind speed parameter and the actual distance.
The time information in the odor simulation process is specifically limited, firstly, a conversion relation between an image and reality is determined, and then propagation parameters are determined according to the conversion relation, wherein the propagation parameters comprise direction, speed and distance; finally, the relevant odor simulator is combined according to the transmission parameters.
It is worth mentioning that in the context of the prior art, there are only a limited number of odour types that can be simulated by the odour simulator.
Fig. 4 is a block diagram of a third sub-flow of the artificial intelligence social method based on the smart space of the apartment house, and the step of establishing a connection channel between the environment models, acquiring the interactive data in real time and transmitting the interactive data based on the connection channel includes steps S401 to S404:
step S401: receiving a connection request containing connection intention sent by a user, and matching a plurality of users according to the connection intention;
step S402: sending a matching success signal to a plurality of users, and receiving connection permission containing a hidden instruction sent by each user;
step S403: reading the environment model of each user, and correcting the read environment model based on the hidden instruction;
step S404: and establishing a connection channel between the environment models based on the connection authority, acquiring interactive data in real time and transmitting based on the connection channel.
The channel establishment process is described in detail in steps S401 to S404, it should be noted that the hiding instruction is necessary content, which is an optional item but is selected by most people, and the hidden content may be replaced by some cartoon characters or cartoon environments or may be in a direct non-display manner. It needs to guarantee the virtuality of network socialization.
Example 2
Fig. 5 is a block diagram illustrating a structure of an artificial intelligence social system based on an apartment smart space, in an embodiment of the present invention, the artificial intelligence social system based on the apartment smart space includes:
the registration information generating module 11 is configured to receive a registration request sent by a user, acquire filing information of the user, identify the filing information, and generate registration information corresponding to the user;
the comparison and verification module 12 is configured to receive an access request containing account information sent by a user, and compare and verify the account information and the registration information;
the environment model obtaining module 13 is configured to send an environment obtaining request to the user when the account information passes the comparison verification, receive feedback information sent by the user, and determine an environment model according to the feedback information;
and the data transmission module 14 is used for establishing a connection channel between the environment models, acquiring interactive data in real time and transmitting the interactive data based on the connection channel.
Fig. 6 is a block diagram illustrating a structure of a registration information generation module 11 in an artificial intelligence social system based on an apartment smart space, where the registration information generation module 11 includes:
the file acquisition unit 111 is configured to receive a registration request sent by a user, send a preset information acquisition template to the user, and acquire a living class file of the user based on the information acquisition template; the living class file comprises a house purchasing contract and a renting contract;
a type determining unit 112, configured to perform content identification on the living class file, and determine a user type according to a content identification result;
and the information conversion unit 113 is configured to obtain identity information of the user according to the user type, and input the identity information into the trained registration model to obtain registration information.
Further, the type determining unit 112 includes:
the reference acquisition subunit is used for acquiring label information of the living class file and acquiring a reference file containing a region mark according to the label information;
the utilization rate calculating subunit is used for comparing the reference file with the living class file and calculating the utilization rate of the living class file to the reference file;
the file distinguishing subunit is used for comparing the utilization rate with a preset utilization rate threshold, and when the utilization rate reaches the preset utilization rate threshold, segmenting the living type file according to the area mark to obtain a sub-area; wherein the sub-region includes a text region and an image region;
and the processing execution subunit is used for respectively carrying out content identification on the text area and the image area and determining the user type according to the content identification result.
The functions which can be realized by the artificial intelligence social method based on the intelligent space of the apartment house are all completed by a computer device which comprises one or more processors and one or more memories, wherein at least one program code is stored in the one or more memories, and is loaded and executed by the one or more processors to realize the functions of the artificial intelligence social method based on the intelligent space of the apartment house.
The processor fetches instructions and analyzes the instructions one by one from the memory, then completes corresponding operations according to the instruction requirements, generates a series of control commands, enables all parts of the computer to automatically, continuously and coordinately act to form an organic whole, realizes the input of programs, the input of data, the operation and the output of results, and the arithmetic operation or the logic operation generated in the process is completed by the arithmetic unit; the Memory comprises a Read-Only Memory (ROM) for storing a computer program, and a protection device is arranged outside the Memory.
Illustratively, a computer program can be partitioned into one or more modules, which are stored in memory and executed by a processor to implement the present invention. One or more of the modules may be a series of computer program instruction segments capable of performing certain functions, which are used to describe the execution of the computer program in the terminal device.
Those skilled in the art will appreciate that the above description of the service device is merely exemplary and not limiting of the terminal device, and may include more or less components than those described, or combine certain components, or different components, such as may include input output devices, network access devices, buses, etc.
The Processor may be a Central Processing Unit (CPU), other general purpose Processor, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), an off-the-shelf Programmable Gate Array (FPGA) or other Programmable logic device, discrete Gate or transistor logic, discrete hardware components, etc. The general-purpose processor may be a microprocessor or the processor may be any conventional processor or the like, which is the control center of the terminal equipment and connects the various parts of the entire user terminal using various interfaces and lines.
The memory may be used to store computer programs and/or modules, and the processor may implement various functions of the terminal device by operating or executing the computer programs and/or modules stored in the memory and calling data stored in the memory. The memory mainly comprises a storage program area and a storage data area, wherein the storage program area can store an operating system, application programs required by at least one function (such as an information acquisition template display function, a product information publishing function and the like) and the like; the storage data area may store data created according to the use of the berth-state display system (e.g., product information acquisition templates corresponding to different product types, product information that needs to be issued by different product providers, etc.), and the like. In addition, the memory may include high speed random access memory, and may also include non-volatile memory, such as a hard disk, a memory, a plug-in hard disk, a Smart Media Card (SMC), a Secure Digital (SD) Card, a Flash memory Card (Flash Card), at least one magnetic disk storage device, a Flash memory device, or other volatile solid state storage device.
The terminal device integrated modules/units, if implemented in the form of software functional units and sold or used as separate products, may be stored in a computer readable storage medium. Based on such understanding, all or part of the modules/units in the system according to the above embodiment may be implemented by a computer program, which may be stored in a computer-readable storage medium and used by a processor to implement the functions of the embodiments of the system. Wherein the computer program comprises computer program code, which may be in the form of source code, object code, an executable file or some intermediate form, etc. The computer readable medium may include: any entity or device capable of carrying computer program code, recording medium, U.S. disk, removable hard disk, magnetic disk, optical disk, computer Memory, Read-Only Memory (ROM), Random Access Memory (RAM), electrical carrier wave signals, telecommunications signals, software distribution media, and the like.
It should be noted that, in this document, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other like elements in a process, method, article, or apparatus that comprises the element.
The above description is only a preferred embodiment of the present invention, and not intended to limit the scope of the present invention, and all modifications of equivalent structures and equivalent processes, which are made by using the contents of the present specification and the accompanying drawings, or directly or indirectly applied to other related technical fields, are included in the scope of the present invention.
Claims (10)
1. An artificial intelligence social method based on an apartment house smart space, which is characterized by comprising the following steps:
receiving a registration request sent by a user, acquiring the filing information of the user, identifying the filing information, and generating registration information corresponding to the user;
receiving an access request containing account information sent by a user, and comparing and verifying the account information and the registration information;
when the account information passes the comparison verification, sending an environment acquisition request to the user, receiving feedback information sent by the user, and determining an environment model according to the feedback information;
and establishing a connecting channel among the environment models, acquiring interactive data in real time and transmitting the interactive data based on the connecting channel.
2. The artificial intelligence social method based on the intelligent space of the apartment house as recited in claim 1, wherein the step of receiving a registration request from a user, obtaining docket information of the user, identifying the docket information, and generating registration information corresponding to the user comprises:
receiving a registration request sent by a user, sending a preset information acquisition template to the user, and acquiring a living class file of the user based on the information acquisition template; the living class file comprises a house purchasing contract and a renting contract;
identifying the content of the living class file, and determining the type of a user according to the content identification result;
and acquiring the identity information of the user according to the user type, and inputting the identity information into the trained registration model to obtain registration information.
3. The artificial intelligence social method based on the smart space of the apartment house according to claim 2, wherein the step of performing the content recognition on the living class file and determining the user type according to the content recognition result comprises:
acquiring label information of a living class file, and acquiring a reference file containing a region mark according to the label information;
comparing the reference file with the living class file, and calculating the utilization rate of the living class file to the reference file;
comparing the utilization rate with a preset utilization rate threshold, and when the utilization rate reaches the preset utilization rate threshold, segmenting the living class file according to the region mark to obtain a sub-region; wherein the sub-region includes a text region and an image region;
and respectively carrying out content identification on the text area and the image area, and determining the user type according to the content identification result.
4. The artificial intelligence social method based on the smart space of the apartment house according to claim 3, wherein the content recognition is performed on the text area and the image area, respectively, and the step of determining the user type according to the result of the content recognition comprises:
carrying out contour recognition on the image area, and calculating parameters of a closed area; the closed area parameters comprise closed area central point position information and closed area size information;
inputting the parameters of the closed area into a trained authenticity verification model to obtain a state label of the living document; the status tag includes at least valid and invalid;
when the status label is valid, identifying the content of the text area, and extracting text information;
determining user parameters according to the text information, and determining the user type according to the user parameters; the user parameters comprise user personal information and residence time length information.
5. The artificial intelligence social method based on the smart space of the apartment house according to claim 1, wherein the step of sending an environment acquisition request to the user and receiving feedback information sent by the user when the account information is verified by comparison, and determining the environment model according to the feedback information comprises:
when the account information passes the comparison verification, sending an environment acquisition request to a user;
receiving authorization information sent by a user and acquiring environment information; the environment information comprises an environment image and air parameters, the environment image is a panoramic image, and the air parameters at least comprise target gas concentration, wind direction parameters and wind speed parameters; the type of the target gas is a preset limited value;
sending the environment image to a user, receiving a positioning instruction of the user based on the environment image, and determining a target area according to the positioning instruction;
performing content recognition on the target area, and determining the odor type according to the content recognition result and the target gas concentration;
calculating a distance between the target area and a user based on the environment image, determining a scent propagation time according to the distance;
and (5) counting the environmental image, the odor type and the odor propagation time to obtain an environmental model.
6. The artificial intelligence social method based on the smart space of an apartment house according to claim 5, wherein the calculating of the distance between the target area and the user based on the environment image, the determining of the scent propagation time according to the distance comprises:
carrying out contour recognition on the target area, and determining a feature in the target area;
acquiring the image size and the reference size of the feature, and determining a scale according to the image size and the reference size;
acquiring an image distance between a feature object and a user in the environment image, and calculating an actual distance according to the image distance and the scale;
and reading a wind direction parameter and a wind speed parameter in the air parameters, and calculating the smell propagation time according to the wind speed parameter and the actual distance.
7. The artificial intelligence social method based on the smart space of the apartment house according to claim 6, wherein the step of establishing a connection channel between the environment models, acquiring the interactive data in real time and transmitting the interactive data based on the connection channel comprises:
receiving a connection request containing connection intention sent by a user, and matching a plurality of users according to the connection intention;
sending a matching success signal to a plurality of users, and receiving connection permission containing a hidden instruction sent by each user;
reading the environment model of each user, and correcting the read environment model based on the hidden instruction;
and establishing a connection channel between the environment models based on the connection authority, acquiring interactive data in real time and transmitting based on the connection channel.
8. An artificial intelligence social system based on an apartment house smart space, the system comprising:
the registration information generation module is used for receiving a registration request sent by a user, acquiring the record information of the user, identifying the record information and generating registration information corresponding to the user;
the comparison and verification module is used for receiving an access request containing account information sent by a user and comparing and verifying the account information and the registration information;
the environment model acquisition module is used for sending an environment acquisition request to the user when the account information passes the comparison verification, receiving feedback information sent by the user and determining an environment model according to the feedback information;
and the data transmission module is used for establishing a connecting channel between the environment models, acquiring interactive data in real time and transmitting the interactive data based on the connecting channel.
9. The artificial intelligence social system based on the smart space of an apartment house according to claim 8, wherein the registration information generation module includes:
the file acquisition unit is used for receiving a registration request sent by a user, sending a preset information acquisition template to the user, and acquiring the residence class file of the user based on the information acquisition template; the living class file comprises a house purchasing contract and a renting contract;
the type determining unit is used for carrying out content identification on the living class file and determining the user type according to the content identification result;
and the information conversion unit is used for acquiring the identity information of the user according to the user type and inputting the identity information into the trained registration model to obtain the registration information.
10. The artificial intelligence social system based on an apartment-housing smart space as recited in claim 9, wherein the type determination unit includes:
the reference acquisition subunit is used for acquiring the label information of the living class file and acquiring a reference file containing the area mark according to the label information;
the utilization rate calculation subunit is used for comparing the reference file with the living class file and calculating the utilization rate of the living class file to the reference file;
the file distinguishing subunit is used for comparing the utilization rate with a preset utilization rate threshold, and when the utilization rate reaches the preset utilization rate threshold, segmenting the living type file according to the area mark to obtain a sub-area; wherein the sub-region includes a text region and an image region;
and the processing execution subunit is used for respectively carrying out content identification on the text area and the image area and determining the user type according to the content identification result.
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