CN113626788A

CN113626788A - Data processing method and system, intelligent security equipment and storage medium

Info

Publication number: CN113626788A
Application number: CN202111189463.3A
Authority: CN
Inventors: 黄燕青; 谢剑; 杨洋
Original assignee: Shanghai Chuangmi Technology Co ltd; Beijing Chuangmizhihui Iot Technology Co ltd
Current assignee: Shanghai Imilab Technology Co Ltd
Priority date: 2021-10-13
Filing date: 2021-10-13
Publication date: 2021-11-09

Abstract

The present disclosure provides a data processing method, a system, an intelligent security device, and a storage medium, wherein the method includes: acquiring behavior habit data of a user and/or sensing signals acquired by at least one sensor; determining a target working mode of the intelligent security equipment based on the behavior habit data and/or the induction signal; determining a target working environment matched with the target working mode; the intelligent security equipment acquires monitoring information in a target working environment in a target working mode; obtaining a first recognition result; under the condition that a first identification result represents that a monitored object exists in the monitoring information, target output data in the target working mode are obtained; and outputting the target output data. According to the method and the device, the functions of the equipment can be greatly enriched, accurate output is guaranteed, and user experience is improved.

Description

Data processing method and system, intelligent security equipment and storage medium

Technical Field

The disclosure relates to the technical field of internet of things, in particular to a data processing method and system, intelligent security equipment and a storage medium.

Background

In the technology of the internet of things, in consideration of the fact that a large number of devices exist in the network of the internet of things, in order to guarantee communication quality, a single function is generally set for each piece of equipment of the internet of things. For increasing user use requirements, the internet of things equipment with limited functions may not meet actual use requirements, and the user experience is poor. In addition, for the internet of things equipment with a data output function, how to ensure accurate output becomes an urgent technical problem to be solved.

Disclosure of Invention

The embodiment of the disclosure provides a data processing method and system, intelligent security equipment and a storage medium, which are used for solving the problems that in the related art, the function of Internet of things equipment is limited, the requirement of a user cannot be met, and the problem that accurate output cannot be achieved.

The technical scheme provided by the embodiment of the disclosure is realized as follows:

the embodiment of the disclosure provides a data processing method, which includes:

acquiring behavior habit data of a user and/or sensing signals acquired by at least one sensor; determining a target working mode of the intelligent security equipment based on the behavior habit data and/or the induction signal; the target working mode is one of at least two working modes which the intelligent security equipment has; determining a target working environment matched with the target working mode; the target working environment is a trusted execution environment TEE or a rich execution environment REE in which the intelligent security equipment can run; the intelligent security equipment acquires monitoring information in the target working environment in the target working mode; obtaining a first identification result, wherein the first identification result is obtained by identifying the monitoring information; under the condition that a first identification result represents that a monitored object exists in the monitoring information, target output data in the target working mode are obtained; and outputting the target output data.

In the above scheme, the at least two working modes include a first working mode and a second working mode, when the target working mode of the intelligent security device is the first working mode, the target working environment matched with the first working mode is a TEE, and the intelligent security device collects monitoring information in the TEE in the first working mode; when the target working mode of the intelligent security equipment is a second working mode, the target working environment matched with the second working mode is REE, and the intelligent security equipment acquires monitoring information in the REE in the second working mode; and the target output data in the first working mode is different from the target output data in the second working mode, and/or the data output effect in the first working mode is different from the data output effect in the second working mode.

In the above scheme, the method further comprises: obtaining an original working mode of the intelligent security equipment; determining whether the target working mode is the same as the original working mode; and if the intelligent security equipment is different, switching the original working mode of the intelligent security equipment to a target working mode.

In the above scheme, the method further comprises: obtaining an original working environment of the intelligent security equipment; determining whether the target working environment is the same as the original working environment; and if the intelligent security equipment is different, switching the original working environment of the intelligent security equipment to the target working environment.

In the above scheme, the target output data is audio data output by the intelligent security device; the audio data output by the intelligent security equipment in a first working mode of the at least two working modes is different from the audio data output by the intelligent security equipment in a second working mode of the at least two working modes; and/or the audio output effect of the intelligent security equipment in the first working mode is different from the audio output effect of the intelligent security equipment in the second working mode.

In the foregoing solution, when the first identification result indicates that the monitored object exists in the monitoring information, the method further includes: obtaining a second identification result, wherein the second identification result represents the identity information of the monitored object; and determining target output data in the target working mode based on the identity information.

In the foregoing solution, the obtaining a second recognition result includes: based on the target information appearing in the monitoring information, carrying out identity recognition on the monitored object appearing in the monitoring information to obtain the identity information of the monitored object; the target information includes at least one of: face images, fingerprint information, voice, iris and eye mask information; and/or receiving or reading the second recognition result.

In the foregoing solution, the identifying a monitored object appearing in the monitoring information based on target information appearing in the monitoring information to obtain identity information of the monitored object includes:

calling a deep neural network model, wherein the deep neural network model obtains physiological characteristic information of a monitored object appearing in the monitoring information based on the target information and identifies the identity of the monitored object based on the physiological characteristic information to obtain the identity information;

and/or, invoking physiological characteristic information stored in the TEE; performing similarity matching on the physiological characteristic information extracted from the target information and the stored physiological characteristic information; and determining the identity information according to the matching result.

In the above scheme, when the identity information of the monitored object is the identity information of N monitored objects appearing in the monitoring information, N is a positive integer greater than or equal to 2; the determining target output data in the target operating mode based on the identity information includes: judging whether the identity information of N monitoring objects appearing in the monitoring information is the identity information of a preset object one by one to obtain a judgment result; under the condition that the judgment result represents that the identity information of the predetermined object and/or the identity information of the non-predetermined object exists in the identity information of the N monitoring objects, the determined target output data is first target output data aiming at the first target object; for a second target object, the determined target output data is second target output data; the first target object is a monitoring object having the identity information of the predetermined object in the monitoring information, and the second target object is a monitoring object not having the identity information of the predetermined object in the monitoring information.

In the above scheme, when the judgment result indicates that the identity information of the predetermined object and the identity information of the non-predetermined object exist in the identity information of the N monitoring objects, the first target output data and the second target output data are sequentially output.

In the foregoing solution, the obtaining of the first recognition result may be implemented by at least one of the following manners: identifying the monitoring information to obtain the first identification result; and receiving or reading the first identification result.

In the foregoing solution, the identifying the monitoring information to obtain the first identification result includes: identifying whether target information exists in the monitoring information, wherein the target information comprises at least one of the following: face images, fingerprint information, voice, iris and eye mask information; and when the target information is identified to be present in the monitoring information, generating a first identification result of the monitored object present in the monitoring information.

The embodiment of the present disclosure further provides an intelligent security device, the intelligent security device includes at least two kinds of working modes, the intelligent security device includes:

the first obtaining unit is used for obtaining behavior habit data of a user and/or sensing signals collected by at least one sensor; the first determining unit is used for determining a target working mode of the intelligent security equipment based on the behavior habit data and/or the induction signal; the second determining unit is used for determining a target working environment matched with the target working mode; the target working environment is a trusted execution environment TEE or a rich execution environment REE in which the intelligent security equipment can run; the intelligent security equipment acquires monitoring information in the target working environment in the target working mode; a second obtaining unit configured to obtain a first recognition result, where the first recognition result is obtained by recognizing the monitoring information; a third obtaining unit, configured to obtain target output data in the target working mode when the first identification result represents that the monitored object exists in the monitoring information; an output unit for outputting the target output data.

In the above scheme, the at least two working modes include a first working mode and a second working mode, when the first determining unit determines that the target working mode is the first working mode, the second determining unit determines that the target working environment matched with the first working mode is a TEE, and the intelligent security device collects monitoring information in the TEE in the first working mode; when the first determining unit determines that the target working mode is the second working mode, the second determining unit determines that the target working environment matched with the second working mode is the REE, and the intelligent security device collects monitoring information in the REE in the second working mode; and the target output data in the first working mode is different from the target output data in the second working mode, and/or the data output effect in the first working mode is different from the data output effect in the second working mode.

In the foregoing scheme, the second obtaining unit is configured to obtain a second identification result, where the second identification result represents identity information of the monitored object; correspondingly, a third obtaining unit is configured to determine target output data in the target operating mode based on the identity information.

In the foregoing solution, the second obtaining unit, in the solution for obtaining the second recognition result, is configured to: based on the target information appearing in the monitoring information, carrying out identity recognition on the monitored object appearing in the monitoring information to obtain the identity information of the monitored object; the target information includes at least one of: face images, fingerprint information, voice, iris and eye mask information; and/or, receiving or reading the second recognition result; the second obtaining unit, in a scheme for obtaining the first recognition result, is configured to: identifying the monitoring information to obtain the first identification result; and/or receiving or reading the first recognition result.

An embodiment of the present disclosure further provides a data processing system, including:

the intelligent security equipment is used for acquiring behavior habit data of a user and/or sensing signals acquired by at least one sensor; determining a target working mode of the intelligent security equipment based on the behavior habit data and/or the induction signal; determining a target working environment matched with the target working mode; the target working environment is a trusted execution environment TEE or a rich execution environment REE in which the intelligent security equipment can run; the intelligent security equipment acquires monitoring information in the target working environment in the target working mode; receiving or reading a first identification result, and acquiring target output data in the target working mode under the condition that the first identification result represents that a monitored object exists in the monitoring information; outputting the target output data; and the service equipment is used for acquiring the monitoring information acquired by the intelligent security equipment, and identifying the monitoring information to obtain a first identification result.

In the above scheme, the service device is further configured to perform identity recognition on a monitored object appearing in the monitoring information based on target information appearing in the monitoring information, so as to obtain identity information of the monitored object; and the intelligent security equipment is used for receiving or reading the identity information and determining target output data in the target working mode based on the identity information.

The embodiment of the present disclosure further provides an intelligent security device, including: one or more processors; a memory communicatively coupled to the one or more processors; one or more computer programs, wherein the one or more computer programs are stored in the memory, and when the one or more computer programs are executed by the smart security device, the smart security device is caused to execute the aforementioned data processing method.

Embodiments of the present disclosure also provide a computer-readable storage medium storing computer instructions, which, when executed on a computer, cause the computer to execute the data processing method as described above.

The technical scheme provided by the embodiment of the disclosure at least comprises the following beneficial effects:

the intelligent security equipment in the embodiment of the disclosure is integrated with an information acquisition function, can work in different working environments, can acquire monitoring information in different working environments, and is suitable for different use requirements. The intelligent security equipment in the embodiment of the disclosure further has at least two working modes, and what mode the intelligent security equipment in the at least two working modes uses as the target working mode can be determined based on behavior habit data of a user and/or sensing signals acquired by the sensor. The working environment of the intelligent security equipment depends on the target working mode of the intelligent security equipment. The scheme for determining the target working mode based on the induction signals and/or the behavior habit data and determining the target working environment based on the target working mode can ensure the determination accuracy of the working mode and the working environment, so that the intelligent security equipment is more suitable for different use requirements. The accurate determination of the working mode and the working environment of the intelligent security equipment can obtain and output accurate data (target output data) to be output when a monitored object appears in the collected monitoring information. Therefore, the intelligent security equipment provided by the embodiment of the disclosure has more functions and is more intelligent, accurate output of data can be realized, increasing actual use requirements of users can be met, and user experience is improved.

Other features and aspects of the present disclosure will become apparent from the following detailed description of exemplary embodiments, which proceeds with reference to the accompanying drawings.

Drawings

Fig. 1 is a schematic diagram of a dual working environment in which an intelligent security device according to an embodiment of the present disclosure operates;

fig. 2 is a first schematic flow chart illustrating an implementation of a data processing method according to an embodiment of the present disclosure;

FIG. 3 is a schematic diagram of a second implementation flow of the data processing method according to the embodiment of the present disclosure;

fig. 4 is a schematic flow chart illustrating an implementation of the data processing method according to the embodiment of the present disclosure;

fig. 5 is a schematic flow chart illustrating an implementation of the data processing method according to the embodiment of the present disclosure;

FIG. 6 is a schematic view of an application scenario according to an embodiment of the present disclosure;

FIG. 7 is a schematic diagram of a deep neural network model according to an embodiment of the present disclosure;

fig. 8 is a schematic structural diagram of the intelligent security device according to the embodiment of the present disclosure;

fig. 9 is a schematic diagram of a hardware configuration of the intelligent security device according to the embodiment of the present disclosure;

fig. 10 is a schematic diagram of a configuration of a data processing system according to an embodiment of the present disclosure.

Detailed Description

The present disclosure will be described in further detail below with reference to the accompanying drawings. In the drawings, like reference numbers can indicate functionally identical or similar elements. While the various aspects of the embodiments are presented in drawings, the drawings are not necessarily drawn to scale unless specifically indicated.

Furthermore, in the following detailed description, numerous specific details are set forth in order to provide a better understanding of the present disclosure. It will be understood by those skilled in the art that the present disclosure may be practiced without some of these specific details. In some instances, methods, means, elements, circuits, etc., that are well known to those skilled in the art have not been described in detail so as not to obscure the present disclosure.

The internet of things equipment in the embodiment of the disclosure can be intelligent security equipment. The intelligent security equipment is integrated with an information acquisition function, and can acquire monitoring information in an intelligent security scene, such as acquiring monitoring information outside the intelligent security equipment. The intelligent security equipment is further integrated with a data output function, the data output function can be an audio output function, a video or image output function, or the combination of the audio output function and the video or image output function. The intelligent security device is provided with a processor, and a Trusted Execution Environment (TEE) and a Rich Execution Environment (REE) can run on the processor. The intelligent security equipment can be accessed to a network constructed in a security environment, such as a home security Internet of things network. When the intelligent security device is in the network, the intelligent security device can communicate with the service device, and the data processing logic of the embodiment of the disclosure can be realized based on the communication between the intelligent security device and the service device. The service device may be any reasonable device, such as a server or a smart phone. Of course, the data processing logic provided by the embodiment of the present disclosure may also be implemented only by the intelligent security device without the participation of the service device.

The intelligent security device of the embodiment of the disclosure is provided with a processor. The processor may be any reasonable module with Processing function, such as a Central Processing Unit (CPU), a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), a Field Programmable Gate Array (FPGA), and so on. As shown in fig. 1, the smart security device of the embodiment of the present disclosure, specifically, a Trusted Execution Environment (TEE) and a Rich Execution Environment (REE) may run on a processor. Behaviors with high requirements on security, such as physiological characteristic comparison (fingerprint comparison), payment behavior, password verification and the like, can be executed in the TEE environment. Routine activities such as shopping, teaching, voice or video communication, etc. may be performed in the REE environment. Generally, TEE is called Secure World and REE is called Normal World. Applications that can be run or used in the TEE are Trusted Applications (TAs). The Application that can be run or used in the REE is a Client Application (CA) or a regular Application. The TA and CA are communicable, communicating through Application Program Interfaces (APIs) provided for them in the REE and TEE. The TEE has its own execution space, that is, there is one operating system in each of the TEE environment and the REE environment, and program execution of the two operating systems implements different environments. The TA and CA may communicate with each other based on two operating systems. Among them, the operating system in the TEE environment has a higher security level than the operating system Rich OS (normal or ordinary operating system) in the REE environment. Software and Hardware resources (such as Hardware Hardware) which can be accessed under the TEE environment are separated from software and Hardware resources which can be accessed under the Rich OS operating system. Illustratively, the storage space used in the TEE environment may be physically isolated from the storage space used in the REE environment. The storage space used in the TEE environment can be used for storing information such as physiological characteristics (such as fingerprints), passwords, keys and the like, which have higher security requirements and need to be used by behaviors, and the information is higher in security because of being stored in the TEE environment. The TEE environment provides a safe execution environment for TA execution, and ensures the confidentiality, integrity and access authority of data. In the starting process, in order to ensure the credibility of the TEE environment, the TEE is verified and kept isolated from the Rich OS in the REE environment during the secure starting process. The applications running on the operating system of the TEE environment are TAs, each TA in the TEE also needs authorization and runs independently of each other, as well as authorization if they need to access each other. Two TAs authorized to have mutual access may communicate via a communication interface. Specific authorization and communication procedures this disclosure is not specifically described.

The intelligent security equipment in the embodiment of the disclosure can simultaneously run two execution/working environments, namely REE and TEE, and can work in the two working environments, such as collecting monitoring information. The intelligent security equipment in the embodiment of the disclosure is provided with or integrated with an information acquisition device for acquiring monitoring information. The intelligent security equipment monitors the environment around the intelligent security equipment by using the information acquisition device to obtain monitoring information. The intelligent security equipment utilizes the information acquisition device to acquire the monitoring information under one of the two working environments at a certain moment, namely the monitoring information is acquired in the two working environments in turn. The intelligent security equipment in the embodiment of the disclosure has at least two working modes. Two modes of operation are exemplified, including a master away mode and a master at home mode. Of course, the work mode can be further refined, such as a master away work mode, a master away vacation mode, a master at home work mode, a master at home rest mode, and the like. The division of the two or more working modes of the intelligent security device may also be any conceivable situation, and details are not specifically described.

If the intelligent security device collects the monitoring information, the intelligent security device collects the monitoring information in the REE or collects the monitoring information (works) in the TEE at the same time. In practical applications, an operating environment corresponding to each operating mode can be configured in advance. Taking the working modes including the owner leaving mode and the owner leaving mode as an example, the monitoring information collection in the TEE working environment in the owner leaving mode and the monitoring information collection in the REE working environment in the owner leaving mode can be configured, and vice versa. Under the condition, the intelligent security equipment collects monitoring information in different working environments in different working modes. The intelligent security equipment comprises a plurality of working modes, wherein the two working modes are mutually independent, the two working environments are physically separated, the monitoring information is acquired in different working environments in different working modes, the acquired monitoring information can not interfere with each other, and therefore data which are acquired based on the monitoring information and need to be output by the intelligent security equipment are not interfered and are more accurate. Taking the working modes including the master away working mode, the master away vacation mode, the master at home working mode and the master at home rest mode as examples, the monitoring information acquisition in the working environment of TEE can be configured in the master away working mode and away vacation mode, and the monitoring information acquisition in the working environment of REE in the master at home rest and at home working mode. It is also possible to configure the collection of the monitoring information in the work environment such as the REE in the host away work mode and away vacation mode, and the collection of the monitoring information in the work environment such as the TEE in the host rest at home and home work mode. Under the condition, the intelligent security equipment can collect monitoring information in corresponding working environments in different working modes. Similar to the two working modes of leaving home and being at home, the monitoring information acquired in the corresponding working environment in each working mode is not interfered with each other under the condition that the working modes are four, so that the output data of the intelligent security equipment is more accurate.

In practical application, each working mode and the working environment corresponding to the working mode configured for each working mode can be recorded into a corresponding relationship. When the system is used, the working environment corresponding to the working mode (target working mode) which needs to be used currently is searched from the recorded corresponding relation, and then the working environment (target working environment) which is matched with the working mode which needs to be used currently can be used.

It should be noted that, in the case where the operation mode includes two types, such a configuration relationship may be preferable: the monitoring information is collected in the work environment of the TEE in the host away mode, and the monitoring information is collected in the work environment of the REE in the host at home mode. In the case where the operation mode includes four, such a configuration relationship may be preferable: the monitoring information collection is performed in a work environment such as TEE in the host away work mode and away vacation mode, and in a work environment such as REE in the host rest and at home work mode. This preferred solution mainly takes into account: in practical application, the subjective consciousness of people is mostly used as the leading factor when the owner is at home, and the intelligent security device is used as the leading factor when the owner leaves home. Compared with the REE working environment in which the intelligent security device operates, the TEE environment is higher in safety, and the monitoring information acquired by the intelligent security device in the TEE working environment in the master leaving mode is better in safety and confidentiality and is not easy to tamper. The data needing to be output is obtained and output according to the monitoring information with better confidentiality and safety, and the accuracy of the data needing to be output can be guaranteed, so that more accurate information is provided for users, the safety and the reliability of the security can be effectively improved through the scheme of the intelligent security equipment, and good use experience is brought to the users.

The following describes data processing logic provided by embodiments of the present disclosure.

Fig. 2 is a first schematic flow chart illustrating an implementation of the data processing method according to the embodiment of the present disclosure. As shown in fig. 2, the method includes:

s201: acquiring behavior habit data of a user and/or sensing signals acquired by at least one sensor;

s202: determining a target working mode of the intelligent security equipment based on the behavior habit data and/or the induction signal;

in S201 to S202, the behavior habit data of the user may be obtained by observing the behavior of the owner by the intelligent security device, or may be obtained by observing the behavior of the owner by the service device. If the behavior of the host is observed by the service device, the intelligent security device reads or receives the behavior habit data from the service device. The at least one sensor may be at least one of a door sensor, an infrared or near infrared sensor, a proximity sensor, and the like. The sensor can be connected with intelligent security equipment, and based on this connection, intelligent security equipment reads or receives the signal that comes from sensor to. Or the sensor is connected with the service equipment, the service equipment reads or receives signals sensed by the sensor, and then the sensing signals are transmitted to the intelligent security equipment. In the embodiment of the disclosure, the intelligent security device can obtain the behavior habit data and/or the sensing signal in real time or at regular time, and determine the target working mode of the intelligent security device based on the obtained sensing signal and/or the behavior habit data. It may also be based on a certain triggering event, which may be any reasonable event that characterizes the user leaving or returning home. Illustratively, the door magnetic sensor detects that the door of the home is changed from the originally closed door to the opened door or that the window is changed from the originally closed door to the opened door. Alternatively, the triggering event may be the arrival of the owner at or away from home time, such as when the time gradually moves from 18 o ' clock to 19 o ' clock, which is typically the time the user arrives at home, and when 19 o ' clock arrives, the behavioural data and/or sensory signals are obtained.

It is understood that the behavioral habit data of the user can be data obtained by observing the behavior of the host for a period of time, for example, 8 o 'clock of the host going out to work and 19 o' clock of the host going home every day, and the period of time from 8 o 'clock to 19 o' clock is usually the state that the host is not at home. Before 8 o 'clock or after 19 o' clock, the owner is in the home state. The scheme for determining the target working mode of the intelligent security equipment based on the behavior habit data of the user by the intelligent security equipment can be as follows: the current time information is obtained, and based on the time information, it is determined whether the master is in the away-from-home mode or the in-home mode. If the current time is 10 points, the master is judged to be in the home mode, and if the current time is 22 points, the master is judged to be in the home mode. Based on the sensing signal sensed by the sensor, the scheme for determining the target working mode of the intelligent security equipment can be as follows: the door magnetic sensor is installed on the door or the window or near the door or the window, the on-off state of the door or the window can be detected, and the intelligent security device can determine whether the owner is at home or not at home according to the on-off state of the door or the window detected by the door magnetic sensor. For example, if the door magnetic sensor detects that the window is open, the smart security device determines that the owner is at home, and if the door magnetic sensor detects that the window is closed, the smart security device determines that the owner is not at home. The infrared or near-infrared sensor can be installed at any reasonable position in the home, such as a living room or a bedroom, because the human body can radiate heat outwards, the intelligent security device can determine whether the owner is at home or not according to whether the infrared or near-infrared sensor detects the heat radiated outwards by the human body. Illustratively, if the infrared or near-infrared sensor does not detect human body heat, it is determined that the owner is not at home; if human body heat is detected, it is determined that the owner is at home. The proximity sensor may be installed at any reasonable place in the home, such as a living room or a bedroom where the owner is often located, and the proximity sensor can detect whether a person is approaching. The intelligent security device can determine whether the owner is at home or not according to the result of whether the proximity sensor detects that a person approaches. Illustratively, the smart security device determines that the owner is at home if the proximity sensor detects the proximity of a person, and determines that the owner is not at home if the proximity sensor detects the proximity of an nobody.

It can be understood that, in the scheme of determining the target working mode of the intelligent security device based on the sensing signal, the target working mode may be determined based on the signal sensed by a single sensor, or the target working mode may be determined based on the signal sensed by two or more sensors. In addition, the target operation mode can be determined only based on the behavior habit data of the user, and can also be determined only based on the induction signal. And the target working mode of the intelligent security equipment can be determined based on the behavior habit data and the induction signal of the user. If the target working mode of the intelligent security equipment is determined based on the behavior habit data of the user and the induction signal, the working mode determined based on the behavior habit data of the user and the working mode determined based on the induction signal are the same working mode, and the same working mode is determined to be the target working mode of the intelligent security equipment. And if the working mode determined based on the behavior habit data of the user is not the same as the working mode determined based on the induction signal, ending the process or re-executing S201-S202.

When the intelligent security device determines that the owner is not at home, the target working mode can be determined to be the owner leaving mode. When the intelligent security device determines that the owner is at home, the target working mode can be determined to be the owner-at-home mode. And determining the target working mode of the intelligent security equipment based on the sensing signal and/or the behavior habit data of the user, so that the determination accuracy of the target working mode can be ensured. The intelligent security device can realize automatic identification of the mode that the owner is at home or away from home, and the intelligence is embodied.

S203: determining a target working environment matched with the target working mode; the target working environment is TEE or REE which can be operated by the intelligent security equipment; the intelligent security equipment acquires monitoring information in the target working environment in the target working mode;

in this step, the working environment corresponding to the working mode that needs to be used currently is searched from the recorded corresponding relationship, and the working environment can be used as the target working environment matched with the working mode that needs to be used currently. Taking the working modes including a first working mode and a second working mode, the first working mode being a master away mode, the second working mode being a master in-home mode as an example, when the target working mode of the intelligent security device is the first working mode, the target working environment matched with the first working mode is a TEE, and the intelligent security device collects monitoring information in the TEE in the first working mode. When the target working mode of the intelligent security equipment is the second working mode, the target working environment matched with the second working mode is REE, and the intelligent security equipment collects monitoring information in the REE in the second working mode.

The intelligent security equipment collects monitoring information in different working environments in different working modes. The collected monitoring information can not be interfered mutually. Compared with the working environment of REE, the security of the TEE environment is higher, and the intelligent security device collects monitoring information in the working environment of TEE in a master leaving mode, so that the security and confidentiality of the monitoring information are better, and the monitoring information is not easy to tamper.

S204: obtaining a first identification result, wherein the first identification result is obtained by identifying the monitoring information;

in this step, the intelligent security device can identify the monitoring information to obtain a first identification result. Or the service equipment receives or reads monitoring information acquired by the intelligent security equipment in a target working environment in a target working mode, and identifies the monitoring information to obtain a first identification result. The intelligent security device reads the first identification result from the service device or receives the first identification result sent from the service device. The scheme for obtaining the first identification result includes that the intelligent security equipment or the service equipment identifies monitoring information: the intelligent security equipment or the service equipment identifies whether target information exists in the monitoring information, wherein the target information comprises at least one of the following information: face image, fingerprint information, voice, iris and eye mask information. And if the target information is identified to be present in the monitoring information, generating a first identification result of the monitored object present in the monitoring information. And if the target information is identified as not present in the monitoring information, generating a first identification result of the monitored object which is not present in the monitoring information.

S205: under the condition that a first identification result represents that a monitored object exists in the monitoring information, target output data in the target working mode are obtained;

s206: outputting the target output data;

in S201~ S206, intelligent security equipment integration has the information acquisition function, and can work in the operational environment of difference, can carry out the collection of monitoring information in the operational environment of difference promptly, is applicable to different user demands. The intelligent security equipment in the embodiment of the disclosure has two or more working modes, and which working mode is used as the target working mode can be determined based on the sensing signal acquired by the sensor and/or the behavior habit data of the user. The intelligent security device in the embodiment of the disclosure is integrated with an information acquisition function, and can acquire monitoring information in different working environments, and the acquisition of the monitoring information in which working environment depends on the target working mode of the intelligent security device. According to the scheme, the determination accuracy of the working mode and the working environment can be guaranteed, so that the intelligent security equipment is more suitable for different use requirements. In addition, when a monitoring object appears in the monitoring information collected from the intelligent security equipment, the data in the working mode of the current intelligent security equipment can be used as the data needing to be output by the intelligent security equipment and output, so that the output of the corresponding data in different working modes is realized, and the safety and the interestingness are reflected. Therefore, the intelligent security equipment provided by the embodiment of the disclosure has more functions, is more intelligent, can realize accurate output, meets the increasing actual use requirements of users, and improves the user experience.

The intelligent security equipment in the embodiment of the disclosure can be any reasonable security equipment, such as an intelligent cat eye, an intelligent door, a safe, a vehicle and the like. Under the condition that intelligent security equipment is intelligent cat eye, intelligent cat eye has the function of gathering monitoring information and output data, can carry out monitoring information's collection in the operational environment of difference, can the accurate mode and the operational environment who confirms self, and accurate acquisition and output target output data, the function of intelligent cat eye can be greatly enriched, compare with the cat eye that has single function in the correlation technique, intelligent cat eye in the embodiment of this disclosure is more intelligent, the function is no longer single, can satisfy growing user's in-service use demand, promote user experience. In S205 to S206, if the first identification result represents that the monitoring object exists in the monitoring information, the target output data set for the target working mode is read and output. Taking the operation mode as the master-at-home mode (second operation mode) and the master-away-from-home mode (first operation mode) as an example, different output data are set for different operation modes, i.e., the target output data in the first operation mode and the target output data in the second operation mode are different. Illustratively, information such as "when the host has a lot of toiletries at home" or "door has opened quickly and requests" is set for the host at home mode to make the smart security device express, instead of the host, that the guest is expected to arrive early on to the monitoring object. The master away mode is set such as "master is not now coming later in the family please" to express a apology. Or the master leaves the home mode to set information of ' the master is busy and slightly please ', etc ' to cause the illusion of the presence of people in the home. If the set information is output in the intelligent security device in an audio form, the intelligent security device is equivalently integrated with an audio output module such as a loudspeaker. The audio data output by the intelligent security device, specifically the audio output module, in the first working mode can be different from the audio data output by the audio output module in the second working mode. If the set information is output in the intelligent security device in a video form, the intelligent security device is equivalently integrated with an image output module such as a display screen. The video data output by the intelligent security device, particularly the display screen, in the first working mode can be different from the video data output by the display screen in the second working mode.

In the embodiment of the disclosure, different data can be output in different working modes, so that the intelligent security device can replace the host to realize real reaction to the visiting guest under the actual condition that the host is at home or not at home, and the intelligence of the intelligent security device is embodied. Aiming at different data output under different working modes, the interestingness and the safety can be improved through different output effects among different data. Different output effects may refer to outputting in different output modes. The output mode comprises an audio output mode and a video output mode. For example, in the host away mode, information "the host is not present at home and will come back later" is output in audio to the monitoring object appearing in the monitoring object to prompt that the monitoring object currently has no person at home. As in the master at home mode, information of "door has opened fast forward" is outputted in the form of a video to the monitoring object appearing in the monitoring object, instead of the master expressing the arrival of the monitoring object which is eagerly welcomed. Different output effects may also refer to the output of data with different audio and/or visual effects. For example, the audio data may be output at different volumes or different sounds, and the data may be output at different image sizes and/or different image output effects. Taking the output data as the audio data as an example, in the host away mode, the intelligent security device can simulate the voice of the host to output the data, such as "the host is not at home and will come again later", so as to increase the interest. Or, the voice of the owner is simulated to output the data 'which position you are' so as to cause the false impression of people in the house and play the aim of driving thieves. If the output data is video data, the different image output effects may be: in one working mode, video data is output in a static mode, for example, data to be output is displayed in a whole manner through one picture. And in another working mode, the video data is output in a dynamic mode, for example, the data needing to be output are sequentially displayed in a dynamic mode.

Of course, it is also possible to set the same data to be output in different operation modes, such as setting information "the host is not convenient to see you for coming later" in both the host at home mode and the host away from home mode. In this case, it is necessary to distinguish whether the owner is at home or not by setting different output effects on the same data. For example, in the host away mode, the smart security device utters a message "the host is not convenient to see you please come later" in the host's voice. In the host at home mode, the information that "the host is not convenient to see you please come later" is spoken in the sound of the machine, so that the interest is increased. In summary, whether different data is output in different operation modes or the same data is output, the data output effect in the first operation mode (e.g., the owner leaving mode) and the data output effect in the second operation mode (e.g., the owner leaving mode) may be different. The output effect can be different no matter the same output mode is adopted for data output under different working modes or different output modes are adopted for data output. For example, in the case that the target output data is audio data, the audio output effect of the smart security device in the first working mode may be different from the audio output effect of the smart security device in the second working mode. In the case that the target output data is video data, the video output effect of the intelligent security device in the first working mode may be different from the video output effect of the intelligent security device in the second working mode, which is described in detail in the foregoing description. Therefore, the intelligent security equipment can output different or same data in different working modes, or output the same or different data by adopting different output effects, so that the intelligent security equipment adapts to actual use conditions and enriches the functions of the intelligent security equipment.

In the embodiment of the disclosure, the intelligent security equipment can be an intelligent peephole and also can be an intelligent door. Under the condition that intelligent security equipment is intelligent cat eye, intelligent cat eye has the function of gathering monitoring information and output data, can carry out monitoring information's collection in the operational environment of difference, can confirm self working mode and operational environment, and obtain and output target output data, can richen intelligent cat eye's function greatly, make intelligent cat eye more intelligent, the function is no longer single, can satisfy growing user's in-service use demand, promote user experience. The intelligent cat eye has two working modes of home and away of the owner, and the monitoring information is acquired in the working environment of TEE in the away mode of the owner, so that the confidentiality and the safety of the monitoring information can be greatly improved, and the monitoring information is not easily tampered by the outside. Under the condition that the intelligent security device is an intelligent cat eye, a subject executing S201-S206 can be a processor of the intelligent cat eye or an application specially developed for realizing data processing logic of the intelligent cat eye, such as TA in a TEE working environment or CA in a REE working environment. If the TA executes the processes of S201-S206, the safety execution of the TA process can be ensured due to the TEE environment, so that the data processing logic realized by the TA has higher safety and stronger reliability.

It can be understood that the monitoring information collected by the intelligent security equipment can be image information and also can be sound information. In practical applications, the image information includes at least one of face image, eye mask, iris and fingerprint information. The voice information includes a human speech. Based on this, intelligent security equipment integrates or is provided with one of the following types of information acquisition device: image acquisition device, sound collection system and fingerprint collection system. Wherein, information acquisition device can be the camera, and sound collection system can be the microphone, and fingerprint collection device can be the fingerprint collection panel for gather the fingerprint of user to this panel input. If the intelligent security device collects a monitoring picture in a target working environment in a target working mode, the intelligent security device can identify whether at least one of target information such as a human face image, a human eye membrane and an iris of human eyes appears in the monitoring picture, and if the target information appears in the monitoring picture, a first identification result of a monitored object appears in the monitoring information. If the intelligent security device collects the voice information in the target working environment in the target working mode, the intelligent security device can identify whether the voice of a person appears in the voice information, and if the voice of the person appears in the voice information, a first identification result of the monitored object appearing in the monitoring information is generated. If the intelligent security equipment acquires fingerprint information in a target working environment in a target working mode, generating a first identification result of a monitored object in the monitoring information. Any two or three information acquisition devices in the three types can be combined for use, and if the results obtained by using the monitoring information acquired by the combined information acquisition devices are all the monitoring objects existing in the monitoring information, the first identification result of the monitoring objects existing in the monitoring information is generated.

Fig. 3 is a schematic diagram of an implementation flow of the data processing method according to the embodiment of the disclosure. As shown in fig. 3, the method includes:

s301: acquiring behavior habit data of a user and/or sensing signals acquired by at least one sensor;

s302: determining a target working mode of the intelligent security equipment based on the behavior habit data and/or the induction signal;

s303: obtaining an original working mode of the intelligent security equipment;

here, the executing step of obtaining the original working mode of the intelligent security device may also be executed before any step in S301 to S302 or between two steps. The current working mode of the intelligent security equipment is identified.

S304: determining whether the target working mode is the same as the original working mode, if so, switching the original working mode of the intelligent security equipment to the target working mode so that the intelligent security equipment works in the target working mode;

here, it is determined whether the current operating mode of the identified smart security device is the same as the target operating mode determined in S302. If the working modes are different, switching is carried out, and the original working mode is switched to the target working mode. And if the working modes are the same, the working is still carried out according to the target working mode or the original working mode.

For example, taking the two operation modes as examples, the mode can be switched from the master away mode to the master at home mode, or from the master at home mode to the master away mode. Taking the above four operation modes as an example, the operation mode can be switched from any one of the four operation modes to one of the remaining three operation modes.

S305: determining a target working environment matched with a target working mode, so that the intelligent security equipment acquires monitoring information in the target working environment in the target working mode;

s306: obtaining a first identification result, wherein the first identification result is obtained by identifying the monitoring information;

s307: under the condition that a first identification result represents that a monitored object exists in the monitoring information, target output data in the target working mode are obtained;

s308: outputting the target output data;

in S301 to S308, the determination of the working mode to be used may be implemented based on the determination of whether the target working mode and the original working mode are the same working mode, for example, the working mode may be switched at different times, so that the intelligent security device works in the switched working mode to ensure the accuracy of the working mode to be used. The data to be output by the intelligent security equipment is output data in a target working mode, the accuracy of the output data can be ensured by the determination accuracy of the target working mode, correct output is further realized, the usability and the reliability of the intelligent security equipment are improved, and the functions of the intelligent security equipment are more diversified.

For details related to S301 to S308 and the same contents as S201 to S206, please refer to the related description of S201 to S206, and the repeated details are not repeated. Under the condition that the intelligent security device is an intelligent cat eye, a main body executing S301-S308 can be a processor of the intelligent cat eye, or an application specially developed for realizing data processing logic of the intelligent cat eye, such as TA in a TEE working environment or CA in a REE working environment. If the TA executes the processes from S301 to S308, the safety of the data processing logic realized by the TA is higher and the reliability is stronger because the TEE environment can ensure the safe execution of the TA processes.

Fig. 4 is a third schematic flow chart illustrating an implementation process of the data processing method according to the embodiment of the present disclosure. As shown in fig. 4, the method includes:

s401: acquiring behavior habit data of a user and/or sensing signals acquired by at least one sensor;

s402: determining a target working mode of the intelligent security equipment based on the behavior habit data and/or the induction signal;

s403: acquiring an original working mode and an original working environment of the intelligent security equipment;

here, the executing step of obtaining the original working mode of the intelligent security device may also be executed before any step or between two steps of S401 to S402. The method comprises the steps of identifying the current working mode of the intelligent security equipment and identifying the current working environment in which monitoring information is acquired. The step of obtaining the original working environment can also be preceded by any step of determining whether the target working environment and the original working environment are the same scheme.

S404: determining whether the target working mode is the same as the original working mode, if so, switching the original working mode of the intelligent security equipment to the target working mode so that the intelligent security equipment works in the target working mode;

s405: determining a target working environment matched with the target working mode;

s406: determining whether the target working environment is the same as the original working environment; if the intelligent security equipment is different from the target working environment, switching the original working environment of the intelligent security equipment to the target working environment so that the intelligent security equipment acquires monitoring information in the target working environment in the target working mode;

here, it is determined whether the identified working environment in which the monitoring information is currently collected is the same as the target working environment determined in S405. And if the working environment is different, switching to switch the original working environment to the target working environment. And if the monitoring information is in the same working environment, the monitoring information is still acquired according to the target working environment or the original working environment.

For example, taking the two aforementioned operation modes as an example, the collection of monitoring information in the TEE in the owner away mode may be switched to the collection of monitoring information in the REE in the owner at home mode. Or, the monitoring information collection in the REE is switched from the master home mode to the TEE in the master away mode. Taking the above four operation modes as an example, the collection of the monitoring information in the TEE in the host leaving home vacation mode may be switched to the collection of the monitoring information in the REE in the host home operation mode, and vice versa. Or, the monitoring information collection in the REE is switched from the master in the home mode to the TEE in the master away mode, and vice versa.

S407: obtaining a first identification result, wherein the first identification result is obtained by identifying the monitoring information;

s408: under the condition that a first identification result represents that a monitored object exists in the monitoring information, target output data in the target working mode are obtained;

s409: outputting the target output data;

in S401 to S409, the determination of the working mode used by the intelligent security device may be implemented based on the determination of whether the target working mode and the original working mode are the same working mode, for example, the working mode may be switched when different working modes are different. The determination of the working environment where the intelligent security device is located when collecting the monitoring information can also be realized based on the determination of whether the target working environment and the original working environment are the same working environment, for example, the working environment can be switched when different. So as to ensure the accuracy of the working mode and the working environment which need to be used. The accuracy of determining the target working mode and the target working environment can ensure the accuracy of output data, so that correct output is realized, the usability and the reliability of the intelligent security equipment are improved, and the functions of the equipment are increased.

For details related to S401 to S409 and the same contents as S301 to S308, please refer to the related descriptions of S301 to S308, and repeated details are not repeated. Under the condition that the intelligent security device is an intelligent cat eye, a main body executing S401-S409 can be a processor of the intelligent cat eye, or an application specially developed for realizing data processing logic of the intelligent cat eye, such as TA in a TEE working environment or CA in a REE working environment. If the TA executes the processes from S401 to S409, the safety of the data processing logic realized by the TA is higher and the reliability is stronger because the TEE environment can ensure the safe execution of the TA processes.

In the following description with reference to the scenario shown in fig. 6, taking the smart security device 601 as a smart cat eye (disposed on a door) as an example, it is assumed that the time period from 8 o 'clock to 19 o' clock is a state that the owner is not at home. Before 8 o 'clock or after 19 o' clock, the owner is in the home state.

Scene one: the intelligent cat eye regularly obtains time information from the service equipment side, if the obtained time information is 9 points, the owner is not at home under most of the 9 points, and the current working mode which can be used by the intelligent cat eye is determined to be the owner leaving mode. And according to the preset corresponding relation, finding out that the working environment corresponding to the host leaving mode is the TEE, and determining that the monitoring information can be acquired in the TEE at present. The intelligent cat eye acquires monitoring information in the TEE in a master leaving mode by using the information acquisition device, and identifies whether target information exists in the monitoring information or not, if yes, whether a human face exists or not. And if the existing target information is identified, generating a first identification result of the monitored object in the monitoring information. In a case where the first recognition result of the monitored object is present in the generated monitoring information, target output data set for the master away mode "the master does not want to come again at home now" is read and output.

Scene two: the intelligent cat eye regularly obtains time information from the service equipment side, if the obtained time information is 21 points, the owner is known to be at home under the condition of the 21 points most of time based on the recorded user behavior habit data, and the current usable work mode of the intelligent cat eye is determined to be the owner home mode. And according to the preset corresponding relation, finding out that the working environment corresponding to the home mode of the master is the REE, and determining that the monitoring information can be acquired in the REE at present. The intelligent cat eye collects monitoring information in the REE operated by the owner in a home mode by using the information collection device, and identifies whether target information exists in the monitoring information or not, if yes, whether a human face exists or not. And if the existing target information is identified, generating a first identification result of the monitored object in the monitoring information. In the case where the first recognition result of the monitored object is present in the generated monitoring information, target output data "please when the owner has happened to be plentiful" set for the owner in the home mode is read and output.

Scene three: based on the scheme in the first scenario, in a state that the owner leaves home, the smart peep hole reads a signal sensed by the door magnetic sensor, if the smart peep hole obtains that the door is changed from a closed state to an opened state (the owner unlocks into the home) from the signal sensed by the door magnetic sensor, the fact that the owner has arrived home is indicated, and a currently usable work mode of the owner is determined to be an owner home mode. And when the master leaving mode is different from the previously used master leaving mode, the working mode of the self-body is switched from the master leaving mode to the master leaving mode. And according to the preset corresponding relation, finding out that the working environment corresponding to the home mode of the owner is the REE, and the working environment is different from the working environment TEE in which the monitoring information is collected before, and switching the information collection device to the REE for collecting the monitoring information. The smart cat eye switches the acquisition of monitoring information in the TEE from the owner away mode to the acquisition of monitoring information in the REE in the owner at home mode using the information acquisition device. The intelligent cat eye identifies whether target information exists in the monitoring information, and if the target information exists, whether voice or fingerprints of people exist is judged. And if the existing target information is identified, generating a first identification result of the monitored object in the monitoring information. In the case where the first recognition result of the monitored object is present in the generated monitoring information, target output data "when the owner has been at home for a long time" set for the owner in the home mode is read and output.

In the above several scenarios, the target output data may be output in a video form, may also be output in an audio-video form, and may be accompanied by a certain sound effect or visual effect during output.

In the above several scenarios, the smart cat eye can collect monitoring information in different working environments in different working modes, and obtain and output target output data in a target working mode when a monitored object exists in the monitoring information. The intelligent cat eye is integrated with information acquisition and data output functions, and the determination of a target working mode and a target working environment is realized simultaneously, so that data needing to be output is more accurate, and the function of the intelligent cat eye is not single or limited any more. The monitoring information is collected in the working environment of TEE in the host leaving mode, so that the confidentiality and the safety of the monitoring information can be greatly improved, and the monitoring information is not easy to be tampered by the outside. The execution reliability and safety of the data processing logic are improved. The monitoring information is collected in the working environment with higher safety in the host leaving mode, the expectation of the user is met, the functions of the intelligent security equipment are enriched, and the functions of the intelligent security equipment are diversified.

Fig. 5 is a schematic flow chart illustrating an implementation of the data processing method according to the embodiment of the present disclosure. As shown in fig. 5, the method includes:

s501: acquiring behavior habit data of a user and/or sensing signals acquired by at least one sensor;

s502: determining a target working mode of the intelligent security equipment based on the behavior habit data and/or the induction signal;

s503: determining a target working environment matched with the target working mode; the target working environment is TEE or REE which can be operated by the intelligent security equipment; the intelligent security equipment acquires monitoring information in the target working environment in the target working mode;

s504: obtaining a first identification result, wherein the first identification result is obtained by identifying the monitoring information;

s505: obtaining a second identification result, wherein the second identification result represents the identity information of the monitored object;

in this step, the intelligent security device may perform identity recognition on the monitored object appearing in the monitoring information based on the target information appearing in the monitoring information, to obtain a second recognition result. Or the service equipment receives or reads monitoring information acquired by the intelligent security equipment in a target working environment in a target working mode, and performs identity recognition on a monitored object appearing in the monitoring information based on the target information appearing in the monitoring information to obtain a second recognition result. The intelligent security device reads the second identification result from the service device or receives the second identification result sent from the service device. The Identity information of the object appearing in the monitoring information may be an Identity ID (Identity Document), such as a face ID, a fingerprint ID, a voiceprint ID, an eye mask ID, an iris ID, or the like.

S506: determining target output data in the target operating mode based on the identity information;

in practical applications, the identities of monitoring objects appearing in monitoring information are mainly classified into two categories, one category is self-belongings, and the other category is strangers. Based on this, the step is to judge whether the identity information of the monitored object appearing in the monitoring information is the identity information of a predetermined object (self-family person), if so, the monitored object appearing in the monitoring information is determined to be the self-family person, and the first target output data set for the self-family person in the target working mode is obtained and output. If not, the monitoring object appearing in the monitoring information is determined to be a stranger, and second target output data set for the stranger in the target working mode is obtained and output.

In this embodiment, (target) output data corresponding to the identity is set in advance based on different identities of the monitored object in each operating mode. Taking the intelligent security device as an example, the intelligent security device comprises two working modes of a master-at-home mode and a master-away-from-home mode, in the master-away-from-home mode, the output data set for the self-owned people is 'welcome the master to go home' (first target output data), and the output data set for strangers is 'the master is not at home and contacts again' (second target output data). In the home mode, the output data set for the owner is "other family members are looking for you to come back a sonar" (first target output data), and the output data set for strangers is "when the owner has been done a lot" (second target output data). The scheme that the intelligent security equipment determines the output data under different working modes based on the identity information of the monitoring object appearing in the monitoring information is applicable to different use requirements, is equivalent to personifying the intelligent security equipment, can output corresponding data based on different identity objects, brings strong interest, and improves the use experience of users.

S507: outputting the target output data;

here, the target output data may be output by audio, output by video, or output by audio and video. And outputting by adopting different data output effects under different working modes. For details, please refer to the related description, which is not repeated.

In S501 to S507, the data to be output by the intelligent security device (target output data) may depend on the working mode and the identity information of the monitored object appearing in the monitoring information. The monitoring objects with different identities in different working modes have different output data, and the monitoring objects with different identities in the same working mode also have different output data. According to the scheme, the functional diversity of the intelligent security equipment can be embodied, the functions of the intelligent security equipment are not single or limited any more, and good experience is brought to users.

The same contents as those mentioned above in S501-S507 are understood, and repeated descriptions are omitted. Under the condition that the intelligent security device is an intelligent cat eye, a main body executing S501-S507 can be a processor of the intelligent cat eye, or an application specially developed for realizing data processing logic of the intelligent cat eye, such as TA in a TEE working environment or CA in a REE working environment. If the TA executes the processes of S501-S507, the safety execution of the TA process can be ensured due to the TEE environment, so that the data processing logic realized by the TA has higher safety and stronger reliability.

In S505, the intelligent security device or the service device performs identity recognition on the monitored object appearing in the monitoring information based on the target information appearing in the monitoring information, and the scheme for obtaining the identity information of the monitored object can be implemented in at least one of the following two ways:

before the two ways are introduced, it should be noted that in the two ways, it may be only distinguished whether the monitoring object appearing in the monitoring information is a person of his own or a stranger. It is also possible to distinguish not only the own person but also a stranger, and further identify who is among the own persons such as dad or mom in the case where the monitored object is identified as the own person. In the scheme of specifically identifying who is the self-family, setting the output data corresponding to the identity of the monitored object in each operation mode in advance based on the different identity of the monitored object can be further refined for the identity of the monitored object. Illustratively, taking the smart security device as an example of two working modes, namely a home mode and a home mode, in the home mode, the output data set for dad in the family is "welcome dad get home", and the output data set for mom in the family is "welcome mom get home". In the home mode, the output data set for father in the self is "mom and baby are looking for you to come back", and the output data set for mom in the self is "father and baby are looking for you to come back". The scheme can output corresponding data based on the role of the monitored object at home, such as dad or mom, and brings good use experience to the user while increasing the interest.

It should be noted that the master home mode in the embodiment of the present disclosure may be a state where at least one family is at home, and the master away mode may be a state where all families are not at home or a state where all families specify that a family, such as dad, is not at home, and preferably a state where all families are not at home.

Two implementations are described below:

the implementation mode is as follows: calling a deep neural network model, wherein the deep neural network model obtains physiological characteristic information of a monitored object appearing in the monitoring information based on the target information and identifies the identity of the monitored object based on the physiological characteristic information to obtain the identity information;

the deep neural network model may be pre-trained, and the training process may occur in the REE and also in the TEE. The trained deep neural network model may be stored in memory space open for TEE or in memory space open for REE. The memory space opened up for TEE and the memory space opened up for REE are physically separated, e.g. stored in different memories or in different memory addresses of the same memory. When needed, either the TA is called from the memory space opened up for the TEE, or the TA requests the model from a CA in the REE, such as CA1, and receives the model fed back by CA 1. As shown in fig. 7, the deep neural network model generally includes an input layer, a convolutional layer, and an output layer. The number of the convolution layers may be one, or two or more. Further, pooling layers may also be present between convolutional layers for dimensionality reduction of the data to reduce the computational workload of the neurons, which may be one, or two or more. Wherein the input layer is used for receiving the target information. The convolutional layer is used for extracting physiological characteristic information in the target information. The extracted physiological characteristic information is a multi-dimensional matrix with high dimensionality, and the pooling layer is used for reducing the dimensionality of the extracted physiological characteristic information so as to reduce the calculation workload. The output layer is used for predicting whether the identity of the person appearing in the monitoring information is the identity of the person and outputting a prediction result based on the physiological characteristic information extracted from the target information. If the output layer comprises a discriminator, the discriminator is used for predicting the probability that the identity of the person appearing in the monitoring information is the self-family person, and the probability is compared with a set probability threshold value, and the output is carried out according to the comparison result. Illustratively, the probability of predicting the self-family is 0.9, the probability of predicting the self-family is 0.1, the two probability values are respectively compared with a set probability threshold value of 0.85, the probability of 0.9 of the self-family is found to be greater than 0.85, and the output layer outputs a prediction result, namely the person appearing in the monitoring information is the self-family. Or predicting the probability that the identity of the person appearing in the monitoring information is each person in the family, comparing the probability with a set probability threshold value, and outputting according to the comparison result. Illustratively, the probability of predicting dad is 0.2, the probability of predicting mom is 0.7, the probability of predicting child is 0.1, and the probability of predicting mom is greater than a predetermined probability threshold of 0.6, the output layer outputs the prediction result-the identity of the person appearing in the monitoring information is the identity ID of mom. The probability of predicting father is 0.2, the probability of predicting mom is 0.3, the probability of predicting child is 0.1, and all probabilities are less than the probability threshold, then the output layer outputs the prediction result, namely the person appearing in the monitoring information is not a family person or a stranger. Because the deep neural network model has strong robustness and robustness, the accuracy of the identity information identified according to the deep neural network model is higher.

The deep neural network model in the embodiment of the disclosure may be a neural network model capable of recognizing a human face, a neural network model capable of recognizing a fingerprint, a neural network model capable of recognizing a voiceprint, or a neural network model capable of recognizing an eye mask or an iris. And if the monitoring information shows a face image, calling a neural network model capable of identifying the face to identify. And if fingerprint information appears in the monitoring information, calling a neural network model capable of recognizing the fingerprint to perform identity recognition. And if the monitoring information shows voice information, calling a neural network model capable of recognizing the voiceprint to perform identity recognition. And if the eye membrane or iris information appears in the monitoring information, calling a neural network model capable of identifying the eye membrane or iris for identity identification.

The deep neural network model in the embodiments of the present disclosure may be any reasonable model that can identify the user identity, such as a multitasking convolutional neural network (MTCNN), a residual neural network (ResNet), a twin convolutional neural network model, a Convolutional Neural Network (CNN), a deep convolutional network (DNN), and the like. The above model, if any reasonable variation is made on the basis of the model shown in fig. 7, is also within the scope of the embodiments of the present disclosure.

The implementation mode two is as follows: calling physiological characteristic information stored in the TEE; performing similarity matching on the physiological characteristic information extracted from the target information and the stored physiological characteristic information; and determining the identity information according to the matching result.

The face feature, fingerprint feature, voiceprint feature, iris feature, eye mask feature, and the like of each family are stored in advance in a storage space opened for the TEE or the REE, as physiological feature information stored in the TEE. Until use, it is read out from the storage space opened up for the TEE, or the TA requests the physiological characteristic information from a CA in the REE, such as CA1, and receives the physiological characteristic information fed back by CA 1. And extracting physiological characteristic information of people appearing in the monitoring environment from the target information, judging whether the physiological characteristic information appears in the physiological characteristic information read from the storage space, and if so, determining that the monitored object appearing in the monitoring information is a self-owned person. If not, the monitored object which does not appear in the monitoring information is determined to be a stranger. Or, physiological feature information of a person appearing in the monitored environment is extracted from the target information, and the similarity between the extracted physiological feature information and the read physiological feature of the family is judged to be higher than a preset similarity, such as 90%. And if the similarity between the extracted face features and the face features of dad is judged to be higher than 90%, determining that the person appearing in the monitoring information is a self-person and dad, and determining that the identity ID of the person appearing in the monitoring information is the identity ID of dad. And if the similarity between the physiological characteristic information of the person appearing in the monitoring information and the read physiological characteristics of all the family members is smaller than the preset similarity, the person appearing in the monitoring information is considered to be not the family member but a stranger. The method can ensure the identification accuracy of the identity of the person appearing in the monitoring information through the similarity matching.

In an optional embodiment, the identification of the identity information may be performed in the two manners described above at the same time, and it is determined whether the identity information obtained in the two manners is consistent, if so, the process is continuously executed, and if not, the process is ended.

In the foregoing two modes, if the target information is a face image, the extracted physiological features may be face features, eye mask features, and iris features. The face features include contour, color, size, face edge features, and the like. The ophthalmic or iris features include the contour, color, size, edge features, etc. of the ophthalmic or iris. If the target information is a fingerprint image, the extracted physiological characteristics can be the trend, the texture and the like of the fingerprint. If the target information is a sound, the extracted physiology may be voiceprint information such as the frequency and amplitude of the fluctuation of the sound. Because the physiological characteristics of each person have uniqueness, the uniqueness is used for identifying the identity of the person, so that the accuracy of identity identification can be ensured, and further, the functions of the intelligent security equipment are more diversified.

In the two modes, whether the deep neural network model and the physiological characteristic information are stored in the TEE or the REE is set according to specific conditions. If stored in the REE and the execution subject of the data processing logic is the TA, the TA may make a request to the CA in the REE for the model and physiological characteristic information, and continue execution flow if requested to the model or physiological characteristic information. Based on this, the scheme of the embodiment of the present disclosure can be regarded as a data processing scheme implemented based on the interaction between the CA in the REE and the TA in the TEE. The data processing scheme enables the functions of the intelligent security equipment to be more diversified.

In practical application, the monitoring object identified by the intelligent security device in the monitoring information may be a single person, that is, the identity information is single identity information, in addition, the identity information may also be two or more identity information, that is, the identity information appearing in the monitoring information is the identity information of N monitoring objects appearing in the monitoring information, and N is a positive integer greater than or equal to 2. In this case, the aforementioned S506 determining the target output data in the target operation mode based on the identity information may be implemented as follows: judging whether the identity information of N monitoring objects appearing in the monitoring information is the identity information of a preset object one by one to obtain a judgment result; under the condition that the judgment result represents that the identity information of the predetermined object and/or the identity information of the non-predetermined object exists in the identity information of the N monitoring objects, the determined target output data is first target output data aiming at the first target object; for a second target object, the determined target output data is second target output data; the first target object is a monitoring object having the identity information of the predetermined object in the monitoring information, and the second target object is a monitoring object not having the identity information of the predetermined object in the monitoring information. And under the condition that the judgment result represents that the identity information of the preset object and the identity information of the non-preset object exist in the identity information of the N monitoring objects, sequentially outputting the first target output data and the second target output data. According to the scheme, the intelligent security equipment determines the data to be output finally based on the number of the monitoring objects identified in the monitoring information and the judgment of whether each monitoring object is a person of own, so that the corresponding output of the monitoring objects with different identities in different working modes is realized, the actual use requirements are met, and the interestingness is increased.

The foregoing solution can be understood that, for the identity information of N monitoring objects appearing in the monitoring information, whether the identity information of each monitoring object is the identity information of a predetermined object is determined one by one, that is, whether each monitoring object appearing in the monitoring information is a person of its own is determined, and the determining process has the following three determination results. The first judgment result: the N monitoring objects appearing in the monitoring information are all the own, and the first target output data set for the own in the target operation mode in advance is read and output, for example, the information of "welcome owner to go home" set for the own in the master away from home mode is read and output, or the information of "other family waiting for you to go on a dinner" set for the own in the master away from home mode is read and output. The second judgment result: the N monitoring objects appearing in the monitoring information are strangers, and second target output data set for the strangers in the target working mode in advance is read and output, for example, information that a user does not want to come later and set for the strangers in the user leaving mode is read and output; or reads and outputs information of "please wait for the owner to be busy" set for a stranger in the home mode by the owner. The third judgment result: if there are any family members and any strangers among the N monitoring objects, the first target output data set for the family members in the target operation mode and the second target output data set for the strangers may be read and output in sequence. For example, information of "other family members are waiting for you to get a meal" set for the family members by the host in the home mode and information of "please go home following the host" set for strangers are read and sequentially output. Information of "welcome owner to go home" set for the self-owner in the master away mode and information of "please follow the master to the house if you are a friend of the master" set for the stranger are read and output in sequence. The information in the scheme can be output in an audio mode, in a video mode and in an audio-video mode. During output, certain audio and video output effects can be accompanied, and details are described in relevant descriptions and are not repeated.

The scheme of the embodiment of the present disclosure is further explained with reference to the scenario shown in fig. 6.

Scene four: the intelligent cat eye regularly obtains time information from the service equipment side, if the obtained time information is 10 points, the owner is not at home under the condition of 10 points of time most, and the current usable work mode of the intelligent cat eye is determined to be the owner leaving mode. And according to the preset corresponding relation, finding out that the working environment corresponding to the host leaving mode is the TEE, and determining that the monitoring information can be acquired in the TEE at present. The intelligent cat eye acquires monitoring information in the TEE in a master leaving mode by using the information acquisition device, and identifies whether target information exists in the monitoring information or not, if yes, whether a human face exists or not. And if the existing target information is identified, generating a first identification result of the monitored object in the monitoring information. The smart cat eye recognizes the identity information of the monitored object appearing in the monitoring information. If two monitoring objects exist in the monitoring information and are determined to be self-owned based on the identified identity information, the situation that the owner wants to enter the door is indicated, the output data set for the self-owned people in the mode that the owner leaves the home is read, if the output data is welcome to the owner to go home, the output data is output in the form of audio, and meanwhile, the intelligent cat eye displays the word of welcome to the owner to go home. If it is determined that two monitoring objects exist in the monitoring information based on the recognized identity information and both are strangers, the output data set for the strangers in the master away mode is read, such as "the master does not please come later" and the output is performed in the form of audio. If one of the two identified monitoring objects is the self-owner, which indicates that the self-owner wants to enter the door, and the other is a stranger, the output data set for the self-owner in the master leaving mode is read, such as 'welcoming the self-owner to go home', and the output data set for the stranger 'please pay attention to the foot and follow the master to enter the door', and the two pieces of information are sequentially output in an audio mode.

In the application scenario of the disclosure, the smart cat eye acquires the monitoring information in the work environment of the TEE under the host leaving mode, and the security and confidentiality of the monitoring information acquired in the TEE are better and are not easy to be tampered. The data needing to be output are obtained and output according to the monitoring information with confidentiality and safety better, the accuracy of the data needing to be output can be guaranteed, and therefore more accurate information is provided for users.

Scene five: when the owner leaves home, the smart peep hole reads a signal sensed by the door magnetic sensor, if the smart peep hole obtains that the door is changed from a closed state to an opened state (the owner unlocks into the home) from the signal sensed by the door magnetic sensor, the fact that the owner has arrived at the home is indicated, and the current usable work mode of the owner is determined to be the home mode of the owner. And when the master leaving mode is different from the previously used master leaving mode, the working mode of the self-body is switched from the master leaving mode to the master leaving mode. And according to the preset corresponding relation, finding out that the working environment corresponding to the home mode of the owner is the REE, and the working environment is different from the working environment TEE in which the monitoring information is collected before, and switching the information collection device to the REE for collecting the monitoring information. The smart cat eye collects monitoring information in the REE in a home mode of the owner using the information collecting device. The intelligent cat eye identifies whether target information exists in the monitoring information, and if the target information exists, whether voice or fingerprints of people exist is judged. And if the existing target information is identified, generating a first identification result of the monitored object in the monitoring information. Based on the identity information of the monitored object, the smart cat eye recognizes that the person appearing in the monitored information is self and dad, reads and outputs the output data set for the self in the master home mode, such as "daddy goes home". If a person appears in the monitoring information as a stranger, output data "the owner is busy and please a little bit" set for the stranger in the owner's home mode is read and output.

The intelligent cat eye has the above functions, so that the function of the intelligent cat eye is not single any more. In addition, in the data processing logic that this disclosed embodiment provided, can realize switching over simultaneously of working mode and operational environment, utilized these two operational environments of TEE and REE, can carry out the collection of monitoring information under the operational environment of difference for the function of intelligent cat eye is more diversified.

The embodiment of the present disclosure provides an intelligent security device, as shown in fig. 8, the intelligent security device includes two at least working modes, the intelligent security device includes:

a first obtaining unit 801, configured to obtain behavior habit data of a user and/or an induction signal acquired by at least one sensor;

a first determining unit 802, configured to determine a target working mode of the intelligent security device based on the sensing signal and/or the behavior habit data;

a second determining unit 803, configured to determine a target working environment matching the target working mode; the target working environment is a trusted execution environment TEE or a rich execution environment REE in which the intelligent security equipment can run; the intelligent security equipment acquires monitoring information in the target working environment in the target working mode;

a second obtaining unit 804, configured to obtain a first identification result, where the first identification result is obtained by identifying the monitoring information;

a third obtaining unit 805, configured to obtain target output data in the target working mode when the first identification result represents that the monitored object exists in the monitoring information;

an output unit 806, configured to output the target output data.

As an optional mode, the at least two working modes include a first working mode and a second working mode, when the first determining unit 802 determines that the target working mode is the first working mode, the second determining unit determines 803 that the target working environment matched with the first working mode is a TEE, and the intelligent security device collects monitoring information in the TEE in the first working mode; when the first determining unit 802 determines that the target working mode is the second working mode, the second determining unit determines 803 that the target working environment matched with the second working mode is an REE, and the intelligent security device collects monitoring information in the REE in the second working mode; and the target output data in the first working mode is different from the target output data in the second working mode, and/or the data output effect in the first working mode is different from the data output effect in the second working mode.

As an optional manner, the second obtaining unit 804 is configured to obtain a second recognition result, where the second recognition result represents identity information of the monitored object; accordingly, a third obtaining unit 805 is configured to determine target output data in the target operating mode based on the identity information.

As an alternative, the second obtaining unit 802 is configured to, in a scheme for obtaining the second recognition result: based on the target information appearing in the monitoring information, carrying out identity recognition on the monitored object appearing in the monitoring information to obtain the identity information of the monitored object; the target information includes at least one of: face images, fingerprint information, voice, iris and eye mask information; and/or, receiving or reading the second recognition result; the second obtaining unit 802 is configured to, in a scheme for obtaining the first recognition result,: identifying the monitoring information to obtain the first identification result; and/or receiving or reading the first recognition result.

As an alternative, the first determining unit 802 is configured to: obtaining an original working mode of the intelligent security equipment; determining whether the target working mode is the same as the original working mode; and if the intelligent security equipment is different, switching the original working mode of the intelligent security equipment to a target working mode.

As an alternative, the second determining unit 803 is configured to: obtaining an original working environment of the intelligent security equipment; determining whether the target working environment is the same as the original working environment; and if the intelligent security equipment is different, switching the original working environment of the intelligent security equipment to the target working environment.

As an optional mode, the target output data is audio data output by the intelligent security device; the audio data output by the intelligent security equipment in a first working mode of the at least two working modes is different from the audio data output by the intelligent security equipment in a second working mode of the at least two working modes; and/or the audio output effect of the intelligent security equipment in the first working mode is different from the audio output effect of the intelligent security equipment in the second working mode.

As an optional manner, the second obtaining unit 802 is configured to: calling a deep neural network model, wherein the deep neural network model obtains physiological characteristic information of a monitored object appearing in the monitoring information based on the target information and identifies the identity of the monitored object based on the physiological characteristic information to obtain the identity information; and/or, invoking physiological characteristic information stored in the TEE; performing similarity matching on the physiological characteristic information extracted from the target information and the stored physiological characteristic information; and determining the identity information according to the matching result. As an optional mode, when the identity information of the monitored object is the identity information of N monitored objects appearing in the monitoring information, N is a positive integer greater than or equal to 2;

the second obtaining unit 802 is configured to: judging whether the identity information of N monitoring objects appearing in the monitoring information is the identity information of a preset object one by one to obtain a judgment result; the third obtaining unit 805 is configured to: under the condition that the judgment result represents that the identity information of the predetermined object and/or the identity information of the non-predetermined object exists in the identity information of the N monitoring objects, determining target output data as first target output data aiming at the first target object; for a second target object, the determined target output data is second target output data; the first target object is a monitoring object having the identity information of the predetermined object in the monitoring information, and the second target object is a monitoring object not having the identity information of the predetermined object in the monitoring information. The output unit 806 is used to output the first target output data and the second target output data.

As an optional manner, in a case that the identification information of the predetermined object and the identification information of the non-predetermined object exist in the identification information representing the N monitoring objects according to the determination result, the output unit 806 is configured to sequentially output the first target output data and the second target output data.

It should be noted that, in the embodiment of the present disclosure, the division of each functional unit is schematic, and is only one logical functional division, and there may be another division manner in actual implementation. Each functional unit in the embodiments of the present disclosure may be integrated into one processing unit, each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit can be realized in a form of hardware, and can also be realized in a form of a software functional unit.

The integrated unit, if implemented in the form of a software functional unit and sold or used as a stand-alone product, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present disclosure may be embodied in the form of a software product, which is stored in a storage medium and includes several instructions for causing a computer device (which may be a personal computer, a server, a network device, or the like) or a processor (processor) to execute all or part of the steps of the method provided by the embodiments of the present disclosure. And the aforementioned storage medium includes: u disk, removable hard disk, read only memory, random access memory, magnetic or optical disk, etc. for storing program codes.

Fig. 9 is a block diagram of an intelligent security device according to an embodiment of the present disclosure. As shown in fig. 9, the intelligent security device includes: a memory 910 and a processor 920, the memory 910 having stored therein computer programs operable on the processor 920. The number of the memory 910 and the processor 920 may be one or more. The memory 910 may store one or more computer programs that, when executed by the smart security device, cause the smart security device to perform the methods provided by the above-described method embodiments.

This intelligent security equipment still includes: and a communication interface 930 for communicating with an external device to perform data interactive transmission. If the memory 910, the processor 920 and the communication interface 930 are implemented independently, the memory 910, the processor 920 and the communication interface 930 may be connected to each other through a bus and perform communication with each other. The bus may be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, an Extended ISA (EISA) bus, or the like. The bus may be divided into an address bus, a data bus, a control bus, etc. For ease of illustration, only one thick line is shown in FIG. 9, but this does not indicate only one bus or one type of bus. Optionally, in an implementation, if the memory 910, the processor 920 and the communication interface 930 are integrated on a chip, the memory 910, the processor 920 and the communication interface 930 may complete communication with each other through an internal interface.

The embodiment of the present disclosure also provides a computer-readable storage medium, which stores computer instructions, and when the computer instructions are run on a computer, the computer is caused to execute the method provided by the above method embodiment.

The embodiment of the present disclosure further provides a computer program product, where the computer program product is used to store a computer program, and when the computer program is executed by a computer, the computer may implement the method provided by the above method embodiment.

The embodiment of the disclosure also provides a chip, which is coupled with the memory, and is used for implementing the method provided by the embodiment of the method.

It should be understood that the processor may be a Central Processing Unit (CPU), other general purpose processor, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), a Field Programmable Gate Array (FPGA) or other Programmable logic device, discrete Gate or transistor logic, discrete hardware components, etc. A general purpose processor may be a microprocessor or any conventional processor or the like. It is noted that the processor may be a processor supporting an Advanced reduced instruction set machine (ARM) architecture. Further, optionally, the memory may include a read-only memory and a random access memory, and may further include a nonvolatile random access memory. The memory may be either volatile memory or nonvolatile memory, or may include both volatile and nonvolatile memory. The non-volatile Memory may include a Read-Only Memory (ROM), a Programmable ROM (PROM), an Erasable PROM (EPROM), an Electrically Erasable PROM (EEPROM), or a flash Memory. Volatile Memory can include Random Access Memory (RAM), which acts as external cache Memory. By way of example, and not limitation, many forms of RAM are available. For example, Static Random Access Memory (Static RAM, SRAM), Dynamic Random Access Memory (DRAM), Synchronous Dynamic Random Access Memory (SDRAM), Double Data rate Synchronous Dynamic Random Access Memory (DDR SDRAM), Enhanced SDRAM (ESDRAM), SLDRAM (SLDRAM), and Direct RAMBUS RAM (DR RAM).

In the above embodiments, the implementation may be wholly or partly realized by software, hardware, firmware, or any combination thereof. When implemented in software, may be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions. When loaded and executed on a computer, cause the processes or functions described in accordance with the embodiments of the disclosure to occur, in whole or in part. The computer may be a general purpose computer, a special purpose computer, a network of computers, or other programmable device. The computer instructions may be stored on a computer readable storage medium or transmitted from one computer readable storage medium to another, for example, from one website, computer, server, or data center to another website, computer, server, or data center via wire (e.g., coaxial cable, fiber optic, Digital Subscriber Line (DSL)) or wireless (e.g., infrared, bluetooth, microwave, etc.). The computer-readable storage medium can be any available medium that can be accessed by a computer or a data storage device, such as a server, a data center, etc., that includes one or more of the available media. The usable medium may be a magnetic medium (e.g., floppy Disk, hard Disk, magnetic tape), an optical medium (e.g., Digital Versatile Disk (DVD)), or a semiconductor medium (e.g., Solid State Disk (SSD)), among others. Notably, the computer-readable storage media referred to in this disclosure may be non-volatile storage media, in other words, non-transitory storage media.

It will be understood by those skilled in the art that all or part of the steps for implementing the above embodiments may be implemented by hardware, or may be implemented by a program instructing relevant hardware, where the program may be stored in a computer-readable storage medium, and the above-mentioned storage medium may be a read-only memory, a magnetic disk or an optical disk, etc.

An embodiment of the present disclosure further provides a data processing system, as shown in fig. 10, the system includes: intelligent security equipment 1001 and service equipment 1002; wherein the content of the first and second substances,

the intelligent security device 1001 is used for acquiring behavior habit data of a user and/or sensing signals acquired by at least one sensor; determining a target working mode of the intelligent security equipment based on the induction signal and/or the behavior habit data; determining a target working environment matched with the target working mode; the target working environment is a trusted execution environment TEE or a rich execution environment REE in which the intelligent security device 1001 can run; the intelligent security device 1001 collects monitoring information in the target working environment in the target working mode; receiving or reading a first identification result, and acquiring target output data in the target working mode under the condition that the first identification result represents that a monitored object exists in the monitoring information; outputting the target output data;

and the service equipment 1002 is configured to obtain monitoring information acquired by the intelligent security equipment 1001, identify the monitoring information, and obtain a first identification result.

As an optional mode, the service device 1002 is configured to perform identity recognition on a monitored object appearing in the monitoring information based on target information appearing in the monitoring information acquired by the intelligent security device 1001, so as to obtain identity information of the monitored object;

correspondingly, the intelligent security device 1001 is configured to receive or read identity information of a monitored object appearing in the monitoring information, and determine target output data in a target operating mode based on the identity information.

It should be noted that, in the intelligent security device and the data processing system according to the embodiments of the present disclosure, because the principle of solving the problem is similar to the data processing method based on the intelligent security device, the implementation process and the implementation principle of the intelligent security device and the data processing system can be described with reference to the implementation process and the implementation principle of the data processing method based on the intelligent security device, and repeated parts are not described again.

In the description of the embodiments of the present disclosure, reference to the description of the term "one embodiment," "some embodiments," "an example," "a specific example," or "some examples," etc., means that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the present disclosure. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples. Furthermore, various embodiments or examples and features of different embodiments or examples described in this specification can be combined and combined by one skilled in the art without contradiction.

In the description of the embodiments of the present disclosure, "/" indicates an OR meaning, for example, A/B may indicate A or B; "and/or" herein is merely an association describing an associated object, and means that there may be three relationships, e.g., a and/or B, which may mean: a exists alone, A and B exist simultaneously, and B exists alone.

In the description of the embodiments of the present disclosure, the terms "first" and "second" are used for descriptive purposes only and are not to be construed as indicating or implying relative importance or implying any number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature. In the description of the embodiments of the present disclosure, "a plurality" means two or more unless otherwise specified.

The above description is only exemplary of the present disclosure and is not intended to limit the present disclosure, and any modification, equivalent replacement, or improvement made within the spirit and principle of the present disclosure should be included in the scope of the present disclosure.

Claims

1. A data processing method, comprising:

acquiring behavior habit data of a user and/or sensing signals acquired by at least one sensor;

determining a target working mode of the intelligent security equipment based on the behavior habit data and/or the induction signal; the target working mode is one of at least two working modes which the intelligent security equipment has;

determining a target working environment matched with the target working mode; the target working environment is a trusted execution environment TEE or a rich execution environment REE in which the intelligent security equipment can run; the intelligent security equipment acquires monitoring information in the target working environment in the target working mode;

obtaining a first identification result, wherein the first identification result is obtained by identifying the monitoring information;

in case the first recognition result characterizes that the monitored object is present in the monitoring information,

obtaining target output data in the target working mode;

and outputting the target output data.

2. The method of claim 1, wherein the at least two operating modes include a first operating mode and a second operating mode,

when the target working mode of the intelligent security equipment is a first working mode, the target working environment matched with the first working mode is a TEE, and the intelligent security equipment acquires monitoring information in the TEE in the first working mode;

when the target working mode of the intelligent security equipment is a second working mode, the target working environment matched with the second working mode is REE, and the intelligent security equipment acquires monitoring information in the REE in the second working mode;

the target output data in the first working mode is different from the target output data in the second working mode, and/or the data output effect in the first working mode is different from the data output effect in the second working mode.

3. The method of claim 1 or 2, further comprising:

obtaining an original working mode of the intelligent security equipment;

determining whether the target working mode is the same as the original working mode;

and if the intelligent security equipment is different, switching the original working mode of the intelligent security equipment to a target working mode.

4. The method of claim 3, further comprising:

obtaining an original working environment of the intelligent security equipment;

determining whether the target working environment is the same as the original working environment;

and if the intelligent security equipment is different, switching the original working environment of the intelligent security equipment to the target working environment.

5. The method according to claim 1 or 2, wherein the target output data is audio data output by the smart security device;

the audio data output by the intelligent security equipment in a first working mode of the at least two working modes is different from the audio data output by the intelligent security equipment in a second working mode of the at least two working modes;

and or, the audio output effect of the intelligent security equipment in the first working mode is different from the audio output effect of the intelligent security equipment in the second working mode.

6. The method according to claim 1 or 2, wherein in case the first recognition result characterizes the presence of a monitored object in the monitoring information, the method further comprises:

obtaining a second identification result, wherein the second identification result represents the identity information of the monitored object;

and determining target output data in the target working mode based on the identity information.

7. The method of claim 6, wherein obtaining the second recognition result comprises:

based on the target information appearing in the monitoring information, carrying out identity recognition on the monitored object appearing in the monitoring information to obtain the identity information of the monitored object; the target information includes at least one of: face images, fingerprint information, voice, iris and eye mask information;

and or (b) a,

and receiving or reading the second identification result.

8. The method according to claim 7, wherein the identifying a monitored object appearing in the monitoring information based on target information appearing in the monitoring information to obtain the identity information of the monitored object comprises:

and or, calling physiological characteristic information stored in the TEE; performing similarity matching on the physiological characteristic information extracted from the target information and the stored physiological characteristic information; and determining the identity information according to the matching result.

9. The method according to claim 6, wherein when the identity information of the monitored object is the identity information of N monitored objects appearing in the monitoring information, N is a positive integer greater than or equal to 2;

the determining target output data in the target operating mode based on the identity information includes:

judging whether the identity information of N monitoring objects appearing in the monitoring information is the identity information of a preset object one by one to obtain a judgment result;

the judgment result represents that under the condition that the identity information of the predetermined object and/or the identity information of the non-predetermined object exist in the identity information of the N monitoring objects,

for a first target object, determining target output data as first target output data;

for a second target object, the determined target output data is second target output data;

the first target object is a monitoring object having the identity information of the predetermined object in the monitoring information, and the second target object is a monitoring object not having the identity information of the predetermined object in the monitoring information.

10. The method according to claim 9, wherein in the case that the judgment result represents that the identity information of the predetermined object and the identity information of the non-predetermined object exist in the identity information of the N monitoring objects,

and outputting the first target output data and the second target output data in sequence.

11. The method according to claim 1 or 2, wherein the obtaining of the first recognition result is performed by at least one of:

identifying the monitoring information to obtain the first identification result;

and receiving or reading the first identification result.

12. The method of claim 11, wherein the identifying the monitoring information to obtain the first identification result comprises:

identifying whether target information exists in the monitoring information, wherein the target information comprises at least one of the following: face images, fingerprint information, voice, iris and eye mask information;

and when the target information is identified to be present in the monitoring information, generating a first identification result of the monitored object present in the monitoring information.

13. The utility model provides an intelligent security equipment, its characterized in that, intelligent security equipment includes two kinds at least modes of operation, intelligent security equipment includes:

the first obtaining unit is used for obtaining behavior habit data of a user and/or induction signals collected by at least one sensor;

the first determining unit is used for determining a target working mode of the intelligent security equipment based on the behavior habit data and/or the induction signal;

the second determining unit is used for determining a target working environment matched with the target working mode; the target working environment is a trusted execution environment TEE or a rich execution environment REE in which the intelligent security equipment can run; the intelligent security equipment acquires monitoring information in the target working environment in the target working mode;

a second obtaining unit configured to obtain a first recognition result, where the first recognition result is obtained by recognizing the monitoring information;

a third obtaining unit, configured to obtain target output data in the target working mode when the first identification result represents that the monitored object exists in the monitoring information;

an output unit for outputting the target output data.

14. The apparatus of claim 13, wherein the at least two operating modes include a first operating mode and a second operating mode,

when the first determining unit determines that the target working mode is the first working mode, the second determining unit determines that the target working environment matched with the first working mode is a TEE, and the intelligent security equipment collects monitoring information in the TEE in the first working mode;

when the first determining unit determines that the target working mode is the second working mode, the second determining unit determines that the target working environment matched with the second working mode is the REE, and the intelligent security device collects monitoring information in the REE in the second working mode;

15. The apparatus according to claim 13, wherein the second obtaining unit is configured to obtain a second recognition result, where the second recognition result represents identity information of the monitored object;

correspondingly, a third obtaining unit is configured to determine target output data in the target operating mode based on the identity information.

16. The apparatus according to claim 15, wherein the second obtaining unit, in the scheme for obtaining the second recognition result, is configured to:

based on the target information appearing in the monitoring information, carrying out identity recognition on the monitored object appearing in the monitoring information to obtain the identity information of the monitored object; the target information includes at least one of: face images, fingerprint information, voice, iris and eye mask information; and/or, receiving or reading the second recognition result;

the second obtaining unit, in a scheme for obtaining the first recognition result, is configured to: identifying the monitoring information to obtain the first identification result; and/or receiving or reading the first recognition result.

17. A data processing system, comprising:

the intelligent security equipment is used for acquiring behavior habit data of a user and/or sensing signals acquired by at least one sensor; determining a target working mode of the intelligent security equipment based on the behavior habit data and/or the induction signal; the target working mode is one of at least two working modes which the intelligent security equipment has; determining a target working environment matched with the target working mode; the target working environment is a trusted execution environment TEE or a rich execution environment REE in which the intelligent security equipment can run; the intelligent security equipment acquires monitoring information in the target working environment in the target working mode; receiving or reading a first identification result, and acquiring target output data in the target working mode under the condition that the first identification result represents that a monitored object exists in the monitoring information; outputting the target output data;

and the service equipment is used for acquiring the monitoring information acquired by the intelligent security equipment, and identifying the monitoring information to obtain a first identification result.

18. The system according to claim 17, wherein the service device is further configured to perform identity recognition on a monitored object appearing in the monitoring information based on target information appearing in the monitoring information, so as to obtain identity information of the monitored object;

and the intelligent security equipment is used for receiving or reading the identity information and determining target output data in the target working mode based on the identity information.

19. The utility model provides an intelligent security equipment which characterized in that includes:

one or more processors;

a memory communicatively coupled to the one or more processors;

one or more computer programs, wherein the one or more computer programs are stored in the memory, which when executed by the smart security device, cause the smart security device to perform the method of any of claims 1-12.

20. A computer-readable storage medium having stored thereon computer instructions which, when run on a computer, cause the computer to perform the method of any one of claims 1 to 12.