[go: up one dir, main page]

CN111132139A - Anti-theft control method and intelligent wearable device - Google Patents

Anti-theft control method and intelligent wearable device Download PDF

Info

Publication number
CN111132139A
CN111132139A CN201911289298.1A CN201911289298A CN111132139A CN 111132139 A CN111132139 A CN 111132139A CN 201911289298 A CN201911289298 A CN 201911289298A CN 111132139 A CN111132139 A CN 111132139A
Authority
CN
China
Prior art keywords
data
period
wearable device
user
intelligent wearable
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Granted
Application number
CN201911289298.1A
Other languages
Chinese (zh)
Other versions
CN111132139B (en
Inventor
王玄
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Xian Yep Telecommunication Technology Co Ltd
Original Assignee
Xian Yep Telecommunication Technology Co Ltd
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Xian Yep Telecommunication Technology Co Ltd filed Critical Xian Yep Telecommunication Technology Co Ltd
Priority to CN201911289298.1A priority Critical patent/CN111132139B/en
Publication of CN111132139A publication Critical patent/CN111132139A/en
Application granted granted Critical
Publication of CN111132139B publication Critical patent/CN111132139B/en
Active legal-status Critical Current
Anticipated expiration legal-status Critical

Links

Images

Classifications

    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W12/00—Security arrangements; Authentication; Protecting privacy or anonymity
    • H04W12/30—Security of mobile devices; Security of mobile applications
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F1/00—Details not covered by groups G06F3/00 - G06F13/00 and G06F21/00
    • G06F1/16—Constructional details or arrangements
    • G06F1/1613—Constructional details or arrangements for portable computers
    • G06F1/163—Wearable computers, e.g. on a belt
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F21/00—Security arrangements for protecting computers, components thereof, programs or data against unauthorised activity
    • G06F21/70—Protecting specific internal or peripheral components, in which the protection of a component leads to protection of the entire computer
    • G06F21/88—Detecting or preventing theft or loss
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W12/00—Security arrangements; Authentication; Protecting privacy or anonymity
    • H04W12/12—Detection or prevention of fraud
    • H04W12/126—Anti-theft arrangements, e.g. protection against subscriber identity module [SIM] cloning
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W12/00—Security arrangements; Authentication; Protecting privacy or anonymity
    • H04W12/60—Context-dependent security
    • H04W12/61—Time-dependent
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02D—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN INFORMATION AND COMMUNICATION TECHNOLOGIES [ICT], I.E. INFORMATION AND COMMUNICATION TECHNOLOGIES AIMING AT THE REDUCTION OF THEIR OWN ENERGY USE
    • Y02D30/00—Reducing energy consumption in communication networks
    • Y02D30/70—Reducing energy consumption in communication networks in wireless communication networks

Landscapes

  • Engineering & Computer Science (AREA)
  • Computer Security & Cryptography (AREA)
  • Computer Hardware Design (AREA)
  • Theoretical Computer Science (AREA)
  • Signal Processing (AREA)
  • Computer Networks & Wireless Communication (AREA)
  • Physics & Mathematics (AREA)
  • General Engineering & Computer Science (AREA)
  • General Physics & Mathematics (AREA)
  • Human Computer Interaction (AREA)
  • Software Systems (AREA)
  • Telephone Function (AREA)
  • Alarm Systems (AREA)

Abstract

The application provides an anti-theft control method and intelligent wearable equipment. According to the anti-theft control method, the current user behavior data are obtained, wherein the current user behavior data comprise user physiological characteristic data in a first period, the user physiological characteristic data comprise at least one item of physiological index detection data, then the current behavior characteristic value is determined according to the received current user behavior data and a preset characteristic value algorithm, the difference value between the current behavior characteristic value and the historical behavior characteristic value is determined, and if the difference value is larger than a preset difference threshold value, an anti-theft control mode of the intelligent wearable device is started. Therefore, the intelligent wearable device can realize anti-theft control through the embedded functional module, the practicability of the intelligent wearable device is improved, and the user experience is improved.

Description

Anti-theft control method and intelligent wearable device
Technical Field
The application relates to the technical field of communication, in particular to an anti-theft control method and intelligent wearable equipment.
Background
With the rapid development of communication technology, intelligent terminals, such as smart phones, smart home appliances, and intelligent wearable devices, have become necessities of life of everyone, and are closely related to daily work and life of people.
As the intelligent terminal is more miniaturized and intelligent, the intelligent terminal also belongs to a high-value product for users. And most of intelligent terminals belong to portable articles, so that the intelligent terminals are small in size and very easy to be stolen or lost manually. If the situation happens, not only economic loss is brought to the user, but also immeasurable threat can be brought to the information or personal safety of the user. It can be seen that how to perform anti-theft control on the intelligent terminal becomes a problem to be faced by current developers. In the prior art, although some smart terminals, such as smart phones, generally have a general platform, anti-theft control may be implemented through software, a touch screen, a camera, and/or a fingerprint.
However, some intelligent terminals, such as intelligent wearable devices, cannot implement anti-theft control by means of software, touch screens, cameras and/or fingerprints due to the limitation of their own architectures.
Disclosure of Invention
The application provides an anti-theft control method and intelligent wearable equipment, which are used for solving the function loss of the intelligent wearable equipment in the aspect of anti-theft control.
In a first aspect, the present application provides an anti-theft control method applied to an intelligent wearable device, including:
acquiring current user behavior data, wherein the current user behavior data comprises user physiological characteristic data in a first period, and the user physiological characteristic data comprises at least one item of physiological index detection data;
determining a current behavior characteristic value according to the current user behavior data and a preset characteristic value algorithm;
determining a difference value between the current behavior characteristic value and a historical behavior characteristic value, wherein the historical behavior characteristic value is determined according to historical user behavior data and the preset characteristic value algorithm, the historical user behavior data comprises user physiological characteristic data in a second period, and the second period comprises the first period;
and if the difference value is greater than a preset difference threshold value, starting an anti-theft control mode.
In one possible design, the current user behavior data further includes environmental characteristic data for the first period, and the historical user behavior data further includes environmental characteristic data for the second period, the environmental characteristic data including at least one item of environmental indicator detection data.
Optionally, the current user behavior data further includes a time identifier, and the time identifier is used to determine the first period and the second period.
In one possible design, the open antitheft control mode includes at least one of:
locking user data, and uploading the user data to a server, wherein the user data is memory data of the intelligent wearable device;
forbidding interactive functions, wherein the interactive functions comprise a communication function and a setting function;
activating a positioning function, wherein the positioning function is used for uploading the current position of the intelligent wearable device to the server;
and sending an alarm instruction to the server, wherein the alarm instruction is used for indicating that the intelligent wearable device is in a lost state.
In one possible design, the anti-theft control method further includes:
receiving an unlocking instruction, wherein the unlocking instruction comprises an unlocking identity;
and if the unlocking identity identification passes the authentication, exiting the anti-theft control mode.
Optionally, the duration corresponding to the second period is an integer multiple of the duration corresponding to the first period.
In a second aspect, the present application provides an intelligent wearable device, including:
the physiological characteristic detection module is used for acquiring user physiological characteristic data in a first period in current user behavior data, wherein the user physiological characteristic data comprises at least one item of physiological index detection data, and sending the current user behavior data to the control module;
the control module is used for determining a current behavior characteristic value according to the current user behavior data and a preset characteristic value algorithm and determining a difference value between the current behavior characteristic value and a historical behavior characteristic value, wherein the historical behavior characteristic value is determined according to historical user behavior data and the preset characteristic value algorithm, the historical user behavior data comprises user physiological characteristic data in a second period, and the second period comprises the first period;
and if the difference value is greater than a preset difference threshold value, the control module is also used for starting an anti-theft control mode.
In one possible design, the physiological characteristic detection module includes: at least one of a motion sensor, a heart rate sensor, a body temperature sensor, a bio-electrical sensor.
Optionally, the current user behavior data further includes environmental characteristic data in the first period, the historical user behavior data further includes environmental characteristic data in the second period, and the environmental characteristic data includes at least one item of environmental index detection data.
In one possible design, the physiological characteristic detection module further includes: at least one of a proximity sensor and an environmental sensor.
In one possible design, the control module is further configured to add a time identifier to the current user behavior data, where the time identifier is used to determine the first period and the second period.
In one possible design, the control mode is further configured to activate the anti-theft control mode, including at least one of:
the control module locks user data, and uploads the user data to a server through a communication module, wherein the user data are memory data of the intelligent wearable device;
the control module disables interactive functions, wherein the interactive functions comprise a communication function and a setting function;
the control module activates a positioning module, and the positioning module positions the current position of the intelligent wearable device and uploads the current position to the server;
the control module sends an alarm instruction to the server through the communication module, and the alarm instruction is used for indicating that the intelligent wearable device is in a lost state.
In one possible design, the control module is further configured to:
receiving an unlocking instruction, wherein the unlocking instruction comprises an unlocking identity;
and if the unlocking identity identification passes the authentication, the intelligent wearable equipment exits the anti-theft control mode.
Optionally, the duration corresponding to the second period is an integer multiple of the duration corresponding to the first period.
Optionally, the communication module includes: at least one of a Wi-Fi module and an NFC module.
Optionally, the positioning module is a GPS positioning module.
The application provides an anti-theft control method and intelligent wearable equipment, wherein the anti-theft control method is applied to the intelligent wearable equipment. The intelligent wearable device acquires current user behavior data through the physiological characteristic detection module, the data comprise user physiological characteristic data in a first period, and sends the current user behavior data to the control module, wherein the user physiological characteristic data comprise at least one item of physiological index detection data. The control module determines a current behavior characteristic value according to the received current user behavior data and a preset characteristic value algorithm, determines a difference value between the current behavior characteristic value and a historical behavior characteristic value, and starts an anti-theft control mode of the intelligent wearable device if the difference value is larger than a preset difference threshold value. The historical behavior characteristic value is determined by the control module according to historical behavior data and a preset characteristic value algorithm, the historical user behavior data comprises user physiological characteristic data in a second period, and the second period comprises a first period. Therefore, the intelligent wearable device can realize anti-theft control through the embedded functional module of the intelligent wearable device, so that the memory data and the user information of the lost intelligent wearable device are not further threatened, and the user can get back the lost intelligent wearable device to provide assistance, so that the practicability of the intelligent wearable device is improved, and the user experience is improved.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present disclosure and together with the description, serve to explain the principles of the disclosure.
Fig. 1 is an application scene diagram of an intelligent wearable device provided in an embodiment of the present application;
fig. 2 is a schematic flowchart of an anti-theft control method according to an embodiment of the present application;
fig. 3 is a schematic flowchart of another anti-theft control method according to an embodiment of the present application;
fig. 4 is a schematic structural diagram of an intelligent wearable device provided in an embodiment of the present application;
fig. 5 is a schematic physical structure diagram of an intelligent wearable device provided in an embodiment of the present application;
fig. 6 is a block diagram of an intelligent wearable device provided in an embodiment of the present application.
With the foregoing drawings in mind, certain embodiments of the disclosure have been shown and described in more detail below. These drawings and written description are not intended to limit the scope of the disclosed concepts in any way, but rather to illustrate the concepts of the disclosure to those skilled in the art by reference to specific embodiments.
Detailed Description
Reference will now be made in detail to the exemplary embodiments, examples of which are illustrated in the accompanying drawings. When the following description refers to the accompanying drawings, like numbers in different drawings represent the same or similar elements unless otherwise indicated. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with the present application. Rather, they are merely examples of methods and apparatus consistent with certain aspects of the present application, as detailed in the appended claims.
The terms "first," "second," "third," "fourth," and the like in the description and in the claims of the present application and in the above-described drawings (if any) are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used is interchangeable under appropriate circumstances such that the embodiments of the application described herein are, for example, capable of operation in sequences other than those illustrated or otherwise described herein. Furthermore, the terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed, but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.
Nowadays, intelligent terminals, such as smart phones, smart home appliances, and smart wearable devices, have become necessities of life for everyone. Due to the characteristics of miniaturization and intellectualization, the intelligent terminal belongs to a high-value product for users. However, most of intelligent terminals belong to portable articles, have small size and are very easy to be stolen or lost manually. If the situation happens, not only economic loss is brought to the user, but also immeasurable threat can be brought to the information or personal safety of the user. It can be seen that how to perform anti-theft control on the intelligent terminal becomes a problem to be faced by current developers. In the prior art, generally, some intelligent terminals, such as smart phones, have a general platform, and therefore, anti-theft control can be often achieved through devices such as software, touch screens, cameras, and/or fingerprints. However, some intelligent terminals, such as intelligent wearable devices, cannot implement anti-theft control by means of software, touch screens, cameras and/or fingerprints due to the limitations of their own architectures.
To solve the above problems in the prior art, the present application provides an anti-theft control method and an intelligent wearable device, wherein the anti-theft control method is applied to the intelligent wearable device. The intelligent wearable device acquires user physiological characteristic data in a first period in the current user behavior data through the physiological characteristic detection module, and sends the current user behavior data to the control module, wherein the user physiological characteristic data comprises at least one item of physiological index detection data. The control module determines a current behavior characteristic value according to the received current user behavior data and a preset characteristic value algorithm, determines a difference value between the current behavior characteristic value and a historical behavior characteristic value, and starts an anti-theft control mode of the intelligent wearable device if the difference value is larger than a preset difference threshold value. The historical behavior characteristic value is determined by the control module according to historical behavior data and a preset characteristic value algorithm, the historical user behavior data comprises user physiological characteristic data in a second period, and the second period comprises a first period. Through the anti-theft control method, the intelligent wearable device can achieve anti-theft control through the existing functions of the intelligent wearable device, the practicability of the intelligent wearable device is improved, and the user experience is further improved.
The technical solution of the present application will be described in detail below with specific examples. The following several specific embodiments may be combined with each other, and details of the same or similar concepts or processes may not be repeated in some embodiments.
Fig. 1 is an application scenario diagram of the intelligent wearable device provided in the embodiment of the present application, as shown in fig. 1, the intelligent wearable device uses an intelligent bracelet 1 as an example, when a user wears the intelligent bracelet 1, the intelligent bracelet 1 can perform anti-theft control through a functional module embedded in the intelligent bracelet 1, for example, the functional module may be a biometric detection module 2 and a control module 3, where the biometric detection module 2 includes various sensors and/or short-distance modules embedded in the intelligent wearable device, and the control module 3 may be a processor. When losing, can protect intelligent wearing equipment's memory data and user information no longer to further receive the threat to can provide more auxiliary information for user's recovery under server 4's the assistance, thereby improved intelligent wearing equipment's practicality, promoted user experience.
It is worth mentioning that the intelligent wearable device in the embodiment of the present application includes, but is not limited to, an intelligent bracelet, an intelligent watch, intelligent glasses, an intelligent accessory, an intelligent garment, and the like, and includes an intelligent terminal including a biometric detection module and a control module.
Fig. 2 is a schematic flow diagram of an anti-theft control method provided in an embodiment of the present application, where the intelligent wearable device can execute the anti-theft control method provided in the present application through a function module embedded in the intelligent wearable device. As shown in fig. 2, the anti-theft control method provided in this embodiment includes:
s201: and acquiring current user behavior data.
The current user behavior data comprises user physiological characteristic data in a first period, and the user physiological characteristic data comprises at least one item of physiological index detection data.
Acquiring current user behavior data, wherein the current user behavior data comprises user physiological characteristic data in a first period, namely acquiring the user physiological characteristic data corresponding to the current moment every interval of the first period duration. The acquired physiological characteristic data of the user comprises at least one item of physiological index detection data, such as at least one item of index detection data of step number, heart rate, body temperature, bioelectricity and the like. It can be understood that, for the intelligent wearable device, the purpose of the present invention is to better sense the external and self information when the user wears the device, and then process the information more efficiently with the assistance of a computer, a network, or even a human, so that the user can realize self-quantification and in-vitro evolution. Therefore, at least one item of physiological index detection data included in the acquired user physiological characteristic data in the embodiment of the present application may be specifically determined according to data that can be detected by various sensors and/or short-distance modules embedded in the corresponding intelligent wearable device. The present embodiment is not limited to this.
The duration of the first period may be factory-set by a person skilled in the art according to performance characteristics, power capacity, usage, and the like of the intelligent wearable device, for example, the smart bracelet may be worn by a user for ten or more hours each time, and the duration of the first period may be set to every several hours, for example, two hours, to this end, the embodiment of the present application is not limited. Optionally, for the intelligent wearable device that can perform the anti-theft control method provided in the embodiment of the present application, the duration of the first period may also be set and adjusted by the user according to the frequency and/or duration of use of the user when using the intelligent wearable device.
And acquiring the current user behavior data by a physiological characteristic detection module embedded in the intelligent wearable device. The physiological characteristic detection module includes but is not limited to at least one of a motion sensor, a heart rate sensor, a body temperature sensor, and a bio-electric sensor. It can be understood that various sensors and/or short-distance modules can be embedded into the intelligent wearable device, and various physiological index detection data of the user can be collected, so that various functions of the intelligent wearable device can be realized, such as an intelligent sports bracelet, the exercise steps of the user can be detected through the motion sensor, and the heart rate data of the user can be detected through the heart rate sensor. Therefore, the behavior data of the current user can be acquired through various physiological characteristic detection modules of the intelligent wearable device.
Optionally, the current user behavior data further includes environmental characteristic data in the first period, and the environmental characteristic data includes at least one item of environmental index detection data.
The current user behavior data acquired by the physiological characteristic detection module of the intelligent wearable device further comprises environmental characteristic data in a first period, namely the environmental characteristic data of the current moment of each interval of the first period duration is acquired, wherein the environmental characteristic data comprises at least one item of environmental index detection data. The method can also be understood as acquiring the environmental characteristic data in the current environment where the user wears the intelligent wearable device. The environmental index is at least one index detection data such as environmental air pressure, environmental brightness, position information, etc. Similar to the physiological characteristic data of the user, the environmental index detection data included in the acquired environmental characteristic data is not limited in the embodiments of the present application.
The environmental characteristic data may be obtained by at least one of a proximity sensor and an environmental sensor further included in the physiological characteristic detection module.
It can be understood that the intelligent wearable device provided by the embodiment of the application can store the current user behavior data acquired every first period of time.
S202: and determining a current behavior characteristic value according to the current user behavior data and a preset characteristic value algorithm.
After the current user behavior data is obtained, the current behavior characteristic value is determined according to the current user behavior data and a preset characteristic value algorithm, namely, the current user behavior data is processed through the preset characteristic value algorithm to determine the current behavior characteristic value.
For example, the first period is T1, and the feature vector P in the following formula (1) can be usedT1Representing current user behavior data, the current user behavior data may be represented as:
PT1＝(λ1,λ2,....λn) (1)
and lambda is the current behavior characteristic value corresponding to each physiological index detection data or each environmental index detection data.
It should be noted that, for some physiological indicators or environmental indicators, the current user behavior data is the current corresponding data, such as the number of steps, in the time interval of the first period, and the current behavior feature value is the total number of steps generated in the time interval of the first period. For some physiological indexes or environmental indexes, multiple data can be acquired within the first period duration, and the current behavior characteristic value is an average value of the multiple data of the index acquired within the first period.
Optionally, with the time unit of day, week and month, the characteristic values of longer periods such as the day behavior characteristic value, the week behavior characteristic value and the month behavior characteristic value can be determined according to the current user behavior data and the preset characteristic value algorithm.
S203: and determining the difference value between the current behavior characteristic value and the historical behavior characteristic value.
The historical behavior characteristic value is determined according to historical user behavior data and a preset characteristic value algorithm, the historical user behavior data comprises user physiological characteristic data in a second period, and the second period comprises a first period.
The historical behavior data comprises the physiological characteristic data of the user in the second period, namely the physiological characteristic data of the user separated by the second period. The historical behavior data may be understood as that, after the current user behavior data of each interval of the first period duration is obtained, the data is stored, because the second period includes the first period, the current user behavior data corresponding to each first period stored in the second period duration is the historical user behavior data.
The implementation principle and effect of determining the historical behavior feature value according to the historical user behavior data and the preset feature value algorithm are similar to the implementation principle and effect of determining the current behavior feature value in step S202, and are not described herein again.
After the current behavior feature value and the historical behavior feature value are determined, a difference value between the two may be calculated.
For example, the difference value is calculated by formula (2), and formula (2) is as follows:
Figure BDA0002316810140000071
wherein, PTiIs the current behavior characteristic value, P ', corresponding to the ith physiological or environmental detection index in the T period'TiThe historical behavior characteristic value corresponding to the same physiological or environmental detection index as the current behavior characteristic value in the T period,
Figure BDA0002316810140000072
is the weight corresponding to the ith physiological or environmental detection index, and Z is a difference value.
It will be appreciated that the T period may be selected to be one of the durations of a day, week, month, etc. The weight can be set according to the physiological and/or environmental detection indexes related to the specific intelligent wearable device, or the user can dynamically adjust the weight according to the daily behavior of wearing the intelligent device, and the comparison is not limited in the embodiment of the application.
S204: and if the difference value is greater than a preset difference threshold value, starting an anti-theft control mode.
After the difference value between the current behavior characteristic value and the historical behavior characteristic value is determined, comparing the relation between the difference value and a preset difference threshold value, if the determined difference value is larger than the preset difference threshold value, indicating that the intelligent wearable device is in a lost state, and the lost state is stolen or lost, at the moment, starting an anti-theft control mode, wherein the anti-theft control mode can be understood as a protection mode of the intelligent wearable device, so that the memory data or user information of the lost intelligent wearable device is not further threatened, and some functions are activated to be found back.
And if the difference value is not greater than the preset difference threshold value, the intelligent wearable device is normal in operation, at the moment, the current behavior data are reserved, and the historical behavior data are cleared, so that the self-adaption of the intelligent terminal device and the user behavior is kept.
The preset difference threshold may be factory set by a technician in the field according to the performance and use of the intelligent wearable device, or dynamically adjusted by a user according to daily activities performed by the user wearing the intelligent wearable device, which is not limited in the embodiment of the present application.
Optionally, in the above embodiment, the current user behavior data further includes a time identifier, and the time identifier is used to determine the first period and the second period.
The current user behavior data further comprises a time identifier, and the time identifier can be understood as adding timestamp information to the current user behavior data when the current user behavior data is obtained, the added timestamp is the current moment when the current user behavior data is obtained, and the timestamp information is the time identifier. And the difference value between the timestamps corresponding to the adjacent current user behavior data is the first period. The difference between the timestamp included in the earliest current user behavior data and the timestamp included in the latest current user behavior data is the second period.
Optionally, the duration corresponding to the second period is an integer multiple of the duration corresponding to the first period, for example, if the duration corresponding to the first period is one hour, the duration corresponding to the second period is two hours, three hours, and so on, even N hours, where N is a positive integer. The duration of the first period and the duration of the second period can be set when the intelligent wearable device leaves a factory, and the user can also dynamically adjust the daily activities of wearing the intelligent wearable device according to the user, so that the embodiment of the application is not limited.
Steps S202 to S204 in this embodiment are executed by a control module of the intelligent terminal device, where the control module may be a processor, and the processor is configured to execute the anti-theft control method in steps S202 to S204.
The anti-theft control method provided by the embodiment is applied to intelligent wearable equipment. The method comprises the steps of firstly, acquiring current user behavior data, wherein the data comprise user physiological characteristic data in a first period, and the user physiological characteristic data comprise at least one item of physiological index detection data. And then determining a current behavior characteristic value according to the received current user behavior data and a preset characteristic value algorithm, determining a difference value between the current behavior characteristic value and the historical behavior characteristic value, and if the difference value is larger than a preset difference threshold value, starting an anti-theft control mode of the intelligent wearable device. The historical behavior characteristic value is determined by the control module according to historical behavior data and a preset characteristic value algorithm, the historical user behavior data comprises user physiological characteristic data in a second period, and the second period comprises a first period. Through the anti-theft control method provided by the embodiment, the intelligent wearable device can realize anti-theft control through the embedded functional module, so that the memory data or the user information of the lost intelligent wearable device is not further threatened, and the user can get back to provide assistance, so that the practicability of the intelligent wearable device is improved, and the user experience is improved.
In one possible design, the anti-theft control mode is enabled, and the anti-theft control mode includes at least one of the following:
s2041: and locking user data, and uploading the user data to a server, wherein the user data is the memory data of the intelligent wearable device.
S2042: and forbidding interactive functions, wherein the interactive functions comprise a communication function and a setting function.
S2043: and activating a positioning function, wherein the positioning function is used for uploading the current position of the intelligent wearable device to a server.
S2044: and sending an alarm instruction to the server, wherein the alarm instruction is used for indicating that the intelligent wearable device is in a lost state.
The contents included in S2041 to S2044 are described below, respectively.
S2041: and locking user data, and uploading the user data to a server, wherein the user data is the memory data of the intelligent wearable device.
After the anti-theft control mode is started, the control module can lock the user data, wherein the user data can be locked to understand that the current user cannot perform any operation on the memory data of the intelligent wearable device, such as viewing, copying, editing and the like. And the communication module of the intelligent terminal device uploads the user data to the server.
S2042: and forbidding interactive functions, wherein the interactive functions comprise a communication function and a setting function.
One of the anti-theft control modes is to disable the interactive function, that is, the control module disables the functions of the intelligent wearable device when the intelligent wearable device is normally used, such as the communication function and the setting function of the intelligent wearable device.
S2043: and activating a positioning function, wherein the positioning function is used for uploading the current position of the intelligent wearable device to a server.
After the anti-theft control module is started, the control module activates the positioning module, the positioning module feeds back the current position of the intelligent wearable device and uploads the current position data to the server, so that the lost accurate current position information of the intelligent wearable device can be timely known in the server corresponding to the intelligent wearable device. Optionally, after activating the positioning function, the positioning function can also upload the current position to the server periodically, so that the server can check the trace of the lost intelligent wearable device.
S2044: and sending an alarm instruction to the server, wherein the alarm instruction is used for indicating that the intelligent wearable device is in a lost state.
After the anti-theft control module is started, the control module sends an alarm instruction to the server through the communication module to prompt that the intelligent wearable device is currently in a lost state, so that a user can timely know that the intelligent wearable device is lost.
Optionally, a plurality of intelligent terminals of the user, such as a smart phone, an intelligent wearable device, a notebook computer, and the like, may share one server, and when sending an alarm instruction to the server, other intelligent terminals of the user sharing one server with the intelligent wearable device may also receive the alarm instruction at the same time, so that the user can know that the current intelligent wearable device is lost in time, and can take an alarm or other measures to find back the lost intelligent wearable device.
It should be noted that the server in the embodiment of the present application corresponds to the smart wearable device, and is only a network platform and/or a cloud server, etc. that an owner of the smart wearable device has a right to operate, for example, iCloud. The Communication module may be a wireless local area network (Wi-Fi) module and/or a Near Field Communication (NFC) module, and the Positioning module may be a Global Positioning System (GPS) Positioning module. It can be understood that the communication module and the positioning module are both embedded functional modules of the intelligent wearable device.
The anti-theft control mode includes, but is not limited to, at least one of the modes described in S2041 to S2044, and a person skilled in the art may set other modes according to specific performance of the smart wearable device, or combine the above modes, to protect memory data or user information of the lost smart wearable device from further threats, and activate some functions to assist the user in finding the lost smart wearable device, which is not limited in the application embodiment.
The anti-theft control mode provided by the embodiment comprises the steps of locking user data and uploading the user data to a server, wherein the user data is memory data of the intelligent wearable device; forbidding interactive functions, wherein the interactive functions comprise a communication function and a setting function; activating a positioning function, wherein the positioning function is used for uploading the current position of the intelligent wearable device to a server; sending an alarm instruction to a server, wherein the alarm instruction is used for indicating that the intelligent wearable device is in a lost state, enabling the stored data or the user information not to be further threatened through a functional module embedded in the intelligent wearable device, and activating some functions to assist the user in finding the lost intelligent wearable device.
On the basis of the above implementation, the method further includes the steps shown in fig. 3 when the lost smart wearable device is retrieved, fig. 3 is a schematic flow diagram of another anti-theft control method provided in the embodiment of the present application, and as shown in fig. 3, the steps include:
s301: and receiving an unlocking instruction.
The unlocking instruction comprises an unlocking identification.
When the intelligent wearing equipment of losing was retrieved, the user can be through unblock instrument and/or network to intelligent wearing equipment input unblock instruction, and wherein, unblock instruction includes unblock identification, and the serial number or the equipment number of unblock identification and intelligent wearing equipment when leaving the factory match in pairs, and intelligent wearing equipment has and only has a serial number or equipment number with sign self. The unlocking instruction is used for an authentication key of the intelligent wearable device, the control module of the intelligent wearable device receives the unlocking instruction, and the unlocking instruction is used for authentication of the intelligent wearable device.
S302: and if the unlocking identity identification passes the authentication, exiting the anti-theft control mode.
When the unlocking identity identification passes the authentication, the control module closes the anti-theft control mode, namely the intelligent wearable device exits the anti-theft control mode and recovers to a normal use state.
According to the anti-theft control method provided by the embodiment, when the lost intelligent wearable device is found back, the user inputs an unlocking instruction to the intelligent wearable device, the unlocking instruction comprises an unlocking identity, the control module of the intelligent wearable device performs authentication according to the unlocking instruction, and when the authentication is passed, the control module closes the anti-theft control mode, the intelligent wearable device exits the anti-theft control mode, and the normal use state is recovered.
Fig. 4 is a schematic structural diagram of an intelligent wearable device provided in an embodiment of the present application. As shown in fig. 4, the intelligent wearable device 400 provided by the present embodiment includes:
the physiological characteristic detection module 401 is configured to obtain user physiological characteristic data in a first period in the current user behavior data, where the user physiological characteristic data includes at least one item of physiological index detection data, and send the current user behavior data to the control module.
The control module 402 is configured to determine a current behavior feature value according to the current user behavior data and a preset feature value algorithm, and determine a difference value between the current behavior feature value and a historical behavior feature value, where the historical behavior feature value is determined according to the historical user behavior data and the preset feature value algorithm, the historical user behavior data includes user physiological feature data in a second period, and the second period includes the first period.
If the difference value is greater than the preset difference threshold, the control module 402 is further configured to start the anti-theft control mode.
Optionally, the duration corresponding to the second period is an integer multiple of the duration corresponding to the first period.
The control module 402 may be the processor 4020 of the smart wearable device 400. Smart wearable device 400 stores data generated in the anti-theft control method, such as the acquired current user behavior data and historical behavior data, through memory 4030 in storage module 403.
The embodiment provides an intelligent wearable device, which first obtains current user behavior data through a physiological characteristic detection module, where the data includes user physiological characteristic data in a first period, and sends the current user behavior data to a control module, where the user physiological characteristic data includes at least one item of physiological index detection data. And then the control module determines a current behavior characteristic value according to the received current user behavior data and a preset characteristic value algorithm, determines a difference value between the current behavior characteristic value and the historical behavior characteristic value, and if the difference value is larger than a preset difference threshold value, the control module starts an anti-theft control mode of the intelligent wearable device. The historical behavior characteristic value is determined by the control module according to historical behavior data and a preset characteristic value algorithm, the historical user behavior data comprises user physiological characteristic data in a second period, and the second period comprises a first period. The intelligent wearing equipment that this embodiment provided can realize anti-theft control through self embedded functional module to make the intelligent wearing equipment's of loss memory data or user information no longer receive the threat further, and give for the user retrieve and provide supplementary, thereby improved intelligent wearing equipment's practicality, promoted user experience.
Referring to fig. 4, the physiological characteristic detection module 401 includes: at least one of a motion sensor 4011, a heart rate sensor 4012, a body temperature sensor 4013, a bio-electrical sensor 4014.
Specifically, the user physiological characteristic data is acquired by at least one of a motion sensor 4011, a heart rate sensor 4012, a body temperature sensor 4013, and a bio-electric sensor 4014.
Optionally, the current user behavior data further includes environmental characteristic data in a first period, and the historical user behavior data further includes environmental characteristic data in a second period, where the environmental characteristic data includes at least one item of environmental index detection data.
With continued reference to fig. 4, the physiological characteristic detection module 401 further includes: at least one of a proximity sensor 4015 and an environmental sensor 4016.
Specifically, the environmental characteristic data is acquired by at least one of the proximity sensor 4015 and the environmental sensor 4016.
It is worth noting that the physiological characteristic detection module 401 includes, but is not limited to, the various sensors described above.
In one possible design, the control module 402 is further configured to add a time identifier to the current user behavior data, where the time identifier is used to determine the first period and the second period.
In one possible design, the control module 402 is further configured to enable the anti-theft control mode, including at least one of:
the control module 402 locks the user data, and uploads the user data to the server through the communication module 404, where the user data is the memory data of the intelligent wearable device 400;
the control module 402 disables interactive functions, including communication functions and setup functions;
the control module 402 activates the positioning module 405, and the positioning module 405 positions the current position of the intelligent wearable device 400 and uploads the current position to the server;
the control module 402 sends an alarm instruction to the server through the communication module 404, where the alarm instruction is used to indicate that the smart wearable device 400 is in a lost state.
It is understood that the communication module 404 and the positioning module 405 are both embedded functional modules of the smart wearable device 400.
The implementation principle and effect of this embodiment are similar to those of the above-mentioned S2041 to S2044, and are not described herein again.
When the smart wearable device is retrieved, optionally, the control module 402 is further configured to:
receiving an unlocking instruction, wherein the unlocking instruction comprises an unlocking identity;
if the unlocking identity authentication is passed, the intelligent wearable device 400 exits the anti-theft control mode.
The implementation principle and effect of this embodiment are similar to those shown in fig. 3, and are not described herein again.
Referring to fig. 4, optionally, the communication module 404 includes, but is not limited to, at least one of a Wi-Fi module 4041 and an NFC module 4042.
Optionally, the positioning module 405 includes, but is not limited to, a GPS positioning module 4051.
Optionally, the server corresponds to the smart wearable device 400, and only the owner of the smart wearable device 400 has the right to operate, such as a network platform and/or a cloud server.
Having described the internal functional modules and the structural schematic of the intelligent wearable device, fig. 5 is an entity structural schematic of the intelligent wearable device provided in the embodiment of the present application, and as shown in fig. 5, the intelligent wearable device 500 includes:
at least one processor 501; and
a memory 502 communicatively coupled to the at least one processor 501; wherein,
the memory 502 stores instructions executable by the at least one processor 501, and the instructions are executed by the at least one processor 501, so that the at least one processor 501 can execute the steps of the anti-theft control method, which can be referred to in the foregoing description of the method embodiments.
Fig. 6 is a block diagram of an intelligent wearable device according to an embodiment of the present application, for example, the intelligent wearable device 600 may be a smart watch, a smart bracelet, smart glasses, a smart accessory, a smart garment, or the like.
As shown in fig. 6, the smart wearable device 600 may include one or more of the following components: a processing component 602, a memory 604, a power component 606, a multimedia component 608, an audio component 610, an input/output (I/O) interface 612, a sensor component 614, and a communication component 616.
The processing component 602 generally controls overall operation of the device 600, such as operations associated with display, telephone calls, data communications, camera operations, and recording operations. The processing component 602 may include one or more processors 620 to execute instructions to perform all or a portion of the steps of the methods described above. Further, the processing component 602 can include one or more modules that facilitate interaction between the processing component 602 and other components. For example, the processing component 602 can include a multimedia module to facilitate interaction between the multimedia component 608 and the processing component 602.
The memory 604 is configured to store various types of data to support operation at the device 600. Examples of such data include instructions for any application or method operating on device 600. The memory 604 may be implemented by any type or combination of volatile or non-volatile memory devices such as Static Random Access Memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, magnetic or optical disks.
A power supply component 606 provides power to the various components of the device 600. The power components 606 may include a power management system, one or more power supplies, and other components associated with generating, managing, and distributing power for the device 600.
The multimedia component 608 includes a screen that provides an output interface between the device 600 and a user. In some embodiments, the screen may include a Liquid Crystal Display (LCD) and a Touch Panel (TP). If the screen includes a touch panel, the screen may be implemented as a touch screen to receive an input signal from a user. The touch panel includes one or more touch sensors to sense touch, slide, and gestures on the touch panel. The touch sensor may not only sense the boundary of a touch or slide action, but also detect the duration and pressure associated with the touch or slide operation.
The audio component 610 is configured to output and/or input audio signals. For example, the audio component 610 includes a Microphone (MIC) configured to receive external audio signals when the device 600 is in an operational mode, such as a call mode, a recording mode, and a voice recognition mode. The received audio signal may further be stored in the memory 604 or transmitted via the communication component 616. In some embodiments, audio component 610 further includes a speaker for outputting audio signals.
The I/O interface 612 provides an interface between the processing component 602 and peripheral interface modules, which may be keyboards, click wheels, buttons, etc. These buttons may include, but are not limited to: a home button, a volume button, a start button, and a lock button.
The sensor component 614 includes one or more sensors for providing status assessment of various aspects of the device 600. For example, the sensor component 614 may include a motion sensor, heart rate sensor, body temperature sensor, bio-electric sensor, etc. to detect physiological characteristic data of the user wearing the smart wearable device 600. Changes in the position of the device 600 or a component of the device 600, the presence or absence of user contact with the device 600, orientation or acceleration/deceleration of the device 600, and temperature changes of the device 600 may be detected. The sensor assembly 614 may include a proximity sensor configured to detect the presence of nearby objects in the absence of any physical contact to enable the acquisition of environmental characteristic data. The sensor assembly 614 may also include an environmental sensor, such as a CMOS or CCD image sensor. In some embodiments, the sensor assembly 614 may also include an acceleration sensor, a gyroscope sensor, a magnetic sensor, a pressure sensor or a temperature sensor, among others.
The communication component 616 is configured to facilitate communications between the device 600 and other devices in a wired or wireless manner. The device 600 may access a wireless network based on a communication standard, such as Wi-Fi, 4G, or 5G, or a combination thereof. In an exemplary embodiment, the communication component 616 receives broadcast signals or broadcast related information from an external broadcast management system via a broadcast channel. And the communication component 616 may also include a positioning module, such as a GPS positioning module. In an exemplary embodiment, the communication component 616 further includes an NFC module to facilitate short-range communications. For example, the NFC module may be implemented based on Radio Frequency Identification (RFID) technology, infrared data association (IrDA) technology, Ultra Wideband (UWB) technology, Bluetooth (BT) technology, and other technologies.
In an exemplary embodiment, the device 600 may be implemented by one or more Application Specific Integrated Circuits (ASICs), Digital Signal Processors (DSPs), Digital Signal Processing Devices (DSPDs), Programmable Logic Devices (PLDs), Field Programmable Gate Arrays (FPGAs), controllers, micro-controllers, microprocessors or other electronic components for performing the above-described methods.
In an exemplary embodiment, the present application provides a non-transitory computer readable storage medium storing computer instructions for causing a computer to execute the steps of the anti-theft control method in the above embodiments. For example, the readable storage medium may be a ROM, a Random Access Memory (RAM), a CD-ROM, a magnetic tape, a floppy disk, an optical data storage device, and the like.
Other embodiments of the disclosure will be apparent to those skilled in the art from consideration of the specification and practice of the disclosure disclosed herein. This application is intended to cover any variations, uses, or adaptations of the disclosure following, in general, the principles of the disclosure and including such departures from the present disclosure as come within known or customary practice within the art to which the disclosure pertains. It is intended that the specification and examples be considered as exemplary only, with a true scope and spirit of the disclosure being indicated by the following claims.
It will be understood that the present disclosure is not limited to the precise arrangements described above and shown in the drawings and that various modifications and changes may be made without departing from the scope thereof. The scope of the present disclosure is limited only by the appended claims.

Claims (10)

1. The anti-theft control method is applied to intelligent wearable equipment and comprises the following steps:
acquiring current user behavior data, wherein the current user behavior data comprises user physiological characteristic data in a first period, and the user physiological characteristic data comprises at least one item of physiological index detection data;
determining a current behavior characteristic value according to the current user behavior data and a preset characteristic value algorithm;
determining a difference value between the current behavior characteristic value and a historical behavior characteristic value, wherein the historical behavior characteristic value is determined according to historical user behavior data and the preset characteristic value algorithm, the historical user behavior data comprises user physiological characteristic data in a second period, and the second period comprises the first period;
and if the difference value is greater than a preset difference threshold value, starting an anti-theft control mode.
2. The theft control method of claim 1, wherein said current user behavior data further comprises environmental signature data over said first period, said historical user behavior data further comprises environmental signature data over said second period, said environmental signature data comprising at least one item of environmental indicator detection data.
3. The antitheft control method according to claim 2, wherein the current user behavior data further includes a time stamp for determining the first period and the second period.
4. The antitheft control method according to any one of claims 1 to 3, wherein the turning on of the antitheft control mode includes at least one of:
locking user data, and uploading the user data to a server, wherein the user data is memory data of the intelligent wearable device;
forbidding interactive functions, wherein the interactive functions comprise a communication function and a setting function;
activating a positioning function, wherein the positioning function is used for uploading the current position of the intelligent wearable device to the server;
and sending an alarm instruction to the server, wherein the alarm instruction is used for indicating that the intelligent wearable device is in a lost state.
5. The antitheft control method according to any one of claims 1 to 3, further comprising:
receiving an unlocking instruction, wherein the unlocking instruction comprises an unlocking identity;
and if the unlocking identity identification passes the authentication, exiting the anti-theft control mode.
6. The antitheft control method according to any one of claims 1 to 3, wherein the duration corresponding to the second period is an integral multiple of the duration corresponding to the first period.
7. An intelligence wearing equipment which characterized in that includes:
the physiological characteristic detection module is used for acquiring user physiological characteristic data in a first period in current user behavior data, wherein the user physiological characteristic data comprises at least one item of physiological index detection data, and sending the current user behavior data to the control module;
the control module is used for determining a current behavior characteristic value according to the current user behavior data and a preset characteristic value algorithm and determining a difference value between the current behavior characteristic value and a historical behavior characteristic value, wherein the historical behavior characteristic value is determined according to historical user behavior data and the preset characteristic value algorithm, the historical user behavior data comprises user physiological characteristic data in a second period, and the second period comprises the first period;
and if the difference value is greater than a preset difference threshold value, the control module is also used for starting an anti-theft control mode.
8. The smart wearable device according to claim 7, wherein the physiological characteristic detection module comprises: at least one of a motion sensor, a heart rate sensor, a body temperature sensor, a bio-electrical sensor.
9. The smart wearable device according to claim 8, wherein the physiological characteristic detection module further comprises: at least one of a proximity sensor and an environmental sensor.
10. The intelligent wearable device according to any one of claims 7 to 9, further comprising: the positioning module is used for positioning the mobile phone;
the communication module comprises at least one of a Wi-Fi module and an NFC module;
the positioning module is a GPS positioning module.
CN201911289298.1A 2019-12-13 2019-12-13 Antitheft control method and intelligent wearable device Active CN111132139B (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN201911289298.1A CN111132139B (en) 2019-12-13 2019-12-13 Antitheft control method and intelligent wearable device

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN201911289298.1A CN111132139B (en) 2019-12-13 2019-12-13 Antitheft control method and intelligent wearable device

Publications (2)

Publication Number Publication Date
CN111132139A true CN111132139A (en) 2020-05-08
CN111132139B CN111132139B (en) 2023-06-02

Family

ID=70499006

Family Applications (1)

Application Number Title Priority Date Filing Date
CN201911289298.1A Active CN111132139B (en) 2019-12-13 2019-12-13 Antitheft control method and intelligent wearable device

Country Status (1)

Country Link
CN (1) CN111132139B (en)

Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN113836604A (en) * 2021-08-27 2021-12-24 太原市高远时代科技有限公司 Case with anti-theft video recording function

Citations (14)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN104361303A (en) * 2014-10-22 2015-02-18 小米科技有限责任公司 Terminal exception processing method and device and electronic equipment
CN104835274A (en) * 2015-05-06 2015-08-12 广东欧珀移动通信有限公司 Wearable device anti-theft method, apparatus and wearable device
CN105095802A (en) * 2014-04-25 2015-11-25 北京奇虎科技有限公司 Intelligent terminal equipment anti-theft method and intelligent terminal equipment
CN105162976A (en) * 2015-08-24 2015-12-16 努比亚技术有限公司 Mobile terminal and anti-theft processing method therefor
CN105450841A (en) * 2014-09-25 2016-03-30 小米科技有限责任公司 Method and device of terminal guard against theft
CN105893888A (en) * 2016-03-31 2016-08-24 广东小天才科技有限公司 Anti-theft and anti-loss method and system of intelligent terminal
WO2016183937A1 (en) * 2015-05-19 2016-11-24 中兴通讯股份有限公司 Identity authentication method, device and system, and user terminal
CN106899745A (en) * 2015-12-18 2017-06-27 小米科技有限责任公司 Unlocking method, device and terminal
CN107361759A (en) * 2017-08-24 2017-11-21 深圳金康特智能科技有限公司 A kind of anti-theft intelligent wearable device based on rhythm of the heart
CN108811181A (en) * 2018-04-27 2018-11-13 努比亚技术有限公司 Intelligent wearable device, security method and computer readable storage medium
CN108875344A (en) * 2018-06-25 2018-11-23 Oppo（重庆）智能科技有限公司 A kind of electronic equipment control method, electronic appliance controlling device and electronic equipment
CN108875327A (en) * 2018-05-28 2018-11-23 阿里巴巴集团控股有限公司 One seed nucleus body method and apparatus
CN109034060A (en) * 2018-07-25 2018-12-18 深圳还是威健康科技有限公司 A kind of method and device of wearing state detection
CN109658668A (en) * 2019-01-23 2019-04-19 出门问问信息科技有限公司 Alarm method, warning device and intelligent wearable device

Patent Citations (15)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN105095802A (en) * 2014-04-25 2015-11-25 北京奇虎科技有限公司 Intelligent terminal equipment anti-theft method and intelligent terminal equipment
CN105450841A (en) * 2014-09-25 2016-03-30 小米科技有限责任公司 Method and device of terminal guard against theft
CN104361303A (en) * 2014-10-22 2015-02-18 小米科技有限责任公司 Terminal exception processing method and device and electronic equipment
CN104835274A (en) * 2015-05-06 2015-08-12 广东欧珀移动通信有限公司 Wearable device anti-theft method, apparatus and wearable device
WO2016183937A1 (en) * 2015-05-19 2016-11-24 中兴通讯股份有限公司 Identity authentication method, device and system, and user terminal
CN106301778A (en) * 2015-05-19 2017-01-04 中兴通讯股份有限公司 Auth method, device, system and user terminal
CN105162976A (en) * 2015-08-24 2015-12-16 努比亚技术有限公司 Mobile terminal and anti-theft processing method therefor
CN106899745A (en) * 2015-12-18 2017-06-27 小米科技有限责任公司 Unlocking method, device and terminal
CN105893888A (en) * 2016-03-31 2016-08-24 广东小天才科技有限公司 Anti-theft and anti-loss method and system of intelligent terminal
CN107361759A (en) * 2017-08-24 2017-11-21 深圳金康特智能科技有限公司 A kind of anti-theft intelligent wearable device based on rhythm of the heart
CN108811181A (en) * 2018-04-27 2018-11-13 努比亚技术有限公司 Intelligent wearable device, security method and computer readable storage medium
CN108875327A (en) * 2018-05-28 2018-11-23 阿里巴巴集团控股有限公司 One seed nucleus body method and apparatus
CN108875344A (en) * 2018-06-25 2018-11-23 Oppo（重庆）智能科技有限公司 A kind of electronic equipment control method, electronic appliance controlling device and electronic equipment
CN109034060A (en) * 2018-07-25 2018-12-18 深圳还是威健康科技有限公司 A kind of method and device of wearing state detection
CN109658668A (en) * 2019-01-23 2019-04-19 出门问问信息科技有限公司 Alarm method, warning device and intelligent wearable device

Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN113836604A (en) * 2021-08-27 2021-12-24 太原市高远时代科技有限公司 Case with anti-theft video recording function
CN113836604B (en) * 2021-08-27 2024-03-01 太原市高远时代科技有限公司 Case with anti-theft video recording function

Also Published As

Publication number Publication date
CN111132139B (en) 2023-06-02

Similar Documents

Publication Publication Date Title
EP3012766B1 (en) Method and apparatus for processing terminal anomaly
US10191564B2 (en) Screen control method and device
CN104850995B (en) Operation execution method and device
EP2911126A1 (en) Method and device for protecting terminal apparatus and terminal apparatus and medium
US10691920B2 (en) Information image display method and apparatus
US11586246B2 (en) Method and apparatus for providing notification regarding wearable device
CN105975828B (en) Unlocking method and device
CN103561163A (en) Intelligent watchband
CN104539776A (en) Alarm prompting method and device
CN104008348A (en) Application program control method, application program control device and terminal
CN105404382A (en) Power saving mode setting method and apparatus
CN109992946A (en) Solve the method, apparatus and computer readable storage medium of locked application
US20120282877A1 (en) Systems and methods for initiating a stand-by signal and a distress signal from a mobile device
CN109214301A (en) Control method and device based on recognition of face and gesture identification
CN105471890A (en) Unlocking method based on wearable device, apparatus and system
US20190087591A1 (en) Method, device and storage medium for printing information
EP3447666A1 (en) Processing fingerprint information
CN104332037A (en) Method and device for alarm detection
CN104952228A (en) Antitheft protection opening method, and apparatus and system thereof
CN111132139B (en) Antitheft control method and intelligent wearable device
US9721454B2 (en) Method for protecting terminal devices and the terminal device thereof
CN106550012B (en) Monitoring method of intelligent equipment and intelligent equipment
EP3200127B1 (en) Method and device for fingerprint recognition
CN110188533B (en) A method, device and medium for preventing abnormal unlocking
CN112883441B (en) A method, device, and storage medium for preventing electronic equipment from being lost

Legal Events

Date Code Title Description
PB01 Publication
PB01 Publication
SE01 Entry into force of request for substantive examination
SE01 Entry into force of request for substantive examination
GR01 Patent grant
GR01 Patent grant