WO2023226502A1 - 电子围栏告警方法、装置、电子设备和存储介质 - Google Patents

电子围栏告警方法、装置、电子设备和存储介质 Download PDF

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Publication number
WO2023226502A1
WO2023226502A1 PCT/CN2023/078831 CN2023078831W WO2023226502A1 WO 2023226502 A1 WO2023226502 A1 WO 2023226502A1 CN 2023078831 W CN2023078831 W CN 2023078831W WO 2023226502 A1 WO2023226502 A1 WO 2023226502A1
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Prior art keywords
electronic fence
fence
exiting
electronic
entering
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PCT/CN2023/078831
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English (en)
French (fr)
Inventor
晁鹏辉
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中兴通讯股份有限公司
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Publication of WO2023226502A1 publication Critical patent/WO2023226502A1/zh

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    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W4/00—Services specially adapted for wireless communication networks; Facilities therefor
    • H04W4/02—Services making use of location information
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W4/00—Services specially adapted for wireless communication networks; Facilities therefor
    • H04W4/02—Services making use of location information
    • H04W4/021—Services related to particular areas, e.g. point of interest [POI] services, venue services or geofences
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W4/00—Services specially adapted for wireless communication networks; Facilities therefor
    • H04W4/02—Services making use of location information
    • H04W4/029—Location-based management or tracking services

Definitions

  • the present disclosure relates to the field of fence alarm technology, and in particular to an electronic fence alarm method, device, electronic device and storage medium.
  • the geo-electronic fence alarm method usually determines the status of the geo-fence through regular positioning, and sends fence alarm information when the status changes; there are usually two methods for Wi-Fi geo-fence: 1. Set the SSID of the Wi-Fi geo-fence and password, and the device automatically connects and disconnects from the set Wi-Fi to determine entry and exit of the Wi-Fi electronic fence. 2. Set the SSID of the Wi-Fi electronic fence, and set the Wi-Fi by regularly scanning the device to determine the situation of entering and exiting the Wi-Fi electronic fence.
  • the timing interval For the processing of geo-electronic fences, if the timing interval is too short, it will have a greater impact on the power consumption of the device. If the timing interval is too long, the judgment of entering and exiting the fence will be insensitive, and status omissions will easily occur.
  • the first method mentioned above is more sensitive, but the Wi-Fi module needs to be in working state all the time, which increases power consumption.
  • the second method if the time interval of the scheduled scan is too short, it will affect the power consumption of the device. If the time interval of the scheduled scan is too long, the device's response to the entry and exit of the Wi-Fi electronic fence will not be sensitive enough, affecting the user experience.
  • the device regularly performs positioning or Wi-Fi scanning to determine the entry and exit status of the electronic fence, and alarms when it detects entering or exiting the fence, there are the following defects: If the timing If the time interval is too short, it will increase the power consumption of the device per unit time, and shorten the use time of the device when the battery is at the same level; if the set time interval is too long, it will affect the device's judgment of entering and exiting the fence, and it is prone to status Omissions result in users being unable to receive geo-fence alerts, affecting user experience.
  • embodiments of the present disclosure provide an electronic fence alarm method, device, electronic equipment and storage medium.
  • Embodiments of the present disclosure provide an electronic fence alarm method.
  • the method includes: reading device motion data; predicting the state of the device entering or exiting the electronic fence based on the motion data, and obtaining prediction results; based on the prediction results Turn on the detection of the status of the device entering or exiting the electronic fence.
  • An embodiment of the present disclosure also provides an electronic fence alarm device.
  • the device includes: an acquisition module for reading equipment movement data; and a prediction module for determining the status of the equipment entering or exiting the electronic fence based on the movement data. Make predictions and obtain prediction results; and enable a module for enabling detection of the state of the device entering or exiting the electronic fence according to the prediction results.
  • An embodiment of the present disclosure also provides an electronic device, including: a processor and a memory used to store a computer program that can be run on the processor; wherein, when the processor is used to run the computer program, the steps of any of the above methods are performed.
  • Embodiments of the present disclosure also provide a storage medium.
  • a computer program is stored in the storage medium.
  • the computer program is executed by a processor, the steps of any of the above methods are implemented.
  • Figure 1 is a schematic flow chart of an electronic fence alarm method according to an embodiment of the present disclosure
  • Figure 2 is another schematic flowchart of an electronic fence alarm method according to an embodiment of the present disclosure
  • FIG. 3 is another schematic flowchart of an electronic fence alarm method according to an embodiment of the present disclosure.
  • Figure 4 is another schematic flowchart of an electronic fence alarm method according to an embodiment of the present disclosure.
  • Figure 5 is a schematic structural diagram of a low-power tracking device according to an application embodiment of the present disclosure
  • Figure 6 is a schematic diagram of the training process according to the application embodiment of the present disclosure.
  • Figure 7 is a schematic diagram of the geo-electronic fence alarm process according to the application embodiment of the present disclosure.
  • Figure 8 is a schematic diagram of the Wi-Fi electronic fence alarm process according to the application embodiment of the present disclosure.
  • Figure 9 is a schematic structural diagram of an electronic fence alarm device according to an embodiment of the present disclosure.
  • Figure 10 is an internal structure diagram of a computer device according to an embodiment of the present disclosure.
  • the embodiment of the present disclosure provides an electronic fence alarm method, as shown in Figure 1.
  • the method may include, but is not limited to, the following operations.
  • Step 101 Obtain device motion data
  • Step 102 Predict the state of the device entering or exiting the electronic fence based on the motion data, and obtain the prediction results;
  • Step 103 Start detecting the state of the device entering or exiting the electronic fence according to the prediction result.
  • the method of this embodiment can be applied to the electronic fence alarm function of a low-power tracking device.
  • this embodiment mainly uses acceleration sensor and direction sensor data to predict the status of the device entering or exiting the electronic fence, and determines whether positioning or Wi-Fi scanning is required based on the inference prediction results to detect the status of the device entering or exiting the fence.
  • the acceleration sensor and the direction sensor are used to sense the acceleration information and movement direction information of the device; among them, the geo-electronic fence uses positioning to detect the status of the device entering and exiting the fence, and the Wi-Fi electronic fence uses Wi-Fi scanning to detect the status of the device entering and exiting the fence.
  • the scheduled positioning or scheduled scanning interval is too short, it will have a greater impact on the power consumption of the device. If the timing interval is too long, the judgment of entering and exiting the fence will not be sensitive, and status omissions will easily occur. .
  • the timing positioning data and the data collected by the acceleration sensor and the direction sensor it determines whether a fence status check is needed. This can be done in a timely manner without shortening the interval between positioning and Wi-Fi scanning. Notify users of fence status.
  • the method may further include:
  • the preset location range may be set to the electronic fence range, or may be set to the electronic fence range and a range close to the perimeter of the electronic fence.
  • the motion data collected by the device's acceleration sensor and direction sensor are obtained for prediction, which can reduce unnecessary calculations by the device.
  • this embodiment can provide two methods for predicting the status of equipment entering and exiting the fence.
  • the first method is:
  • predicting the state of the device entering or exiting the electronic fence based on the motion data and obtaining the prediction results includes:
  • Step 201 Calculate the number of steps and direction of walking of the device according to the motion data
  • Step 202 Predict the state of the device entering or exiting the electronic fence based on the number of steps and direction of the device walking, and obtain the prediction result.
  • This embodiment uses the data collected by the acceleration sensor and direction sensor to calculate the number of walking steps and direction, and determines whether positioning or Wi-Fi scanning is needed to detect the status of entering and exiting the fence based on the calculation results.
  • the second method is:
  • predicting the state of the device entering or exiting the electronic fence based on the motion data and obtaining the prediction results includes:
  • the motion data is input into the trained prediction model to obtain the prediction result of the device entering or exiting the electronic fence state.
  • the acceleration sensor and direction sensor data are used as the input layer of the convolutional neural network. Whether to leave or enter the coverage area of the electronic fence is used as the output layer of the convolutional neural network. Deep learning training is performed, and the trained model is converted into a model suitable for micro-control. The model of the sensor is embedded in the tracking device. When the low-power tracking device is in or close to the electronic fence, the data collected through the acceleration sensor and direction sensor are inferred through the model, and based on the inference results, it is judged whether positioning is required. Or Wi-Fi scan to detect entry and exit fence status.
  • determining whether to detect whether the device enters or exits the electronic fence state based on the prediction result includes:
  • the detection of the status of the device entering or exiting the electronic fence is started.
  • the detection of the state of the device entering or leaving the electronic fence is enabled; or when the prediction result is that the device enters the electronic fence
  • the detection of the status of the device entering or exiting the electronic fence is turned on.
  • the detection of the state of the device entering or exiting the electronic fence is performed according to the original settings. For example, scheduled positioning or scheduled scanning is performed at preset time intervals to detect whether the device enters or exits the electronic fence. Or do not detect the status of the device entering or exiting the electronic fence. Or when the device continues outside the electronic fence, the execution process refers to the following embodiment:
  • electronic fences include geographical electronic fences and Wi-Fi electronic fences. Therefore, during actual detection, for different types of electronic fences, the present disclosure can use different methods to detect the status of the device entering or exiting the electronic fence.
  • the detection of the status of the device entering or exiting the electronic fence is enabled.
  • Step 301 Perform positioning detection on the device to obtain the location information of the device;
  • Step 302 Determine whether the device has left the electronic fence according to the location information
  • Step 303 When it is determined that the device has left the electronic fence based on the location information, send an alarm that the device has left the electronic fence.
  • the acceleration sensor and the direction sensor The collected data is predicted. If the device is predicted to leave the geo-fence, a positioning is performed to confirm whether the device has left the geo-fence. If it has left the geo-fence, an alarm notification is sent to the user.
  • the method when it is determined that the device has left the electronic fence based on the location information, the method further includes:
  • the location information obtain the distance and relative direction between the device and the center of the electronic fence
  • the prediction result is that the device has entered the electronic fence
  • perform positioning detection on the device to obtain the location information of the device; determine whether the device has entered the electronic fence based on the location information; when based on the location
  • send an alarm that the device has entered the electronic fence
  • it is determined based on the location information that the device has not entered the electronic fence continue to obtain the motion data of the device, and monitor the device based on the motion data. Predict the operation of the equipment entering or exiting the electronic fence.
  • the distance and relative direction to the center of the fence are calculated for each timed positioning.
  • the distance is greater than the radius of the fence and less than the first
  • the threshold is preset
  • the data collected by the acceleration sensor and the direction sensor are used for prediction.
  • the prediction result is that the fence range has been entered, a positioning is performed. If the fence range has been entered, a fence entry alarm notification will be sent. If the fence has not been entered, Then continue to perform the next prediction and positioning through the above method.
  • the device when the prediction result is that the device leaves the geo-fence, and the geo-fence is a Wi-Fi geo-fence, the device is enabled to enter or exit the geo-fence state. Testing includes:
  • Step 401 Perform a Wi-Fi scan to detect whether the device has left the electronic fence;
  • Step 402 When it is detected that the device has left the electronic fence, send an alarm that the device has left the electronic fence.
  • the low-power tracking device when it is in a Wi-Fi electronic fence, if it enters the fence for the first time, it will perform a positioning and record the data, and make predictions based on the data collected by the acceleration sensor and direction sensor. If the prediction If the result is that the device has left the Wi-Fi electronic fence, a Wi-Fi scan will be performed to detect whether the device has left the fence. If it has left the fence, an alarm notification of leaving the Wi-Fi electronic fence will be sent to the user. If it has not left the fence, , then continue to perform the next prediction and Wi-Fi scan through the above method.
  • the method when detecting that the device has left the electronic fence, the method further includes:
  • the device movement data Predict the state of the device entering or exiting the electronic fence based on the motion data, and obtain the prediction results;
  • the device When the prediction result is that the device has entered the electronic fence, perform a Wi-Fi scan to detect whether the device has entered the electronic fence; when it is detected that the device has entered the electronic fence, send an alarm that the device has entered the electronic fence; when it is detected that the device has entered the electronic fence When the device does not enter the electronic fence, continue to perform the operation of obtaining motion data of the device and predicting the status of the device entering or exiting the electronic fence based on the motion data.
  • the distance and relative direction to the positioning data in the fence are calculated for each timed positioning.
  • the distance is greater than the fence coverage and less than the second preset threshold.
  • prediction is made based on the data collected by the acceleration sensor and the direction sensor.
  • the prediction result is that the fence range is entered, a Wi-Fi scan is performed. If If it has entered the fence range, a fence entry alarm notification will be sent. If it has not entered the fence, it will continue to perform the next inference and Wi-Fi scan through the above method.
  • the electronic fence alarm method provided by the embodiment of the present disclosure reads device motion data; predicts the status of the device entering or exiting the electronic fence according to the motion data, and obtains the prediction result; and starts monitoring the device according to the prediction result. Detection of entering or exiting electronic fence status.
  • Using the solution provided by the present disclosure can improve the fence alarm sensitivity without affecting the power consumption of the device.
  • This application embodiment provides a low-power tracking device electronic fence alarm method, which is used to solve the problem of untimely alarms and even missing fence status in the processing of electronic fences by low-power tracking devices.
  • the fence alarm provided by this embodiment This method can improve the fence alarm sensitivity without affecting the power consumption of the device.
  • the low-power tracking device may include, but is not limited to: an acceleration sensor 501 , a direction sensor 502 , an MCU control module 503 , a GPS module 504 , and a Wi-Fi module 505 .
  • the acceleration sensor is used to collect acceleration information
  • the direction sensor is used to collect equipment running direction information.
  • this embodiment can also use other components with the same functions.
  • a low-power tracking device may also include more or fewer components than shown in Figure 5, or have a different configuration than shown in Figure 5.
  • model training process of the low-power tracking device may include the following operations.
  • Step 601 Use the low-power tracking device to move and collect data of the acceleration sensor and the direction sensor entering or leaving the electronic fence range.
  • Step 602 Use the collected data as the input layer of the convolutional neural network, and whether it leaves or enters the electronic fence coverage area as the output layer of the convolutional neural network for deep learning training.
  • Step 603 Convert the trained model into a model suitable for a microcontroller and embed it into the tracking device.
  • Step 701 After the low-power tracking device completes positioning, it determines whether the geographical address electronic fence state of the device is consistent with the previous fence state.
  • Step 702 If the geo-electronic fence status of the device is inconsistent with the last fence status, send a fence status alarm notification to the user.
  • Step 703 Determine whether the low-power tracking device is within the geo-electronic fence.
  • Step 704 If the device is within the geo-electronic fence, predict the data collected by the acceleration sensor and the direction sensor.
  • Step 705 Determine whether the prediction result leaves the fence.
  • Step 706 If the prediction result is to leave the fence, perform positioning and check the status of the fence. If it has left the fence, send a geo-fence alarm; otherwise, repeat steps 704 and 705.
  • Step 707 If the device is outside the geo-electronic fence, determine whether the distance from the last timed positioning to the center of the fence is greater than the radius of the fence and does not exceed the preset threshold.
  • Step 708 If the device is outside the fence and the distance from the center of the fence is greater than the radius of the fence and does not exceed the preset threshold, predict the data collected by the acceleration sensor and the direction sensor.
  • Step 709 Judge the prediction result.
  • Step 710 If the prediction result is that it has entered the fence, perform positioning and check the status of the fence. If it has entered the fence, send an electronic fence alarm; otherwise, repeat steps 708 and 709.
  • Step 801 After completing the Wi-Fi scan, the low-power tracking device determines whether the Wi-Fi fence state of the device is consistent with the previous fence state.
  • Step 802 If the device Wi-Fi electronic fence status is inconsistent with the last fence status, send a fence status alarm notification to the user.
  • Step 803 Determine whether the device is within the Wi-Fi electronic fence.
  • Step 804 Determine whether the device has fence location information.
  • Step 805 If the device is within a Wi-Fi electronic fence and there is no fence location information, perform a positioning and record the fence location information.
  • Step 806 Predict the data collected by the acceleration sensor and the direction sensor.
  • Step 807 Predict whether the device leaves the fence.
  • Step 808 If the prediction result is that the user has left the fence, perform a Wi-Fi scan and check the fence status. If the user has left the fence, send a Wi-Fi electronic fence alarm; otherwise, repeat steps 806 and 807.
  • Step 809 Determine that the device is outside the Wi-Fi electronic fence and has saved fence location information.
  • Step 810 Determine whether the distance between the device and the fence exceeds a preset threshold.
  • Step 811 If the distance between the device and the fence does not exceed the preset distance threshold, predict the data collected by the acceleration sensor and the direction sensor.
  • Step 812 If the prediction result is that it has entered the fence, perform a Wi-Fi scan and check the fence status. If it has entered the fence, send a geo-fence alarm; otherwise, repeat steps 811 and 812.
  • This embodiment can improve the fence alarm sensitivity without affecting the power consumption of the device.
  • the embodiment of the present disclosure also provides an electronic fence alarm device.
  • the electronic fence alarm device 900 includes: an acquisition module 901, a prediction module 902 and an opening module 903; wherein,
  • Acquisition module 901 used to read device motion data
  • the prediction module 902 is used to predict the state of the device entering or exiting the electronic fence based on the motion data, and obtain prediction results;
  • the enabling module 903 is configured to enable detection of the state of the device entering or exiting the electronic fence according to the prediction result.
  • the acquisition module 901, the prediction module 902 and the activation module 903 can be implemented by the processor in the electronic fence alarm device.
  • the embodiment of the present disclosure also provides a computer program product.
  • the computer program product includes computer instructions, and the computer instructions are stored in a computer-readable storage medium.
  • the processor of the computer device reads the computer instructions from the computer-readable storage medium, and the processor executes the computer instructions, so that the computer device performs the steps of the above method.
  • the embodiment of the present disclosure also provides an electronic device (computer device).
  • the computer device may be a terminal, and its internal structure diagram may be as shown in FIG. 10 .
  • the computer equipment includes a processor A01, a network interface A02, a display screen A04, an input device A05 and a memory (not shown in the figure) connected through a system bus.
  • the processor A01 of the computer device is used to provide computing and control capabilities.
  • the memory of the computer device includes internal memory A03 and non-volatile storage medium A06.
  • the non-volatile storage medium A06 stores an operating system B01 and a computer program B02.
  • the internal memory A03 provides an environment for the execution of the operating system B01 and the computer program B02 in the non-volatile storage medium A06.
  • the network interface A02 of the computer device is used to communicate with external terminals through a network connection. The calculation When the machine program is executed by the processor A01, the method of any of the above embodiments can be implemented.
  • the display screen A04 of the computer device may be a liquid crystal display or an electronic ink display.
  • the input device A05 of the computer device may be a touch layer covered on the display screen, or may be a button, trackball or touch screen provided on the shell of the computer device.
  • a control panel can also be an external keyboard, trackpad, or mouse.
  • FIG. 10 is only a block diagram of a partial structure related to the disclosed solution, and does not constitute a limitation on the computer equipment to which the disclosed solution is applied.
  • Specific computer equipment can May include more or fewer parts than shown, or combine certain parts, or have a different arrangement of parts.
  • the device provided by the embodiments of the present disclosure includes a processor, a memory, and a program stored in the memory and executable on the processor.
  • the processor executes the program, the method of any of the above embodiments is implemented.
  • embodiments of the present disclosure may be provided as methods, systems, or computer program products. Accordingly, the present disclosure may take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment that combines software and hardware aspects. Furthermore, the present disclosure may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) having computer-usable program code embodied therein.
  • computer-usable storage media including, but not limited to, disk storage, CD-ROM, optical storage, etc.
  • These computer program instructions may also be stored in a computer-readable memory that causes a computer or other programmable data processing apparatus to operate in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including the instruction means, the instructions
  • the device implements the functions specified in a process or processes of the flowchart and/or a block or blocks of the block diagram.
  • These computer program instructions may also be loaded onto a computer or other programmable data processing device, causing a series of operating steps to be performed on the computer or other programmable device to produce computer-implemented processing, thereby executing on the computer or other programmable device.
  • Instructions provide steps for implementing the functions specified in a process or processes of a flowchart diagram and/or a block or blocks of a block diagram.
  • a computing device includes one or more processors (CPUs), input/output interfaces, network interfaces, and memory.
  • processors CPUs
  • input/output interfaces network interfaces
  • memory volatile and non-volatile memory
  • Memory may include non-volatile memory in computer-readable media, random access memory (RAM) and/or non-volatile Non-volatile memory, such as read-only memory (ROM) or flash memory (flashRAM). Memory is an example of a computer-readable medium.
  • RAM random access memory
  • ROM read-only memory
  • flashRAM flash memory
  • Computer-readable media includes both persistent and non-volatile, removable and non-removable media that can be implemented by any method or technology for storage of information.
  • Information may be computer-readable instructions, data structures, modules of programs, or other data.
  • Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), and read-only memory.
  • PRAM phase change memory
  • SRAM static random access memory
  • DRAM dynamic random access memory
  • RAM random access memory
  • read-only memory read-only memory
  • ROM read-only memory
  • EEPROM electrically erasable programmable read-only memory
  • flash memory or other memory technology
  • compact disc read-only memory CD-ROM
  • DVD digital versatile disc
  • Magnetic tape cassettes tape magnetic disk storage or other magnetic storage devices or any other non-transmission medium can be used to store information that can be accessed by a computing device.
  • computer-readable media does not include transitory media, such as modulated data signals and carrier waves.
  • non-volatile memory can be read-only memory (ROM, Read Only Memory), programmable read-only memory (PROM, Programmable Read-Only Memory), erasable programmable read-only memory (EPROM, Erasable Programmable Read-Only Memory).
  • ROM Read Only Memory
  • PROM Programmable Read-Only Memory
  • EPROM Erasable Programmable Read-Only Memory
  • EEPROM Electrically Erasable Programmable Read-Only Memory
  • FRAM Magnetic Random Access Memory
  • Flash Memory Magnetic Surface Memory , optical disk, or compact disc (CD-ROM, Compact Disc Read-Only Memory); magnetic surface memory can be disk storage or tape storage.
  • Volatile memory can be random access memory (RAM, Random Access Memory), which is used as an external cache.
  • RAM Random Access Memory
  • SRAM Static Random Access Memory
  • SSRAM Synchronous Static Random Access Memory
  • DRAM Dynamic Random Access Memory
  • SDRAM Synchronous Dynamic Random Access Memory
  • DDRSDRAM Double Data Rate Synchronous Dynamic Random Access Memory
  • ESDRAM Enhanced Synchronous Dynamic Random Access Memory
  • SLDRAM Synchronous Link Dynamic Random Access Memory
  • DRRAM Direct Rambus Random Access Memory
  • Memories described in embodiments of the present disclosure are intended to include, but are not limited to, these and any other suitable types of memory.

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Abstract

本公开公开了一种电子围栏告警方法、装置、电子设备和存储介质。该方法包括读取设备运动数据；根据运动数据对设备进或出电子围栏的状态进行预测，获取预测结果；根据预测结果开启对设备进或出电子围栏状态的检测。采用本公开提供的方案能提高围栏告警灵敏度且不影响设备的功耗。

Description

电子围栏告警方法、装置、电子设备和存储介质
相关申请的交叉引用
本公开基于2022年5月25日提交的发明名称为“电子围栏告警方法、装置、电子设备和存储介质”的中国专利申请CN202210580562.2，并且要求该专利申请的优先权，通过引用将其所公开的内容全部并入本公开。
技术领域
本公开涉及围栏告警技术领域，尤其涉及一种电子围栏告警方法、装置、电子设备和存储介质。
背景技术
随着通讯技术的发展和物联网概念的不断提升，窄带物联网设备由于其网络覆盖广、低功耗、接入设备量大、模块成本低等特点，应用其功能的产品越来越多，其中包括低功耗跟踪设备。现有的低功耗跟踪设备产品都有电子围栏功能。其中，地理电子围栏告警方法通常是通过定时定位来判断电子围栏状态，状态变化时发送围栏告警信息；而Wi-Fi电子围栏的做法通常有两种，1、设定Wi-Fi电子围栏的SSID及密码，通过设备自动连接、断开设定的Wi-Fi来判断进出Wi-Fi电子围栏的情况。2、设定Wi-Fi电子围栏的SSID，通过设备定时扫描设定Wi-Fi来判断进出Wi-Fi电子围栏的情况。
对于地理电子围栏的处理，如果定时间隔太短，则对设备的功耗影响比较大，如果定时间隔太长，则对进出围栏的判断不灵敏，容易出现状态遗漏。对Wi-Fi电子围栏的处理，上述的第一种方法比较灵敏，但Wi-Fi模块需要一直处于工作状态，增加功耗。第二种方法，若定时扫描的时间间隔太短，则会影响设备的功耗，若定时扫描的时间间隔太长，则设备对进出Wi-Fi电子围栏的响应不够灵敏，影响用户使用体验。
即无论是地理电子围栏或是Wi-Fi电子围栏，设备定时进行定位或者Wi-Fi扫描来判断电子围栏的进出状态，在检测到进入围栏或者出围栏时进行告警，都存在以下缺陷：如果定时的时间间隔太短，则会增加设备单位时间内的功耗，电池同电量状态下，缩短设备使用时间；如果设定的时间间隔太长，则会影响设备对进出围栏的判断，容易出现状态遗漏，导致用户无法收到电子围栏告警，影响用户使用体验。
发明内容
为至少解决电子围栏告警遗漏或耗费功耗较大的技术问题，本公开实施例提供一种电子围栏告警方法、装置、电子设备和存储介质。
本公开实施例的技术方案是这样实现的：
本公开实施例提供了一种电子围栏告警方法，方法包括：读取设备运动数据；根据所述运动数据对所述设备进或出电子围栏的状态进行预测，获取预测结果；根据所述预测结果开启对所述设备进或出电子围栏状态的检测。
本公开实施例还提供了一种电子围栏告警装置，该装置包括：获取模块，用于读取设备运动数据；预测模块，用于根据所述运动数据对所述设备进或出电子围栏的状态进行预测，获取预测结果；开启模块，用于根据所述预测结果开启对所述设备进或出电子围栏状态的检测。
本公开实施例还提供了一种电子设备，包括：处理器和用于存储能够在处理器上运行的计算机程序的存储器；其中，处理器用于运行计算机程序时，执行上述任一方法的步骤。
本公开实施例还提供了一种存储介质，存储介质中存储有计算机程序，计算机程序被处理器执行时，实现上述任一方法的步骤。
附图说明
图1为本公开实施例电子围栏告警方法的流程示意图；
图2为本公开实施例电子围栏告警方法的另一流程示意图；
图3为本公开实施例电子围栏告警方法的另一流程示意图；
图4为本公开实施例电子围栏告警方法的另一流程示意图；
图5为本公开应用实施例低功耗跟踪设备的组成结构示意图；
图6为本公开应用实施例训练过程示意图；
图7为本公开应用实施例地理电子围栏告警过程示意图；
图8为本公开应用实施例Wi-Fi电子围栏告警过程示意图；
图9为本公开实施例电子围栏告警装置的结构示意图；
图10为本公开实施例计算机设备的内部结构图。
具体实施方式
下面将结合附图及实施例对本公开作进一步详细的描述。
本公开实施例提供了一种电子围栏告警方法，如图1所示，该方法可以包括，但不限于下述操作。
步骤101：获取设备运动数据；
步骤102：根据所述运动数据对所述设备进或出电子围栏的状态进行预测，获取预测结果；
步骤103：根据所述预测结果开启对所述设备进或出电子围栏状态的检测。
在一示例性的实施方式中，本实施例方法可应用于低功耗跟踪设备的电子围栏告警功能。
进一步地，本实施例主要通过加速度传感器及方向传感器数据预测设备进或出电子围栏的状态，根据推理预测结果判断是否需要进行定位或Wi-Fi扫描来检测设备进出围栏状态。其中，加速度传感器和方向传感器用于感测设备的加速度信息和运动方向信息；其中，地理电子围栏采用定位来检测设备进出围栏状态，Wi-Fi电子围栏采用Wi-Fi扫描来检测设备进出围栏状态。
现有技术中，对电子围栏的处理，如果定时定位或定时扫描间隔太短，则对设备的功耗影响比较大，如果定时间隔太长，则对进出围栏的判断不灵敏，容易出现状态遗漏。而本实施例通过对定时定位的数据及加速度传感器和方向传感器采集到的数据进行计算分析，判断是否需要进行围栏状态检查，在不缩短定位及Wi-Fi扫描的间隔时间的情况下，可以及时通知用户围栏状态。
进一步地，在一实施例中，获取设备加速度传感器和方向传感器采集的运动数据之前，所述方法还可以包括：
对所述设备进行定位检测，获得所述设备的位置信息；
判断所述设备的位置信息是否在预设位置范围内；
当所述设备的位置信息在预设位置范围内时，获取设备运动数据。
在一示例性的实施方式中，预设位置范围可以设定为电子围栏范围，也可以设定为电子围栏范围及靠近电子围栏周边的范围。实际应用时，当设备处于电子围栏范围内时，或者设备靠近电子围栏周边范围时，再获取设备加速度传感器和方向传感器采集的运动数据进行预测，可减少设备不必要的计算。
进一步地，本实施例可以提供两种预测设备进出围栏状态的方法。
其中，第一种方法为：
参见图2，在一实施例中，所述根据所述运动数据对所述设备进或出电子围栏的状态进行预测，获取预测结果，包括：
步骤201：根据所述运动数据计算所述设备行走的步数和方向；
步骤202：根据所述设备行走的步数和方向，预测所述设备进或出电子围栏的状态，获得预测结果。
本实施例通过加速度传感器和方向传感器采集到的数据计算出行走的步数和方向，根据计算结果判断是否需要进行定位或Wi-Fi扫描来检测进出围栏状态。
其中，第二种方法为：
在一实施例中，所述根据所述运动数据对所述设备进或出电子围栏的状态进行预测，获取预测结果，包括：
将所述运动数据输入训练好的预测模型中，获得所述设备进或出电子围栏状态的预测结果。
本实施例将加速度传感器及方向传感器数据作为卷积神经网络输入层，是否离开或进入电子围栏覆盖范围作为卷积神经网络输出层，进行深度学习训练，将训练后的模型转换为适用于微控制器的模型嵌入所属追踪设备中，当低功耗跟踪设备处于电子围栏中或接近电子围栏时，通过加速度传感器和方向传感器采集到的数据通过所述模型进行推理，根据推理结果判断是否需要进行定位或Wi-Fi扫描来检测进出围栏状态。
进一步地，在一实施例中，所述根据所述预测结果判断是否进行所述设备进或出电子围栏状态的检测，包括：
当所述预测结果为所述设备进入电子围栏或所述设备离开电子围栏时，开启对所述设备进或出电子围栏状态的检测。
在一示例性的实施方式中，当所述预测结果为所述设备离开电子围栏时，开启对所述设备进或出电子围栏状态的检测；或当所述预测结果为所述设备进入电子围栏时，开启对所述设备进或出电子围栏状态的检测。
另外，当所述预测结果为所述设备进或出电子围栏状态未发生改变时，即当所述设备继续在电子围栏内时，按照原来设置进行所述设备进或出电子围栏状态的检测。例如，按照预设时间间隔进行定时定位或定时扫描，来检测所述设备进或出电子围栏状态。或不进行所述设备进或出电子围栏状态的检测。或当所述设备继续在电子围栏外时，执行过程参见以下实施例：
另外，由于电子围栏包括地理电子围栏和Wi-Fi电子围栏。因此，在实际检测时，针对不同类别的电子围栏，本公开可采用不同的方式进行所述设备进或出电子围栏状态的检测。
进一步地，参见图3，在一实施例中，当所述预测结果为所述设备离开电子围栏，且所述电子围栏为地理电子围栏时，开启对所述设备进或出电子围栏状态的检测包括：
步骤301：对所述设备进行定位检测，获得所述设备的位置信息；
步骤302：根据所述位置信息判断所述设备是否已经离开电子围栏；
步骤303：当根据所述位置信息判断所述设备已经离开电子围栏时，发送设备离开电子围栏告警。
实际使用时，当低功耗跟踪设备处于地理电子围栏内时，对加速度传感器和方向传感器 采集到的数据进行预测，如果预测所述设备离开地理电子围栏，则进行一次定位，确认所述设备是否已经离开所述电子围栏，若已离开电子围栏范围，则向用户发送告警通知。
在一实施例中，当根据所述位置信息判断所述设备已经离开电子围栏时，所述方法还包括：
根据所述位置信息，获取所述设备与所述电子围栏中心的距离和相对方向；
判断所述距离是否大于所述电子围栏半径且小于第一预设阈值；
当判断所述距离大于所述电子围栏半径且小于第一预设阈值时，获取所述设备运动数据，根据所述运动数据对所述设备进或出电子围栏的状态进行预测，获取预测结果；
当所述预测结果为所述设备进入电子围栏时，对所述设备进行定位检测，获得所述设备的位置信息；根据所述位置信息判断所述设备是否已经进入电子围栏；当根据所述位置信息判断所述设备已经进入电子围栏时，发送设备进入电子围栏告警；当根据所述位置信息判断所述设备没有进入电子围栏时，继续执行获取所述设备运动数据，根据所述运动数据对所述设备进或出电子围栏的状态进行预测的操作。
本实施例中，当所述低功耗跟踪设备处于地理电子围栏外时，每次定时定位时计算与所述围栏中心的距离和相对方向，当所述距离大于所述围栏半径且小于第一预设阈值时，通过加速度传感器和方向传感器采集到的数据进行预测，当预测结果为进入围栏范围时，进行一次定位，若已进入所述围栏范围则发送进入围栏告警通知，若没有进入围栏，则继续通过上述方法进行下一次预测及定位。
进一步地，参见图4，在一实施例中，当所述预测结果为所述设备离开电子围栏，且所述电子围栏为Wi-Fi电子围栏时，开启对所述设备进或出电子围栏状态的检测包括：
步骤401：进行Wi-Fi扫描，检测所述设备是否已经离开电子围栏；
步骤402：当检测所述设备已经离开电子围栏时，发送设备离开电子围栏告警。
实际使用时，当所述低功耗跟踪设备处于Wi-Fi电子围栏中时，若首次进入围栏，则进行一次定位，并记录数据，通过加速度传感器和方向传感器采集到的数据进行预测，如果预测结果为离开Wi-Fi电子围栏，则进行Wi-Fi扫描，检测所述设备是否已经离开所述围栏，若已离开围栏范围，则向用户发离开Wi-Fi电子围栏告警通知，若没有离开围栏，则继续通过上述方法进行下一次预测及Wi-Fi扫描。
在一实施例中，当检测所述设备已经离开电子围栏时，所述方法还包括：
获取所述设备第一次进入电子围栏时的定位数据；
计算所述设备与所述定位数据之间的距离和方向；
当所述距离大于所述电子围栏的覆盖范围且小于第二预设阈值时，获取所述设备运动数 据，根据所述运动数据对所述设备进或出电子围栏的状态进行预测，获取预测结果；
当所述预测结果为所述设备进入电子围栏时，进行Wi-Fi扫描，检测所述设备是否已经进入电子围栏；当检测所述设备已经进入电子围栏时，发送设备进入电子围栏告警；当检测所述设备没有进入电子围栏时，继续执行获取所述设备运动数据，根据所述运动数据对所述设备进或出电子围栏的状态进行预测的操作。
本实施例中，当所述低功耗跟踪设备处于Wi-Fi电子围栏外时，若存在所述围栏内定位数据，每次定时定位时计算与所述围栏内定位数据的距离和相对方向，当所述距离大于所述围栏覆盖范围且小于第二预设阈值时，通过加速度传感器和方向传感器采集到的数据进行预测，当预测结果为进入所述围栏范围时进行一次Wi-Fi扫描，若已进入所述围栏范围则发送进入围栏告警通知，若没有进入围栏，则继续通过上述方法进行下一次推理及Wi-Fi扫描。
本公开实施例提供的电子围栏告警方法，读取设备运动数据；根据所述运动数据对所述设备进或出电子围栏的状态进行预测，获取预测结果；根据所述预测结果开启对所述设备进或出电子围栏状态的检测。采用本公开提供的方案能提高围栏告警灵敏度且不影响设备的功耗。
下面结合应用实施例对本公开再作进一步详细的描述。
本应用实施例提供一种低功耗追踪设备电子围栏告警方法，用于解决低功耗跟踪设备在电子围栏的处理中存在告警不及时，甚至围栏状态遗漏的问题，本实施例提供的围栏告警方法，可提高围栏告警灵敏度，同时不影响设备的功耗。
在一示例性的实施方式中，参见图5，所述低功耗跟踪设备可以包括，但不限于：加速度传感器501、方向传感器502、MCU控制模块503、GPS模块504、Wi-Fi模块505。这里，加速度传感器用于采集加速度信息，方向传感器用于采集设备运行方向信息。当然，本实施例还可以采用其他具有相同功能的组件。
图5所示的结构仅为示意，其并不对上述低功耗跟踪设备的结构造成限定。例如，低功耗跟踪设备还可包括比图5中所示更多或者更少的组件，或者具有与图5所示不同的配置。
进一步地，参见图6，所述低功耗跟踪设备的模型训练过程可以包括如下操作。
步骤601：使用所述低功耗跟踪设备移动并采集加速度传感器及方向传感器进入或离开电子围栏范围的数据。
步骤602：将采集数据作为卷积神经网络输入层，是否离开或进入电子围栏覆盖范围作为卷积神经网络输出层，进行深度学习训练。
步骤603：将训练后的模型转换为适用于微控制器的模型嵌入所述追踪设备中。
另外，参见图7，所述低功耗跟踪设备的电子围栏为地理电子围栏时，告警流程如下：
步骤701：低功耗跟踪设备在完成定位后，判断所述设备是否所处地理地址电子围栏状态是否与上一次围栏状态一致。
步骤702：若所述设备地理电子围栏状态与上一次围栏状态不一致，则向用户发送围栏状态告警通知。
步骤703：判断低功耗跟踪设备是否在地理电子围栏内。
步骤704：若所述设备处于地理电子围栏内，则对加速度传感器和方向传感器采集到的数据进行预测。
步骤705：判断预测结果是否离开围栏。
步骤706：若预测结果为离开围栏，则进行定位并检查围栏状态，若已出围栏，则发送地理电子围栏告警，否则重复步骤704、步骤705。
步骤707：若所述设备处于地理电子围栏外，判断上一次定时定位距离围栏中心的距离是否大于围栏半径且不超过预置阈值。
步骤708：若所述设备处于围栏外，距离围栏中心距离大于围栏半径且不超过预置阈值，则对加速度传感器和方向传感器采集到的数据进行预测。
步骤709：对预测结果进行判断。
步骤710：若预测结果为进入围栏，进行定位并检查围栏状态，若已进围栏，则发送电子围栏告警，否则重复步骤708、步骤709。
此外，参见图8，所述低功耗跟踪设备的电子围栏为Wi-Fi电子围栏时，告警流程如下：
步骤801：低功耗跟踪设备在完成Wi-Fi扫描后，判断所述设备是否所处Wi-Fi围栏状态是否与上一次围栏状态一致。
步骤802：若所述设备Wi-Fi电子围栏状态与上一次围栏状态不一致，则向用户发送围栏状态告警通知。
步骤803：判断所述设备是否处于Wi-Fi电子围栏内。
步骤804：判断所述设备是否有围栏位置信息。
步骤805：若所述设备处于Wi-Fi电子围栏内且没有围栏位置信息，则进行一次定位并记录围栏位置信息。
步骤806：对加速度传感器和方向传感器采集到的数据进行预测。
步骤807：预测所述设备是否离开围栏。
步骤808：若预测结果为离开围栏，则进行Wi-Fi扫描并检查围栏状态，若已离开围栏，则发送Wi-Fi电子围栏告警，否则重复步骤步骤806、步骤807。
步骤809：判断所述设备处于Wi-Fi电子围栏外，且保存过围栏位置信息。
步骤810：判断所述设备距离围栏位置距离是否超过预置阈值。
步骤811：若所述设备距离围栏距离不超过预置距离阈值，对加速度传感器和方向传感器采集到的数据进行预测。
步骤812：若预测结果为进入围栏，进行Wi-Fi扫描并检查围栏状态，若已进入围栏，则发送电子围栏告警，否则重复步骤811、步骤812。
本实施例可提高围栏告警灵敏度的同时，不影响设备的功耗。
为了实现本公开实施例的方法，本公开实施例还提供了一种电子围栏告警装置，如图9所示，电子围栏告警装置900包括：获取模块901、预测模块902和开启模块903；其中，
获取模块901，用于读取设备运动数据；
预测模块902，用于根据所述运动数据对所述设备进或出电子围栏的状态进行预测，获取预测结果；
开启模块903，用于根据所述预测结果开启对所述设备进或出电子围栏状态的检测。
实际应用时，获取模块901、预测模块902和开启模块903可由电子围栏告警装置中的处理器实现。
需要说明的是：上述实施例提供的上述装置在执行时，仅以上述各程序模块的划分进行举例说明，实际应用时，可以根据需要而将上述处理分配由不同的程序模块完成，即将终端的内部结构划分成不同的程序模块，以完成以上描述的全部或者部分处理。另外，上述实施例提供的上述装置与上述方法实施例属于同一构思，其具体实现过程详见方法实施例，这里不再赘述。
为了实现本公开实施例的方法，本公开实施例还提供了一种计算机程序产品，计算机程序产品包括计算机指令，计算机指令存储在计算机可读存储介质中。计算机设备的处理器从计算机可读存储介质读取计算机指令，处理器执行计算机指令，使得计算机设备执行上述方法的步骤。
基于上述程序模块的硬件实现，且为了实现本公开实施例的方法，本公开实施例还提供了一种电子设备(计算机设备)。在一示例性的实施方式中，在一个实施例中，该计算机设备可以是终端，其内部结构图可以如图10所示。该计算机设备包括通过系统总线连接的处理器A01、网络接口A02、显示屏A04、输入装置A05和存储器(图中未示出)。其中，该计算机设备的处理器A01用于提供计算和控制能力。该计算机设备的存储器包括内存储器A03和非易失性存储介质A06。该非易失性存储介质A06存储有操作系统B01和计算机程序B02。该内存储器A03为非易失性存储介质A06中的操作系统B01和计算机程序B02的运行提供环境。该计算机设备的网络接口A02用于与外部的终端通过网络连接通信。该计算 机程序被处理器A01执行时以实现上述任意一项实施例的方法。该计算机设备的显示屏A04可以是液晶显示屏或者电子墨水显示屏，该计算机设备的输入装置A05可以是显示屏上覆盖的触摸层，也可以是计算机设备外壳上设置的按键、轨迹球或触控板，还可以是外接的键盘、触控板或鼠标等。
本领域技术人员可以理解，图10中示出的结构，仅仅是与本公开方案相关的部分结构的框图，并不构成对本公开方案所应用于其上的计算机设备的限定，具体的计算机设备可以包括比图中所示更多或更少的部件，或者组合某些部件，或者具有不同的部件布置。
本公开实施例提供的设备，设备包括处理器、存储器及存储在存储器上并可在处理器上运行的程序，处理器执行程序时实现上述任意一项实施例的方法。
本领域内的技术人员应明白，本公开的实施例可提供为方法、系统、或计算机程序产品。因此，本公开可采用完全硬件实施例、完全软件实施例、或结合软件和硬件方面的实施例的形式。而且，本公开可采用在一个或多个其中包含有计算机可用程序代码的计算机可用存储介质(包括但不限于磁盘存储器、CD-ROM、光学存储器等)上实施的计算机程序产品的形式。
本公开是参照根据本公开实施例的方法、设备(系统)、和计算机程序产品的流程图和/或方框图来描述的。应理解可由计算机程序指令实现流程图和/或方框图中的每一流程和/或方框、以及流程图和/或方框图中的流程和/或方框的结合。可提供这些计算机程序指令到通用计算机、专用计算机、嵌入式处理机或其他可编程数据处理设备的处理器以产生一个机器，使得通过计算机或其他可编程数据处理设备的处理器执行的指令产生用于实现在流程图一个流程或多个流程和/或方框图一个方框或多个方框中指定的功能的装置。
这些计算机程序指令也可存储在能引导计算机或其他可编程数据处理设备以特定方式工作的计算机可读存储器中，使得存储在该计算机可读存储器中的指令产生包括指令装置的制造品，该指令装置实现在流程图一个流程或多个流程和/或方框图一个方框或多个方框中指定的功能。
这些计算机程序指令也可装载到计算机或其他可编程数据处理设备上，使得在计算机或其他可编程设备上执行一系列操作步骤以产生计算机实现的处理，从而在计算机或其他可编程设备上执行的指令提供用于实现在流程图一个流程或多个流程和/或方框图一个方框或多个方框中指定的功能的步骤。
在一个典型的配置中，计算设备包括一个或多个处理器(CPU)、输入/输出接口、网络接口和内存。
存储器可能包括计算机可读介质中的非永久性存储器，随机存取存储器(RAM)和/或非易 失性内存等形式，如只读存储器(ROM)或闪存(flashRAM)。存储器是计算机可读介质的示例。
计算机可读介质包括永久性和非永久性、可移动和非可移动媒体可以由任何方法或技术来实现信息存储。信息可以是计算机可读指令、数据结构、程序的模块或其他数据。计算机的存储介质的例子包括，但不限于相变内存(PRAM)、静态随机存取存储器(SRAM)、动态随机存取存储器(DRAM)、其他类型的随机存取存储器(RAM)、只读存储器(ROM)、电可擦除可编程只读存储器(EEPROM)、快闪记忆体或其他内存技术、只读光盘只读存储器(CD-ROM)、数字多功能光盘(DVD)或其他光学存储、磁盒式磁带，磁带磁磁盘存储或其他磁性存储设备或任何其他非传输介质，可用于存储可以被计算设备访问的信息。按照本文中的界定，计算机可读介质不包括暂存电脑可读媒体(transitorymedia)，如调制的数据信号和载波。
可以理解，本公开实施例的存储器可以是易失性存储器或者非易失性存储器，也可包括易失性和非易失性存储器两者。其中，非易失性存储器可以是只读存储器(ROM，Read Only Memory)、可编程只读存储器(PROM，Programmable Read-Only Memory)、可擦除可编程只读存储器(EPROM，Erasable Programmable Read-Only Memory)、电可擦除可编程只读存储器(EEPROM，Electrically Erasable Programmable Read-Only Memory)、磁性随机存取存储器(FRAM，ferromagnetic random access memory)、快闪存储器(Flash Memory)、磁表面存储器、光盘、或只读光盘(CD-ROM，Compact Disc Read-Only Memory)；磁表面存储器可以是磁盘存储器或磁带存储器。易失性存储器可以是随机存取存储器(RAM，Random Access Memory)，其用作外部高速缓存。通过示例性但不是限制性说明，许多形式的RAM可用，例如静态随机存取存储器(SRAM，Static Random Access Memory)、同步静态随机存取存储器(SSRAM，Synchronous Static Random Access Memory)、动态随机存取存储器(DRAM，Dynamic Random Access Memory)、同步动态随机存取存储器(SDRAM，Synchronous Dynamic Random Access Memory)、双倍数据速率同步动态随机存取存储器(DDRSDRAM，Double Data Rate Synchronous Dynamic Random Access Memory)、增强型同步动态随机存取存储器(ESDRAM，Enhanced Synchronous Dynamic Random Access Memory)、同步连接动态随机存取存储器(SLDRAM，SyncLink Dynamic Random Access Memory)、直接内存总线随机存取存储器(DRRAM，Direct Rambus Random Access Memory)。本公开实施例描述的存储器旨在包括但不限于这些和任意其它适合类型的存储器。
还需要说明的是，术语“包括”、“包含”或者其任何其他变体意在涵盖非排他性的包含，从而使得包括一系列要素的过程、方法、商品或者设备不仅包括那些要素，而且还包括没有明确列出的其他要素，或者是还包括为这种过程、方法、商品或者设备所固有的要素。 在没有更多限制的情况下，由语句“包括一个......”限定的要素，并不排除在包括要素的过程、方法、商品或者设备中还存在另外的相同要素。
以上仅为本公开的实施例而已，并不用于限制本公开。对于本领域技术人员来说，本公开可以有各种更改和变化。凡在本公开的精神和原理之内所作的任何修改、等同替换、改进等，均应包含在本公开的权利要求范围之内。

Claims (11)

  1. 一种电子围栏告警方法，所述方法包括：
    读取设备运动数据；
    根据所述运动数据对所述设备进或出电子围栏的状态进行预测，获取预测结果；
    根据所述预测结果开启对所述设备进或出电子围栏状态的检测。
  2. 根据权利要求1所述的方法，其中，获取设备运动数据之前，所述方法还包括：
    对所述设备进行定位检测，获得所述设备的位置信息；
    判断所述设备的位置信息是否在预设位置范围内；
    当所述设备的位置信息在预设位置范围内时，读取设备运动数据。
  3. 根据权利要求1所述的方法，其中，所述根据所述运动数据对所述设备进或出电子围栏的状态进行预测，获取预测结果，包括：
    根据所述运动数据计算所述设备行走的步数和方向；
    根据所述设备行走的步数和方向，预测所述设备进或出电子围栏的状态，获得预测结果。
  4. 根据权利要求1所述的方法，其中，所述根据所述运动数据对所述设备进或出电子围栏的状态进行预测，获取预测结果，包括：
    将所述运动数据输入训练好的预测模型中，获得所述设备进或出电子围栏状态的预测结果。
  5. 根据权利要求1所述的方法，其中，所述根据所述预测结果开启对所述设备进或出电子围栏状态的检测，包括：
    当所述预测结果为所述设备进入电子围栏或所述设备离开电子围栏时，开启对所述设备进或出电子围栏状态的检测。
  6. 根据权利要求5所述的方法，其中，当所述预测结果为所述设备离开电子围栏，且所述电子围栏为地理电子围栏时，开启对所述设备进或出电子围栏状态的检测包括：
    对所述设备进行定位检测，获得所述设备的位置信息；
    根据所述位置信息判断所述设备是否已经离开电子围栏；
    当根据所述位置信息判断所述设备已经离开电子围栏时，发送设备离开电子围栏告警。
  7. 根据权利要求6所述的方法，其中，当根据所述位置信息判断所述设备已经离开电子围栏时，所述方法还包括：
    根据所述位置信息，获取所述设备与所述电子围栏中心的距离和相对方向；
    判断所述距离是否大于所述电子围栏半径且小于第一预设阈值；
    当判断所述距离大于所述电子围栏半径且小于第一预设阈值时，获取所述设备运动数据，根据所述运动数据对所述设备进或出电子围栏的状态进行预测，获取预测结果；
    当所述预测结果为所述设备进入电子围栏时，对所述设备进行定位检测，获得所述设备的位置信息；根据所述位置信息判断所述设备是否已经进入电子围栏；当根据所述位置信息判断所述设备已经进入电子围栏时，发送设备进入电子围栏告警；或当根据所述位置信息判断所述设备没有进入电子围栏时，继续执行获取所述设备运动数据，根据所述运动数据对所述设备进或出电子围栏的状态进行预测的操作。
  8. 根据权利要求5所述的方法，其中，当所述预测结果为所述设备离开电子围栏，且所述电子围栏为Wi-Fi电子围栏时，开启对所述设备进或出电子围栏状态的检测包括：
    进行Wi-Fi扫描，检测所述设备是否已经离开电子围栏；
    当检测所述设备已经离开电子围栏时，发送设备离开电子围栏告警。
  9. 根据权利要求8所述的方法，其中，当检测所述设备已经离开电子围栏时，所述方法还包括：
    获取所述设备第一次进入电子围栏时的定位数据；
    计算所述设备与所述定位数据之间的距离和方向；
    当所述距离大于所述电子围栏的覆盖范围且小于第二预设阈值时，获取所述设备运动数据，根据所述运动数据对所述设备进或出电子围栏的状态进行预测，获取预测结果；
    当所述预测结果为所述设备进入电子围栏时，进行Wi-Fi扫描，检测所述设备是否已经进入电子围栏；当检测所述设备已经进入电子围栏时，发送设备进入电子围栏告警；当检测所述设备没有进入电子围栏时，继续执行获取所述设备运动数据，根据所述运动数据对所述设备进或出电子围栏的状态进行预测的操作。
  10. 一种电子设备，包括：处理器和用于存储能够在处理器上运行的计算机程序的存储器；其中，所述处理器用于运行所述计算机程序时，执行权利要求1至9任一项所述方法的步骤。
  11. 一种存储介质，所述存储介质中存储有计算机程序，其中，所述计算机程序被处理器执行时，实现权利要求1至9任一项所述方法的步骤。
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