WO2023020259A1

WO2023020259A1 - Geofence control method and apparatus, storage medium, and electronic device

Info

Publication number: WO2023020259A1
Application number: PCT/CN2022/109000
Authority: WO
Inventors: 谭志鹏
Original assignee: 上海瑾盛通信科技有限公司
Priority date: 2021-08-20
Filing date: 2022-07-29
Publication date: 2023-02-23
Also published as: CN113779166A; CN113779166B

Abstract

Provided are a geofence control method and apparatus, a storage medium, and an electronic device. The method comprises: determining a target service operation for a geofence (S101), and controlling a low-power-consumption controller to respond to the target service operation, and performing fence service processing on the geofence (S102). By using embodiments of the present application, the power consumption of a geofence service can be reduced.

Description

Geo-fence control method, device, storage medium and electronic equipment

This application claims the priority of the Chinese patent application filed on August 20, 2021, with application number 2021109618813, and the title of the invention is "geo-fence control method, device, storage medium and electronic equipment", the entire content of which is incorporated by reference In this application.

technical field

The present application relates to the field of computer technology, and in particular to a geofence control method, device, storage medium and electronic equipment.

Background technique

With the rapid development of communication technologies, some electronic devices have functions for providing location-based services. For example, when an electronic device enters or exits a geo-fence, the electronic device may execute related geo-fence services. For example, when a user chooses public transportation such as subways and buses to travel, the geofence-based arrival service can be turned on, and when the user of the electronic device arrives at the station, the geofence service can be triggered for arrival reminders.

Contents of the invention

The embodiment of the present application provides a geofence control method, device, storage medium and electronic equipment, and the technical solution is as follows:

In the first aspect, the embodiment of the present application provides a geofence control method, the method comprising:

Identify targeted business operations for geofencing;

controlling the low power consumption controller to perform fence service processing on the geo-fence in response to the target service operation, and the power consumption of the low power consumption controller is less than that of the application processor.

In the second aspect, the embodiment of the present application provides a geofence control device, the device comprising:

A business determination module for determining target business operations for geofences;

A service processing module, configured to control the low power consumption controller to perform fence service processing on the geo-fence in response to the target service operation.

In a third aspect, an embodiment of the present application provides a computer storage medium, where a plurality of instructions are stored in the computer storage medium, and the instructions are adapted to be loaded by a processor and execute the above method steps.

In a fourth aspect, an embodiment of the present application provides an electronic device, which may include: a processor and a memory; wherein, the memory stores a computer program, and the computer program is adapted to be loaded by the processor and execute the above-mentioned method steps .

The beneficial effects brought by the technical solutions provided by some embodiments of the present application at least include:

In one or more embodiments of the present application, the electronic device can determine the target business operation for the geo-fence (business operations for geo-fence registration, geo-fence detection, geo-fence update, etc.) by controlling the low-power controller to respond For the target service operation, the low power consumption controller acts as the main processor that responds to the operation to perform fence service processing on the geo-fence. By using the low-power controller in the low-power environment as the main processor, the geo-fence detection and processing work is executed in the low-power environment, and the geo-fence business processing is realized with the low-power controller as the main processor, so as to save and The power consumption of geofence services related to geofences, and at the same time optimize the business response process based on application processor-based operation response in related technologies.

Description of drawings

In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the following will briefly introduce the drawings that need to be used in the description of the embodiments or the prior art. Obviously, the accompanying drawings in the following description are only These are some embodiments of the present application. Those skilled in the art can also obtain other drawings based on these drawings without creative work.

Fig. 1 is a schematic flow chart of a geo-fence control method provided by an embodiment of the present application;

Fig. 2 is a schematic flow chart of another geo-fence control method provided by the embodiment of the present application;

FIG. 3 is a schematic diagram of a fence detection scene involved in the present application;

FIG. 4 is a schematic diagram of another fence detection scene involved in the present application;

Fig. 5 is a schematic flow chart of another geo-fence control method provided by the embodiment of the present application;

FIG. 6 is a schematic structural diagram of a geofence control device provided in an embodiment of the present application;

FIG. 7 is a schematic structural diagram of a service processing module provided by an embodiment of the present application;

FIG. 8 is a schematic structural diagram of an electronic device provided by an embodiment of the present application;

FIG. 9 is a schematic structural diagram of an operating system and user space provided by an embodiment of the present application;

Fig. 10 is an architecture diagram of the Android operating system in Fig. 8;

FIG. 11 is a structural diagram of the IOS operating system in FIG. 8 .

Detailed ways

The following will clearly and completely describe the technical solutions in the embodiments of the application with reference to the drawings in the embodiments of the application. Apparently, the described embodiments are only some of the embodiments of the application, not all of them. Based on the embodiments in this application, all other embodiments obtained by persons of ordinary skill in the art without making creative efforts belong to the scope of protection of this application.

In the description of the present application, it should be understood that the terms "first", "second" and so on are used for descriptive purposes only, and should not be understood as indicating or implying relative importance. In the description of the present application, it should be noted that, unless otherwise specified and limited, "including" and "having" and any variations thereof are intended to cover non-exclusive inclusion. For example, a process, method, system, product or device comprising a series of steps or units is not limited to the listed steps or units, but optionally also includes unlisted steps or units, or optionally further includes For other steps or units inherent in these processes, methods, products or devices. Those of ordinary skill in the art can understand the specific meanings of the above terms in this application in specific situations. In addition, in the description of the present application, unless otherwise specified, "plurality" means two or more. "And/or" describes the association relationship of associated objects, indicating that there may be three types of relationships, for example, A and/or B may indicate: A exists alone, A and B exist simultaneously, and B exists independently. The character "/" generally indicates that the contextual objects are an "or" relationship.

The present application will be described in detail below in conjunction with specific embodiments.

In one embodiment, as shown in FIG. 1 , a geo-fence control method is proposed, which can be realized by relying on a computer program and can run on a geo-fence control device based on the von Neumann system. The computer program can be integrated in the application, or run as an independent utility application. The geofence control device may be a terminal device, including but not limited to: personal computer, tablet computer, handheld device, vehicle device, wearable device, computing device or other processing device connected to a wireless modem. Terminal equipment can be called by different names in different networks, for example: user equipment, access terminal, subscriber unit, subscriber station, mobile station, mobile station, remote station, remote terminal, mobile device, user terminal, terminal, wireless communication Devices, user agents or user devices, cellular phones, cordless phones, terminal equipment in 5G networks or future evolution networks, etc.

Specifically, the geofence control method includes:

S101: Determine a target business operation for the geo-fence.

Geo-fencing is an application of Location Based Services (LBS), which can be understood as using a virtual fence to enclose a virtual geographic boundary. When a moving electronic device enters or leaves a geographic area corresponding to a certain geographic fence, or moves within the geographic area, the electronic device can automatically receive service messages. In this application, when the user enters the geofence range corresponding to the geographic object with an electronic device on a vehicle, the geofence service of the electronic device is triggered at this time, such as a notification service, such as pushing merchant information within the geofence.

The target business operation can be understood as the operation of the fence business for the geo-fence (service). The target business operation is not limited to the human-computer interaction operation triggered by the user for the corresponding fence business, and can also be performed by the user on the electronic device. Applications that subscribe to or associate with geofence services automatically trigger target business operations based on application development logic, such as data update operations for geofences.

Further, the fence business of the target business operation for the geo-fence includes but is not limited to the geo-fence registration business, the geo-fence detection business, the geo-fence update business, the geo-fence trigger business, the geo-fence management business, the geo-fence detection business, etc., based on The actual application environment is determined.

In this application, the target business operation for the geofence is usually triggered in the application processor included in the electronic device, and the electronic device can obtain the active triggering by the user of the electronic device and/or the application carried by the electronic device through the application processor. Targeted business operations for geofences.

For example, the electronic device runs an operating system (such as Android system, ios system, etc.) Enter target business operations such as geofence registration, geofence update, geofence activation, etc.;

Another example is "application software coupled with geofence service or business", as a service applicant, you can subscribe to geofence service in (application), and the application software is based on the service request of geofence service (such as fence registration service request, fence update service request) , can automatically trigger target business operations such as geofence registration, geofence update, and geofence opening based on internal application development logic. In some implementations, it will involve obtaining corresponding services from the network side (such as cloud server) data.

In a specific implementation scenario, the electronic device obtains the fence service request of at least one application on the application processor, and then analyzes the fence service request to determine the target business operation for the geofence based on the fence service request, such as Determine geofence update operations for geofences based on geofence update requests, determine geofence registration operations for geofences based on geofence registration requests, determine geofence enable operations for geofences based on geofence open requests, geofence detection requests Identify geofence detection actions for geofences, and more.

Wherein, the application processor (Application Processor, AP): an application processor on an electronic device, on which an operating system (such as an Android system, an ios system, etc.), various application software, and a user interface run.

In related technologies, in the business operation scenarios involving geo-fences, such as geo-fence update, geo-fence detection, etc., the application processor is usually used as the main processor, that is to say, complex data related to geo-fence business operation scenarios All or most of the processing is handled by the application processor. Even if it involves a low-power controller (which can be SensorHub) to obtain relevant underlying sensor data in the geofencing business, the low-power controller only realizes the sensing data The preliminary processing of the algorithm, while the final complex algorithm data processing such as algorithm application is performed on the application processor side. The difference in this application is that since the power consumption of the application processor is usually much higher than that of the low-power controller, in order to reduce the power consumption of the geo-fence, the geo-fence control method involved in this application uses a low-power controller ( It can be SensorHub) as the main processor, and responds to the target business operations involved in the geo-fence control method mainly in the low-power controller, thereby changing the operation response logic in related technologies, such as complex data processing related to the aforementioned business operation scenarios All or most of the process, the complex data processing process can immediately be the algorithm data processing process related to business operations, such as location positioning algorithm, fence matching algorithm and so on.

S102: Control the low power consumption controller to perform fence service processing on the geo-fence in response to the target service operation.

Wherein, the power consumption of the low power consumption controller included in the electronic device is usually lower than the power consumption of the application processor.

Specifically, after the electronic device determines the target service operation based on the application processor, the subsequent operation response process performs operation response control, and the process of responding to the operation is moved down to the low-power consumption controller in the low-power consumption environment for response through the operation response. That is to say, the response process of the entire target business operation uses the low-power controller as the main processor for response processing. Further, different target business operations correspond to the relevant business operation response process; based on the target business operation corresponding to the relevant business operation response process The response can be completed by executing the relevant processing task. In specific implementation, the electronic device controls the low power consumption controller to execute the target processing task corresponding to the target service operation in response to the target service operation. The target processing task is related to the target service operation. The business processing tasks corresponding to the business operation response process. In some embodiments, the target processing tasks include at least a geo-fence registration task, a geo-fence detection task, a geo-fence update task, a geo-fence trigger task, a geo-fence management task, a geo-fence One of the detection tasks.

Schematically, taking the geofence registration task as an example, it may at least include the following aspects:

1. Electronic devices can obtain latitude and longitude data provided by service applicants (such as users and applications) through low-power controllers. It can be latitude and longitude coordinates and radius, and can be closed fence data composed of multiple latitude and longitude coordinates.

2. Control the low-power controller in the included independent operating system (operating systems such as Android on non-application processors): record latitude and longitude data;

3. The low-power controller checks whether the latitude and longitude data has related network cache data in the included independent operating system (which can save the traffic cost caused by network query), and the network cache data can be understood as the corresponding data of the latitude and longitude data. Signal identification (the position of the electronic device is determined based on the correspondence between the signal identification and the geographic location). The signal identifier may be a network signal identifier based on a base station (which may be understood as a base station identifier), or may be a signal identifier of a current radio frequency identifier, such as a WiFi signal identifier.

4. If the above-mentioned network cache data does not exist, the low-power controller queries the cloud network side for the relevant network geo-fence data of the area in the included independent operating system, that is, the network geo-fence data, such as directly to the network side to obtain geofence data, or electronic devices can trigger the application processor to obtain geofence data from the network side through a low-power controller, etc. The geofence data can be based on the longitude and latitude fence data of the global positioning system satellite network; it can be based on The fence data corresponding to the virtual border created by the radio frequency identifier this time, such as WiFi geofence data.

5. The low-power controller creates the current geo-fence object based on the aforementioned network geo-fence data in the included independent operating system, and feeds the geo-fence object back to the service applicant.

Based on the above interpretation, when an electronic device performs a geofence registration task, it does not adopt the technical concept of using the application processor as the main processor in the related technology, but uses a low-power controller in a low-power environment as the main processor. Execute all or most of the fence registration data processing work in a low-power environment, focusing on low-power controllers. If it is not necessary, do not call or trigger the application processor to save power consumption related to geo-fence fence registration .

Schematically, taking the geofence update task as an example, it may at least include the following aspects:

1. In practical applications, the geofence can correspond to a data expiration period. The low-power controller regularly queries the corresponding network geofence data from the network side through the independent operating system according to the data expiration period specified by the service applicant, and triggers the process regularly. Including but not limited to: obtaining the network geo-fence data directly from the network side, or the electronic device can trigger the application processor to obtain the network geo-fence data from the network side through the low-power controller.

2. After querying the new network geofence data, update the network geofence data on the original data at the storage location corresponding to the geofence.

Based on the above interpretation, when an electronic device performs a geofence update task, the low-power controller in a low-power environment is used as the main processor, and all or most of the geo-fence update processing is performed in a low-power environment. The low-power controller is the main one, and if it is not necessary, it does not call or trigger the application processor to work, so as to save the power consumption of the fence update related to the geo-fence.

Schematically, taking the geofence management task as an example, it may at least include the following aspects:

1. The low-power controller obtains the object identifier of a service applicant (which can be an application on the application processor) for a certain geo-fence object, usually it can be that the service applicant requests to perform corresponding operations on the geographic location (modify, delete, start, stop, etc.)

2. The independent system of the low-power controller performs corresponding operations on the corresponding geographical fence determined based on the object identifier according to the operation command of the service applicant:

For example: to modify a geo-fence that has been activated, the independent system of the low-power controller directly responds to the modification command to modify the data of the geo-fence that has been activated, such as modifying the range of the geo-fence, after the modification is completed, it can directly take effect to realize the activated geo-fence Geofence hot modification.

For example: to delete an activated geofence, the independent system of the low power controller directly responds to the deletion command to stop the geofence and release the relevant geofence data.

For example: start a geo-fence, the independent system of the low-power controller directly responds to the start command, and starts to locate and detect whether the conditions represented by the fence are met, such as whether the time and location of the geo-fence start are met.

Based on the above definition, when an electronic device performs a geo-fence management task, the low-power controller in a low-power environment is used as the main processor, and all or most of the geo-fence management processing is performed in a low-power environment. The low-power controller is the main one, and if it is not necessary, it does not call or trigger the application processor to work, so as to save the power consumption of the fence management related to the geo-fence.

Schematically, taking the geofence detection task as an example, it may at least include the following aspects:

1. The independent system of the low-power controller queries the current network base station signal according to the detection frequency specified by the geo-fence

2. The independent system of the low-power controller performs matching to determine the geographic location corresponding to the network base station signal according to the queried network base station signal and the registered network positioning database (collective data representing the corresponding relationship between a large number of base station signal identifiers and actual base station locations); Network base station signals are often composed of LAI (Location Area Identification)+CID (Cell Identity), and LAI is composed of (MCC+MNC+LAC). Among them, the full name of MCC is Mobile Country Code, a three-digit mobile country code, such as 460 in China. MNC full name Mobile Network Code, mobile network number, two digits. The full name of LAC is Location Area Code, which is a 2-byte hexadecimal BCD code (excluding 0000 and FFFE). Cell Identity is also a 2-byte hexadecimal BCD code. Determine the rough geographic location corresponding to the network base station signal (usually the location obtained by the base station positioning method is not accurate, it is often a rough location, and the subsequent detection of the precise geographic location of the geo-fence needs to enable the relevant positioning technology);

3. The independent system of the low-power controller matches the position corresponding to the appropriate network base station signal, and then triggers the precise positioning technology (such as satellite positioning and wifi positioning) involved in the subsequent geo-fence, and initiates the corresponding operation according to the type of geo-fence , the scene geofence type can be longitude and latitude fence, wifi fence;

(1) For longitude and latitude type fences, the low-power controller controls the positioning module to start timing satellite positioning to obtain accurate positions, and then judges whether the position falls within the position range of the geo-fence

(2) For the wifi type fence, the low-power controller queries the wifi data that needs to be compared to determine the location corresponding to the WiFi signal identification, and then judges whether the location falls within the location range of the geofence;

4. If the location falls within the location range of the geo-fence, the low-power controller triggers a fence reporting process, which may be to trigger the application processor to perform a fence reminder.

It should be noted that the above-mentioned geo-fence tasks are just examples and explanations, and do not limit the specific processes involving geo-fence tasks, and the specific processes of related geo-fence tasks can be set based on actual application conditions.

Based on the above definition, when an electronic device performs a geofence detection task, the low-power controller in a low-power environment is used as the main processor, and all or most of the geo-fence detection processing is performed in a low-power environment. The low-power controller is the main one. If it is not necessary, it does not call or trigger the application processor to work, so as to save the power consumption of the fence detection related to the geo-fence.

In the embodiment of the present application, the electronic device can determine the target business operation for the geo-fence (business operations for geo-fence registration, geo-fence detection, geo-fence update, etc.) by controlling the low-power controller to respond to the target For business operation, the low power consumption controller acts as the main processor of the operation response to perform fence business processing on the geo-fence. By using the low-power controller in the low-power environment as the main processor, the geo-fence detection and processing work is executed in the low-power environment, and the geo-fence business processing is realized with the low-power controller as the main processor, so as to save and The power consumption of geofence services related to geofences, and at the same time optimize the business response process based on application processor-based operation response in related technologies.

Please refer to FIG. 2 . FIG. 2 is a schematic flowchart of another embodiment of a geofence control method proposed by the present application. specific:

S201: Obtain a fence service request on an application processor, and determine a target service operation for a geofence based on the fence service request.

According to some embodiments, the application processor (Application Processor, AP) refers to the application processor on the electronic device; the application processor runs the operating system (such as Android system, ios system, etc.), various application software and user interface, the fence service request on the application processor can be understood as being obtained from the application service running on the application processor, and the application service can be understood as the service corresponding to the application software on the application processor; for example, the appearance service corresponding to the map application , the push service corresponding to the shopping application, the food delivery service corresponding to the food delivery application, etc., these applications can subscribe to or associate with the geofence service on the application processor.

When a fence service is requested, it is a service request triggered by a fence service on a geofence. The fence service includes but is not limited to a geofence registration service, a geofence detection service, a geofence update service, a geofence trigger service, a geofence management service, and a geofence Detection services, etc., are determined based on the actual application environment.

In this application, the fence service request for the geo-fence is usually triggered in the application processor included in the electronic device, through which the electronic device can obtain the geo-fence request actively triggered by the application carried by the user operation of the electronic device. Fence service requests for geofences.

According to some embodiments, the electronic device acquires the fence service request of at least one application on the application processor, and then analyzes the fence service request to determine the target business operation for the geo-fence based on the fence service request, such as based on the geo-fence The update request determines the geofence update operation for geofences, the geofence registration operation determines the geofence registration operation for geofences, the geofence open operation determines the geofence open operation for geofences based on the geofence open request, and the geofence detection operation determines the geofence Geofence detection operations for fences and more.

S202: In response to the target service operation, control the low power consumption controller to acquire geofence data from the application processor;

The low-power controller is a low-power device. The power consumption of the low-power controller in the working state is much lower than that of the application processor of the electronic device. The low-power controller can at least include an intelligent sensor hub, Some digital signal processors, etc.; low-power controllers are used to deploy algorithm data corresponding to geo-fence services. In practical applications, low-power controllers are used to implement independent processing of "geo-fence" services without relying on application processors. , that is to say, the low-power controller is used as the main processor, and the low-power controller responds to geofence-related operations first, and the low-power controller provides a low-power environment.

In some implementations, the low-power controller can be a smart sensor hub (SensorHub), or a dedicated digital signal processor, such as a dedicated audio digital signal processor (ADSP). In some scenarios, the low-power controller Also known as sensor hub, sensor control center and so on. The low-power controller is associated with multiple sensors (Sensors) of electronic devices, such as distance sensors, light sensors, gyroscopes, and so on. With the iterative update of sensor technology, the power consumed by the sensors corresponding to the sensor hub is constantly decreasing, which makes it possible for electronic devices to detect more so-called environmental status information in real time, that is, no matter whether the electronic device is Whether working or standby, the energy cost consumed by sensors that continuously read environmental data such as acceleration, direction, coordinates, temperature, air pressure, and magnetic field is close to zero. In this application, the algorithm data related to the business process of geofencing can be deployed on SensorHub.

After the electronic device determines the target business operation based on the application processor, the subsequent operation response process performs operation response control, and the process of responding to the operation is moved down to the low-power consumption controller in the low-power environment for response through the operation response, that is to say, the entire The response process of the target business operation uses the low-power controller as the main processor to perform response processing, and try to avoid or avoid the application processor from participating in the geo-fence business. When it comes to geo-fence business scenarios, it is usually necessary to obtain information for The geofence data of the follow-up geofence detection task, the geofence data can be understood as the data required to construct the geofence, and can also be understood as the network geofence data, the geofence data can be the longitude and latitude fence data based on the global positioning system satellite network ; It can be the fence data corresponding to the virtual boundary created around the location based on the radio frequency identifier this time, such as WiFi geofence data.

In the embodiment of the present application, the difference from the related technology is that after the target business operation is determined, the electronic device does not use the application processor to respond but transfers to the low-power controller based on the target business operation. In actual implementation, If the target business operation is triggered on the application of the application processor, it is determined that it is a business operation related to geofencing, and the application processor transfers the business operation to the low-power controller. The application processor does not respond to the target business operation but only Preliminary operation type judgment can be made. The low-power controller responds to the above-mentioned target business operations, and the low-power controller is used as the main processor for processing. When it comes to data interaction scenarios from the network side, the low-power The consumption controller triggers the application processor to obtain relevant interaction data from the network by responding to the target business operation, that is to say, in the whole process involving the application processor, the application processor is only used as an auxiliary The coprocessor of the low-power controller in the scenario assists in processing geofence-related services.

Further, in this embodiment, how to implement geo-fence detection based on the acquired geo-fence data will be explained below. Generally, the electronic device can control the low-power controller to perform geo-fence positioning based on the geo-fence data in a low-power positioning mode. Please refer to the following explanations for the specific steps and execution process.

S203: Obtain network location data and a mode trigger condition of the low-power positioning mode;

When it comes to geo-fence detection, the low-power controllers of electronic devices usually need to frequently detect the location of electronic devices during travel or movement. Long-term positioning technologies based on high power consumption, such as satellite navigation and positioning technology, will improve geo-fence Controlled power consumption. In this application, in order to control the power consumption related to geo-fences and save the power of electronic devices, the algorithm processing involved in the entire geo-fence detection is moved down to the low-power controller. When it comes to location positioning , to obtain the network location based on the network signal of the electronic device, that is, to obtain the network location data, and the network location data is based on the signal identification of the site (such as a base station) to achieve positioning,

In the specific implementation, relying on the electronic device to call the modem through the low-power controller to obtain the signal of the nearby network base station, the network base station signal is often composed of LAI (Location Area Identification) + CID (Cell Identity), and the LAI is composed of (MCC + MNC + LAC )composition. Among them, the full name of MCC is Mobile Country Code, a three-digit mobile country code, such as 460 in China. MNC full name Mobile Network Code, mobile network number, two digits. The full name of LAC is Location Area Code, which is a 2-byte hexadecimal BCD code (excluding 0000 and FFFE). The Cell Identity cell identification code is also a 2-byte long hexadecimal BCD code. Since the "aggregate data of the corresponding relationship between a large number of base station signal identifiers and actual base station locations" is obtained from the network side in advance, it can also be understood as a network positioning database, and then the network base station signals are matched with the base station signal identifiers in the network positioning database to determine the The matching target base station signal identification, and then the actual location corresponding to the target base station signal can be used as a kind of network location data, usually the rough geographic location corresponding to the network base station signal determined (usually the position accuracy obtained by means of base station positioning is not high, often It is a rough location, and the follow-up involves precise location detection of geofences, which need to enable related positioning technologies);

The low-power positioning mode can be understood as a high-precision and low-power positioning method based on the corresponding positioning technology through modular technology, and the location accuracy of the location data obtained by using the low-power location mode is higher than that of the network location data.

In some implementations, the low-power positioning mode is a high-precision position obtained by a first positioning method such as a satellite navigation system (GNSS) as a reference, and the second positioning method is used to target the high-precision position as a reference Position reckoning or dead reckoning of at least one second position data during the movement of the electronic device, such as the second positioning method may be a position acquisition technology using a neural network or dead reckoning, so that a high-precision position can be obtained, and Since the position estimation process is only based on the sensory data sensed by the sensor, it can greatly save power consumption of the device while meeting the position accuracy acquisition requirements.

The low-power positioning mode is different from the related technologies that only obtain high-precision positions based on satellite positioning and wifi positioning such as satellite navigation systems. In the low-power positioning mode, the first positioning method such as GNSS positioning does not need to be activated in real time. Only based on the first positioning method such as GNSS positioning to obtain the reference position as the reference base station, and then perform position estimation through the second positioning method such as "pedestrian dead reckoning fusion based on neural network". During the position estimation process, the first positioning method The corresponding positioning module can enter sleep mode. Therefore, the power consumption of high-precision positioning is saved. On the other hand, considering the actual application situation, deploying high-precision geo-fence detection and other geo-fence services on low-power chips is limited by the fact that the processing capability of low-power controllers is weaker than that of application processors, while high-precision Geo-fencing services such as fence positioning usually consume a lot of power and require a lot of calculations. In order to protect and reduce the power consumption of low-power controllers, it is necessary to avoid the first positioning method with high power consumption for a long time.

The mode trigger condition is the activation condition for the low-power positioning mode; the mode trigger condition can be the network positioning duration estimated based on the geofence object, such as the estimated time for the electronic device to reach the adjacent geofence range at the initial stage, and the time As the network positioning duration, the condition can be: the current positioning duration satisfies the network positioning duration. It is understandable that the high-precision low-power positioning mode is only turned on when it is close to the geofence range; the mode trigger condition can be set based on the distance between the geofence objects , for example, after the network positioning data is obtained, the condition can be: calculate the distance between the position indicated by the network positioning data and the coverage area of the geofence, and the distance needs to meet the interval distance before enabling the low-power positioning mode; the mode trigger condition can be based on geography At least one adjacent geographic location set by the fence object, the condition may be: the location indicated by the network positioning data matches the aforementioned adjacent geographic location, if the distance between the two is smaller than the distance threshold, the two are considered to match, and so on.

As shown in Figure 3, Figure 3 is a schematic diagram of a fence detection scene involved in this application. The target site corresponding to the travel route obtained by the electronic device is the "Gaobeidian site" in Figure 3, and the user of the electronic device is riding as shown in the figure. The rail vehicle shown is from the starting station "Jiukeshu", and the electronic equipment is traveling from the starting station "Jiukeshu" to the "Gaobeidian station", and the electronic equipment is traveling on the transportation vehicle In the early stage, the network positioning method (such as the base station positioning method) is used to obtain the network positioning data, and every time the network positioning data is continuously obtained during the travel process, it is judged whether the network position data matches the trigger condition of the mode. The trigger condition of the mode is Based on the distance to the destination site being three sites, that is, the low power consumption positioning mode can be turned on only when the “Guanzhuang” site as shown in FIG. 3 needs to be reached.

Further, as shown in FIG. 4, FIG. 4 is a schematic diagram of another fence detection scene involved in the present application. FIG. 4 reflects the way of fence detection at each stage in FIG. 3, and the electronic device in FIG. 4 is the device shown in 302 , starting from the starting site "Nine Trees", the electronic device 302 continues to use the network positioning method for positioning, and when it reaches the "Guanzhuang" site as shown in Figure 3, the electronic device 302 turns on the low-power positioning mode and continues to perform geo-fencing Detection, detecting whether the electronic device 302 has entered the range corresponding to the geographic fence of the destination site, when the electronic device enters the geographic range of the destination site, the geo-fence trigger service is executed, as shown in Figure 4, a reminder can be made, the electronic The device 302 outputs prompt information as shown at 310 in FIG. 4 .

S204: If the network location data matches the mode trigger condition, control the low power consumption controller to acquire device location data in a low power consumption positioning mode based on the geofence data.

In a feasible implementation, the time when the electronic device arrives near the geographic fence is estimated at the initial stage, and this time is used as the network positioning duration. If the time of the location data is equal to or greater than the network positioning duration, it is considered that the network location data matches the mode trigger condition.

In a feasible implementation, the mode triggering condition may be: calculate the distance between the position indicated by the network positioning data and the coverage area of the geofence, and the distance needs to meet the separation distance; When the distance of the range is equal to or less than the separation distance, it is determined that the network location data matches the mode trigger condition.

In a feasible implementation manner, the mode trigger condition may be at least one nearby geographic location set based on the geofence object, and the condition may be: the location indicated by the network positioning data matches the aforementioned nearby geographic location; that is to say, the location indicated by the network positioning data When the location of is close to the geographic location, it is determined that the network location data matches the pattern trigger condition.

It should be noted that the foregoing mode trigger conditions may be set based on actual application conditions, and are not specifically limited in this application.

The following explains the low power consumption positioning mode involved.

According to some embodiments, the low-power positioning mode is a positioning mode based on a first positioning method such as a satellite navigation system (GNSS) for high-precision position acquisition as a reference and neural network-based pedestrian dead reckoning fusion positioning mode, and In the related art, only based on satellite positioning such as satellite navigation system to obtain high-precision position, the low power consumption positioning mode does not need to start the first positioning method such as GNSS positioning in real time, but only based on the first positioning method such as GNSS positioning. The starting position is subsequently calculated through "neural network-based pedestrian dead reckoning fusion". During the position calculation process, the positioning module corresponding to the first positioning method can enter the sleep mode. Thereby saving the power consumption of high precision positioning. On the other hand, deploying high-precision fence positioning on low-power chips is limited by the fact that the processing power of low-power controllers is weaker than that of application processors, and high-precision fence positioning usually consumes a lot of power and requires less calculation. Large, in order to protect the low-power controller and reduce the power consumption of the low-power controller, it is necessary to avoid the first positioning method of high power consumption for a long time.

In this application, the first positioning method may be a satellite positioning method, a wireless fidelity (Wireless Fidelity, Wi-Fi) based positioning, an ultra wide band (Ultra WideBand, UWB) positioning and other LBS-based high-precision positioning technology.

In this application, the low power consumption positioning mode can be at least divided into a first positioning phase and a second positioning phase;

1. (In the first positioning stage) the electronic device controls the low-power controller to obtain the first location data of the electronic device in a first positioning manner;

The first location data is high-precision location data obtained by the electronic device controlling the low-power controller using the first positioning method. It can be understood that the location accuracy of the first location data is greater than that of the network location data in some embodiments. Accuracy, such as the use of satellite positioning technology, Wi-Fi positioning technology, etc.

In this application, the first positioning method is turned on only to obtain at least one or a small amount of high-precision first position data as a reference point. After the acquisition, the positioning module corresponding to the first positioning method can be controlled to enter a sleep state or an off state. To save power consumption for geofence detection. In the subsequent second positioning stage, based on the pedestrian navigation calculation and fusion method using neural network: using the first position data as a reference, determine at least one subsequent second position data for the electronic device during the position change process of the electronic device.

2. (In the second positioning stage) the electronic device controls the low-power controller to obtain at least one second position data for the electronic device based on the first position data in a pedestrian navigation calculation and fusion method using a neural network.

The second location data is obtained by the electronic device controlling the low-power controller with reference to the first location data and the sensory data obtained by the low-power controller using neural network to obtain pedestrian navigation reckoning fusion. It is a position determination technology based on the first position data for position tracking calculation.

Specifically, the electronic device controls the low-power controller to call the sensor to collect sensing data. In the specific implementation, the mobile acceleration data based on the first position data can be obtained. It can be understood that after the first position data is determined by the first positioning method, the Sleep the positioning module corresponding to the first positioning mode, and then acquire the subsequent mobile acceleration data of each sampling period during the movement of the electronic device, the acceleration data is the acceleration in at least one specified direction of the electronic device, such as by accelerometer, gyroscope Acceleration in specified directions such as front, rear, left, right, up, and down of electronic equipment can be obtained by sensor devices such as instrumentation and magnetometers.

Further, the electronic device controls the low-power controller to input the moving acceleration data into the neural network-based navigation calculation model, and output the moving speed data; then determine the position and displacement data based on the moving speed data. In specific implementation, based on The moving speed data and the sampling interval time can be integrated to obtain the position displacement data.

The electronic device controls the low-power controller to perform data accumulation processing based on the first position data and the position displacement data, so as to determine the second position data for the electronic device;

Further, the continuous position determination during the moving process of the electronic device can be realized based on the aforementioned method, the electronic device actually uses the second position data as the next first position data, and then performs the acquisition based on the first position data. The steps to move the acceleration data are sufficient. In this way, the loop is executed,

That is to say, within each sampling interval time ti ((i is a positive integer), the displacement data si can be determined based on the mobile acceleration data ai, and then cumulative processing is performed based on the first position data and displacement data si (that is, in the first Accumulated displacement si on the coordinate point corresponding to the position data, obtain the coordinate point corresponding to the second position data), and obtain the second position data corresponding to the sampling interval time ti. Further, the electronic device can be executed cyclically based on the aforementioned method, thereby determining each Sampling the corresponding second position data within the interval ti realizes the continuous positioning of the electronic device during the second positioning phase.

The following is an interpretation of the neural network-based navigation reckoning model involved in this application. Based on the above interpretation, it can be understood that the pedestrian dead reckoning involved in this application is different from the single prediction calculation using a fixed formula in the related art. The involved pedestrian navigation calculation fusion method using neural network can greatly improve the position positioning accuracy of the PDR algorithm and reduce positioning errors.

In specific implementation, the navigation reckoning model may be obtained after model training after constructing an initial model based on a neural network;

In a specific implementation, the navigation reckoning model can be pre-trained, and a large amount of sample data including acceleration parameters in the actual mobile scene of the electronic device is obtained in advance, and the above sample data is input into the navigation reckoning model for training, and the moving speed is output. The navigation reckoning model It is trained from multiple sample data corresponding to known labeled sample velocities.

Specifically, by obtaining a large amount of sample data in various types of mobile scenarios (such as running, walking, riding, etc.) from the actual application environment in advance, feature information is extracted, and the sample data is marked, and the feature information includes An initial navigation reckoning model is created for the acceleration in a specified direction (for example, for accelerations in specified directions such as front, rear, left, right, up, and down) of the electronic device. Described navigation calculation model can be to use a large amount of sample data to train initial navigation calculation model, can be based on LR (Logistic Regression, logistic regression model), SVM (Support Vector Machine, support vector machine) as navigation calculation model, One of decision tree, naive Bayesian classifier, CNN (Convolutional Neural Network, convolutional neural network), RNN (Recurrent Neural Networks, recurrent neural network), deep neural network (Deep Neural Network, DNN) model, etc. or Various implementations, the initial navigation reckoning model is trained based on sample data that has been labeled (marked moving speed), and a trained navigation reckoning model can be obtained.

Schematically, in this embodiment, the DNN-ResNet model that introduces the error backpropagation algorithm is used to create the initial navigation calculation model. After extracting the feature information, the feature information is input into the neural network model in the form of feature vectors, and the Training, training to complete the production navigation reckoning model;

In some implementations, the training process of the neural network model usually consists of two parts: forward propagation and back propagation. During the forward propagation process, the feature information corresponding to the terminal input sample data passes through the hidden After the transfer function (also known as activation function, conversion function) of layer neurons (also called nodes) is calculated, it is transmitted to the output layer, where the state of neurons in each layer affects the state of neurons in the next layer, and the actual output value is calculated in the output layer - the first voice mark, calculate the expected error between the actual output value and the expected output value, adjust the parameters of the neural network model based on the expected error, the parameters include the weight value and threshold of each layer, after the training is completed , generating a navigation reckoning model.

In a feasible implementation manner, in the above-mentioned (in the second positioning stage), the pedestrian navigation calculation and fusion method using the neural network is used to locate the second position data in the moving process, because the second position data is essentially a kind of position calculation In this way, there will be a process of error accumulation between the coordinates of the second position data and the real coordinates of the accumulated dead reckoning over time. In this application, the first positioning method can be introduced again for error repair, that is, the first positioning method can be used. The positioning method performs position correction processing on the second position data.

In the specific implementation, in the above (in the second positioning stage), the second positioning method is used to push the second position data of the electronic device during the movement, and the first positioning method (such as satellite positioning method) can be started at intervals based on a certain interval period to obtain The third position data, and then perform position correction processing on the second position data calculated by the neural network-based navigation push model in the second positioning method based on the third position data, and correct the generated position estimation deviation. The position correction process may be to perform position weighting processing on the "third position data" and "the second position data calculated by the neural network-based navigation push model", by assigning different weight values respectively, and then obtain a Based on the corrected second position data, the navigation calculation of pedestrians is continued to determine the next second position data.

In a specific implementation, in the process of "determining at least one second location data for the electronic device based on the first location data using the second positioning method", a trigger condition for position correction using the first positioning method may be set.

In a feasible implementation manner, a position correction period (such as 10s) can be set, and the position correction period is used for the electronic device to determine at least one second position data for the electronic device based on the first position data in the second positioning mode. In the process of ", each time the time point of the position correction cycle is reached, the first positioning method is simultaneously started to obtain the third position data of the electronic device, and the position correction process is performed on the second position data based on the third position data. Wherein, the determination of the position correction period may be based on an empirical value obtained through mathematical analysis of collected mobile data in an actual application environment.

In a feasible implementation manner, a reference travel distance can be set, and the reference travel distance is used for the electronic device in the process of "using the pedestrian navigation reckoning and fusion method of neural network to locate the second position data in the moving process", Every time the trip reaches the position reference travel distance (for example, 100m), the first positioning method is started to acquire the third position data of the electronic device at the same time, and the position correction processing is performed on the second position data based on the third position data.

In this application, the second positioning method and the first positioning method based on the position estimation based on the navigation reckoning model are realized. By setting a reasonable scheduling strategy, the positioning process of the first positioning method is started at the right time when the second position in the process of travel is determined. Taking into account the positioning accuracy and positioning power consumption of the whole period; and, by introducing the second positioning method of the neural network and the geographic fence detection strategy of the position correction mechanism, the power consumption of the first positioning method is further reduced, and the geographic fence can be improved. In the detection business, due to the influence of the environment, the first positioning method is used when the signal is poor, and the second positioning method can be used to obtain a position with high positioning accuracy, such as improving the positioning accuracy in indoor positioning scenarios.

S205: Detect whether the electronic device enters a range corresponding to the geo-fence based on the device location data.

The device location data includes at least one of the network location data, the first location data, the second location data, and the third location data in the embodiments of the present application, and at least includes the second location data in practical applications,

In this application, the electronic device controls the low-power controller to detect whether the electronic device enters the range corresponding to the geo-fence. The power consumption controller executes the geo-fence triggering service.

Please refer to FIG. 5 . FIG. 5 is a schematic flowchart of another embodiment of a geofence control method proposed by the present application. specific:

S301: Determine a target business operation for the geo-fence;

For details, please refer to other embodiments of the present application, which will not be repeated here.

S302: Control the low power consumption controller to respond to the target service operation, and only execute the target processing task for the geofence through the low power consumption controller;

Specifically, the electronic device controls the low-power controller to respond to the target service operation, and only the low-power controller executes the target processing task for the geo-fence based on the target service operation during the specific execution process; further , if the target processing task involves the necessary human-computer interaction process (such as output information, display screen, etc.) related to the application carried on the corresponding application processor and/or the necessary interaction process with the data on the network side, it is controlled by low power consumption The processor controls the application processor to execute, such as sending relevant operation instructions to instruct the application processor to complete,

S303: Control the low-power controller to respond to the target service operation, use the application processor as a coprocessor of the low-power controller, and control the low-power controller and the application processor to jointly execute the target The target processing task corresponding to the business operation.

According to some implementations, after the target service operation is determined, the electronic device does not use the application processor to respond, but transfers it to the low-power controller based on the target service operation. In the entire process involving the application processor, the application processor only As an auxiliary processor, the low-power processor acts as the main processor, and assists in processing geo-fence-related services by using the application processor as a co-processor of the low-power controller in the geo-fence scenario. Furthermore, in actual application scenarios, based on the current processor state of the low-power controller, the processor based on the low-power controller The state performs load distribution, and distributes all the data processing tasks originally performed by the low-power processor to the application processor for completion, or calls the application processor and the low-power controller to jointly complete part of the processing tasks, and realizes dynamic load balancing. At the same time, the power consumption of the geofence service control is reduced under the condition of ensuring the processing efficiency of the geofence and the state of the low-power controller.

In a specific implementation scenario, if the target business operation is triggered on the application of the application processor, it is determined that it is a business operation related to geofencing, and the application processor transfers the business operation to the low-power controller. The device does not respond to the target service operation and can only make a preliminary judgment of the operation type. The low-power controller responds to the above-mentioned target service operations, and realizes that the low-power controller is the main processor for processing. When performing data interaction scenarios, the low-power controller triggers the application processor to obtain relevant interaction data from the network by responding to the target business operation. The application processor is used as a coprocessor of the low-power controller in the geo-fence scenario to assist in processing geo-fence-related services.

In a specific implementation scenario, the electronic device executes the target processing task corresponding to the target service operation through the low-power controller and the application processor. During the specific implementation process:

1. The electronic device can obtain the task status parameters corresponding to the low-power controller in advance;

The task state parameter may be the total thread overhead of all threads of the low-power controller, or may be the amount of surplus resources for the low-power controller.

The total thread overhead can be understood as overhead such as space (memory consumption) and time (execution performance during runtime) generated by the low-power controller during execution. The time overhead (execution performance during runtime) may be power consumption overhead, performance overhead, context switching overhead, processor resource overhead (such as the number of I/O ports), and the like.

The amount of surplus resources may be understood as the amount of resources left by the low power consumption controller to meet the resource requirements of the currently running processing tasks. The resource is mainly the computing resource of the processing unit contained in the low-power controller, and the definition of the resource may be the memory size, the number of I/O ports, the computing unit associated with the I/O port, the control unit, and so on.

In the specific implementation, a process for monitoring the current surplus resources and/or total thread overhead of the low-power controller can be created in advance, and the computing resources of the resource pool can be allocated to the process for real-time or periodic processing of low-power The current surplus resources and/or total thread overhead of the power consumption controller are monitored, and the surplus resources and/or total thread overhead of the low-power consumption controller can be obtained through this process.

2. Divide the target processing task corresponding to the target business operation into a first processing task and a second processing task based on the task state parameter, and the task amount of the first processing task is greater than the task amount of the second processing task .

The target processing task is a processing task corresponding to the target business operation, and the target processing task includes at least a geo-fence registration task, a geo-fence detection task, a geo-fence update task, a geo-fence trigger task, a geo-fence management task, and a geo-fence detection task One of.

The first processing task is the step information corresponding to the execution of at least one step in the task processing flow corresponding to the target processing task, which can be understood as a subtask of the target processing task, and the first processing task is mainly executed by the low power consumption controller.

The second processing task is the step information corresponding to the execution of at least one step in the task processing flow corresponding to the target processing task, which can be understood as a subtask of the target processing task, and the second processing task is mainly performed by the low-power controller; in some Implementation manner: the second processing task may have a cross task with the first processing task, and it can be understood that the cross task is jointly executed by the low power consumption controller and the application processor.

Take the task state parameter as the amount of surplus resources as an example:

The low power consumption controller divides the target processing task corresponding to the target business operation into a first processing task and a second processing task based on the task state parameter. During specific implementation: the target processing task corresponding to the target business operation can be obtained The historical resource expenditure amount of the task; then, based on the historical resource expenditure amount and the surplus resource amount, divide the target processing task into a first processing task and a second processing task.

The amount of historical resource overhead can be understood as the amount of resource overhead corresponding to the historical execution of the target processing task.

In a feasible implementation manner, the overhead score A can be evaluated based on the amount of historical resource overhead, and the surplus score B can be estimated based on the amount of surplus resources. Then, when the overhead fraction A is greater than the surplus fraction B, divide the target processing task into the first A processing task and a second processing task, the determination of the second processing task is determined based on the execution steps that the application processor can process. It is sufficient that the low power consumption controller can successfully respond to the first processing task based on the amount of surplus resources.

Further, the second processing task divided from the target processing task may be a parallel processing task, that is, a processing task jointly executed by the low power consumption controller and the application processor.

3. The low power consumption controller executes the first processing task, and the application processor executes the second processing task.

In a feasible implementation manner, the electronic device can monitor the task execution state of the low-power controller, and when the task execution state is a task load state, the execution steps corresponding to the current execution target processing task performing task load offloading, and offloading the third processing task from the target processing task; thereby realizing the step of determining a third processing task from the target processing tasks corresponding to the low power consumption controller based on the task execution state; Then, the application processor executes the third processing task, so as to share the processing pressure of the low power consumption controller.

In the embodiment of the present application, the electronic device can determine the target business operation for the geo-fence (business operations for geo-fence registration, geo-fence detection, geo-fence update, etc.) by controlling the low-power controller to respond to the target For business operation, the low power consumption controller acts as the main processor of the operation response to perform fence business processing on the geo-fence. By using the low-power controller in the low-power environment as the main processor, the geo-fence detection and processing work is executed in the low-power environment, and the geo-fence business processing is realized with the low-power controller as the main processor, so as to save and The power consumption of geofence services related to geofences, and at the same time optimize the business response process based on application processor-based operation response in related technologies. And, throughout the process involving the application processor, the application processor can be used only as an auxiliary processor, and the application processor can be used as a coprocessor of the low-power controller in the geo-fence scenario to assist in processing geo-fence related services, further Improve the intelligence of geo-fence management; and based on the current processor state of the low-power controller, on the premise that data processing is prioritized on the low-power processor, the processor based on the low-power controller The state performs load distribution, and distributes all the data processing tasks originally performed by the low-power processor to the application processor for completion, or calls the application processor and the low-power controller to jointly complete part of the processing tasks to achieve dynamic load balancing.

The geo-fence control device provided by the embodiment of the present application will be described in detail below with reference to FIG. 6 . It should be noted that the geo-fence control device shown in FIG. 6 is used to execute the method of the embodiments shown in FIGS. 1 to 5 of the present application. For technical details not disclosed, please refer to the embodiments shown in FIGS. 1 to 5 of this application.

Please refer to FIG. 6 , which shows a schematic structural diagram of a geofence control device according to an embodiment of the present application. The geo-fence control device 1 can be implemented as all or a part of electronic equipment through software, hardware or a combination of the two. According to some embodiments, the geofence control device 1 includes a business determination module 11 and a business processing module 12, specifically for:

A business determination module 11, configured to determine a target business operation for the geo-fence;

The business processing module 12 is configured to control the low power consumption controller to perform fence business processing on the geo-fence in response to the target business operation, and the power consumption of the low power consumption controller is less than that of the application processor power consumption.

Optionally, as shown in FIG. 7, the service determination module 11 includes:

The service determination unit 111 is configured to obtain a fence service request on the application processor, and determine a target service operation for the geo-fence based on the fence service request.

Optionally, as shown in Figure 7, the business processing module 12 includes:

The service control unit 121 is configured to, in response to the target service operation, control the low power consumption controller to execute the target processing task for the geo-fence;

The target processing task includes at least one of a geo-fence registration task, a geo-fence detection task, a geo-fence update task, a geo-fence trigger task, a geo-fence management task, and a geo-fence detection task.

Optionally, the service control unit 121 includes:

A fence detection subunit, configured to control the low power controller to acquire geofence data of the geofence detection task from the application processor, and control the low power controller to perform geofence based on the geofence data position.

Optionally, the fence detection unit includes:

The fence positioning subunit is configured to acquire device location data of the electronic device in a low-power location location mode, and detect whether the electronic device enters a range corresponding to the geo-fence based on the device location data.

Optionally, the fence detection unit also includes:

The first data acquisition subunit is used to acquire network location data and a mode trigger condition of the low power consumption positioning mode;

The second data acquisition subunit is configured to execute the step of acquiring the device location data of the electronic device in the low power consumption positioning mode if the network location data matches the mode trigger condition, and the low power The location accuracy corresponding to the consumption positioning mode is higher than the location accuracy corresponding to the network location data.

Optionally, the fence positioning subunit includes:

A first location acquisition subunit, configured to acquire first location data of the electronic device by using a first positioning method;

The second location acquisition subunit is configured to determine at least one second location data for the electronic device based on the first location data in a second positioning manner, where the positioning power consumption corresponding to the second positioning manner is smaller than that of the first positioning The positioning power consumption corresponding to the mode.

Optionally, the second location obtains a subunit, specifically for:

Obtaining movement acceleration data based on the first position data, inputting the movement acceleration data into a neural network-based navigation calculation model, outputting movement velocity data, and determining position displacement data based on the movement velocity data;

determining second location data for the electronic device based on the first location data and the location displacement data;

The second position data is used as the next first position data, and the step of acquiring movement acceleration data based on the first position data is performed.

Optionally, the second location obtains a subunit, specifically for:

Performing position correction processing on the second position data by using the first positioning manner.

Optionally, the second location obtains a subunit, specifically for:

Based on the position correction period and/or the reference travel distance, simultaneously start the first positioning method to obtain the third position data of the electronic device, and perform position correction processing on the second position data based on the third position data.

Optionally, the device 1 is specifically used for:

controlling the low power consumption controller to execute the target processing task corresponding to the target service operation; and/or,

The application processor is used as the coprocessor of the low power consumption controller, and the low power consumption controller and the application processor are controlled to jointly execute the target processing task corresponding to the target service operation.

Optionally, the device 1 is specifically used for:

Obtain the task status parameters corresponding to the low-power controller;

dividing the target processing task corresponding to the target business operation into a first processing task and a second processing task based on the task state parameter, the task amount of the first processing task being greater than the task amount of the second processing task;

controlling the low power consumption controller to execute the first processing task, and controlling the application processor to execute the second processing task.

Optionally, the device 1 is specifically used for:

The task status parameter is the amount of surplus resources;

The dividing the target processing task corresponding to the target business operation into a first processing task and a second processing task based on the task status parameter includes:

Acquiring the historical resource overhead of the target processing task corresponding to the target business operation;

Based on the amount of historical resource overhead and the amount of surplus resources, the target processing task is divided into a first processing task and a second processing task.

Optionally, the device 1 is specifically used for:

monitoring the task execution state of the low-power controller, and determining a third processing task from the target processing tasks corresponding to the low-power controller based on the task execution state;

The third processing task is executed by the application processor.

It should be noted that when the geo-fence control device provided by the above-mentioned embodiments executes the geo-fence control method, the division of the above-mentioned functional modules is used as an example for illustration. In practical applications, the above-mentioned functions can be assigned to different functions according to needs Module completion means that the internal structure of the device is divided into different functional modules to complete all or part of the functions described above. In addition, the geo-fence control device provided by the above-mentioned embodiments belongs to the same idea as the geo-fence control method embodiment, and its implementation process is detailed in the method embodiment, and will not be repeated here.

The serial numbers of the above embodiments of the present application are for description only, and do not represent the advantages and disadvantages of the embodiments.

The embodiment of the present application also provides a computer storage medium, the computer storage medium can store a plurality of instructions, and the instructions are suitable for being loaded and executed by a processor as described in the above-mentioned embodiments shown in FIGS. 1 to 5 . For the geo-fence control method, the specific execution process can refer to the specific description of the embodiments shown in FIGS. 1 to 5 , and details are not repeated here.

The present application also provides a computer program product, the computer program product stores at least one instruction, and the at least one instruction is loaded by the processor and executes the geofence in the embodiment shown in the above-mentioned Fig. 1 to Fig. 5 For the control method and the specific execution process, refer to the specific description of the embodiments shown in FIG. 1 to FIG. 5 , and details are not repeated here.

Please refer to FIG. 8 , which shows a structural block diagram of an electronic device provided by an exemplary embodiment of the present application. The electronic device in this application may include one or more of the following components: a processor 110 , a memory 120 , an input device 130 , an output device 140 and a bus 150 . The processor 110 , the memory 120 , the input device 130 and the output device 140 may be connected through a bus 150 .

Processor 110 may include one or more processing cores. The processor 110 uses various interfaces and lines to connect various parts of the entire electronic device, and executes electronic operations by running or executing instructions, programs, code sets or instruction sets stored in the memory 120, and calling data stored in the memory 120. Various functions and processing data of the device 100. Optionally, the processor 110 may use at least one of digital signal processing (digital signal processing, DSP), field-programmable gate array (field-programmable gate array, FPGA), programmable logic array (programmable logic array, PLA) implemented in the form of hardware. The processor 110 may integrate one or a combination of a central processing unit (central processing unit, CPU), an image processor (graphics processing unit, GPU), a modem, and the like. Among them, the CPU mainly handles the operating system, user interface and application programs, etc.; the GPU is used to render and draw the displayed content; the modem is used to handle wireless communication. It can be understood that, the above-mentioned modem may not be integrated into the processor 110, but may be realized by a communication chip alone.

The memory 120 may include a random access memory (random Access Memory, RAM), and may also include a read-only memory (read-only memory, ROM). Optionally, the memory 120 includes a non-transitory computer-readable storage medium. The memory 120 may be used to store instructions, programs, codes, sets of codes, or sets of instructions. The memory 120 may include a program storage area and a data storage area, wherein the program storage area may store instructions for implementing an operating system and instructions for implementing at least one function (such as a touch function, a sound playback function, an image playback function, etc.) , instructions for implementing the following various method embodiments, etc., the operating system can be an Android system, including a system based on the deep development of the Android system, an IOS system developed by Apple, including a system based on the deep development of the IOS system or other systems. The storage data area can also store data created by the electronic device during use, such as phonebook, audio and video data, chat record data, and the like.

As shown in FIG. 9 , the memory 120 can be divided into an operating system space and a user space. The operating system runs in the operating system space, and native and third-party applications run in the user space. In order to ensure that different third-party application programs can achieve better running effects, the operating system allocates corresponding system resources for different third-party application programs. However, different application scenarios in the same third-party application have different requirements for system resources. For example, in the local resource loading scenario, the third-party application has higher requirements for disk reading speed; in the animation rendering scenario, the second Three-party applications have higher requirements on GPU performance. However, the operating system and third-party applications are independent of each other, and the operating system often cannot perceive the current application scenarios of the third-party applications in a timely manner, resulting in the inability of the operating system to perform targeted system resource adaptation according to the specific application scenarios of the third-party applications.

In order for the operating system to distinguish the specific application scenarios of third-party applications, it is necessary to open up the data communication between the third-party applications and the operating system, so that the operating system can obtain the current scene information of the third-party applications at any time, and then based on the current scene. Targeted system resource adaptation.

Taking the operating system as an Android system as an example, the programs and data stored in the memory 120 are shown in Figure 10, the memory 120 can store a Linux kernel layer 320, a system runtime library layer 340, an application framework layer 360 and an application layer 380, Among them, the Linux kernel layer 320 , the system runtime layer 340 and the application framework layer 360 belong to the operating system space, and the application layer 380 belongs to the user space. The Linux kernel layer 320 provides underlying drivers for various hardware of electronic devices, such as display drivers, audio drivers, camera drivers, Bluetooth drivers, Wi-Fi drivers, power management, and so on. The system runtime layer 340 provides main feature support for the Android system through some C/C++ libraries. For example, the SQLite library provides database support, the OpenGL/ES library provides 3D drawing support, and the Webkit library provides browser kernel support. An Android runtime (Android runtime) is also provided in the system runtime library layer 340, which mainly provides some core libraries and can allow developers to use the Java language to write Android applications. The application framework layer 360 provides various APIs that may be used when building applications. Developers can also use these APIs to build their own applications, such as activity management, window management, view management, notification management, content providers, Package management, call management, resource management, location management. There is at least one application program running in the application layer 380, and these application programs can be native application programs that come with the operating system, such as a contact program, a text message program, a clock program, a camera application, etc.; they can also be developed by a third-party developer Third-party applications, such as game applications, instant messaging programs, photo beautification programs, etc.

Taking the operating system as the IOS system as an example, the programs and data stored in the memory 120 are shown in Figure 11. The IOS system includes: a core operating system layer 420 (Core OS layer), a core service layer 440 (Core Services layer), a media layer 460 (Media layer), touchable layer 480 (Cocoa Touch Layer). The core operating system layer 420 includes an operating system kernel, drivers, and underlying program frameworks. These underlying program frameworks provide functions closer to hardware for use by the program frameworks located in the core service layer 440 . The core service layer 440 provides system services and/or program frameworks required by applications, such as foundation framework, account framework, advertisement framework, data storage framework, network connection framework, geographic location framework, exercise framework and so on. The media layer 460 provides audio-visual interfaces for applications, such as interfaces related to graphics and images, interfaces related to audio technology, interfaces related to video technology, and wireless playback (AirPlay) interfaces of audio and video transmission technologies. The touchable layer 480 provides various commonly used interface-related frameworks for application development, and the touchable layer 480 is responsible for the user's touch interaction on the electronic device. Such as local notification service, remote push service, advertising framework, game tool framework, message user interface interface (User Interface, UI) framework, user interface UIKit framework, map framework and so on.

Among the frameworks shown in FIG. 11 , frameworks related to most applications include but are not limited to: the basic framework in the core service layer 440 and the UIKit framework in the touchable layer 480 . The basic framework provides many basic object classes and data types, and provides the most basic system services for all applications, regardless of UI. The class provided by the UIKit framework is a basic UI class library for creating a touch-based user interface. iOS applications can provide UI based on the UIKit framework, so it provides the infrastructure of the application for building user interfaces, drawing , Handle and user interaction events, respond to gestures, and more.

Wherein, the method and principle of implementing the data communication between the third-party application program and the operating system in the IOS system can refer to the Android system, and this application will not repeat them here.

Wherein, the input device 130 is used for receiving input instructions or data, and the input device 130 includes but not limited to a keyboard, a mouse, a camera, a microphone or a touch device. The output device 140 is used to output instructions or data, and the output device 140 includes but not limited to a display device and a speaker. In one example, the input device 130 and the output device 140 can be set together, and the input device 130 and the output device 140 are touch screens, and the touch screen is used to receive any suitable object such as a finger, a touch pen, etc. Nearby touch operation, and display the user interface of each application. The touch display screen is usually arranged on the front panel of the electronic equipment. Touch screens can be designed as full screens, curved screens or special-shaped screens. The touch display screen can also be designed as a combination of a full screen and a curved screen, or a combination of a special-shaped screen and a curved screen, which is not limited in this embodiment of the present application.

In addition, those skilled in the art can understand that the structure of the electronic device shown in the above drawings does not constitute a limitation on the electronic device, and the electronic device may include more or less components than those shown in the illustration, or combine certain components, or a different arrangement of components. For example, the electronic device also includes radio frequency circuit, input unit, sensor, audio circuit, wireless fidelity (wireless fidelity, WiFi) module, power supply, bluetooth module and other components, which will not be repeated here.

In the embodiment of the present application, the execution subject of each step may be the electronic device introduced above. Optionally, each step is executed by an operating system of the electronic device. The operating system may be an Android system, an IOS system, or other operating systems, which is not limited in this embodiment of the present application.

The electronic device of the embodiment of the present application can also be equipped with a display device, and the display device can be various devices capable of realizing display functions, such as: a cathode ray tube display (cathode ray tube display, CR for short), a light emitting diode display (light -emitting diode display, referred to as LED), electronic ink screen, liquid crystal display (liquid crystal display, referred to as LCD), plasma display panel (plasma display panel, referred to as PDP), etc. The user can use the display device on the electronic device 101 to view displayed text, images, videos and other information. The electronic device may be a smart phone, a tablet computer, a game device, an AR (Augmented Reality, augmented reality) device, a car, a data storage device, an audio playback device, a video playback device, a notebook, a desktop computing device, a wearable device such as an electronic Watches, electronic glasses, electronic helmets, electronic bracelets, electronic necklaces, electronic clothing and other equipment.

In the electronic device shown in FIG. 8 , where the electronic device can be a terminal, the processor 110 can be used to call the geofence control program stored in the memory 120, and specifically perform the following operations:

Identify targeted business operations for geofencing;

controlling the low power consumption controller to perform fence service processing on the geo-fence in response to the target service operation, and the power consumption of the low power consumption controller is less than the power consumption of the application processor.

In one embodiment, the processor 1001 specifically performs the following operations when performing the determining target service operation for the geofence:

A fence service request on the application processor is acquired, and a target service operation for the geofence is determined based on the fence service request.

In one embodiment, when the processor 1001 performs the controlling the low power consumption controller to respond to the target service operation to perform fence service processing on the geo-fence, specifically perform the following operations:

In response to the target service operation, controlling a low power consumption controller to perform a target processing task for the geo-fence;

The target processing task includes at least one of a geofence registration task, a geofence detection task, a geofence update task, a geofence trigger task, a geofence management task, and a geofence detection task.

In one embodiment, when the processor 1001 executes the target processing task as a geofence detection task, and the controlling low power consumption controller performs the target processing task on the geofence, the following operations are specifically performed:

Controlling the low power consumption controller to acquire geofence data of the geofence detection task from the application processor, and controlling the low power consumption controller to perform geofence positioning based on the geofence data. In one embodiment, the processor 1001 specifically performs the following operations when performing the geofence positioning based on the geofence data:

The device location data of the electronic device is acquired by adopting a low power consumption positioning mode, and based on the device location data, it is detected whether the electronic device enters a range corresponding to the geo-fence.

In one embodiment, before the processor 1001 executes the acquisition of the location data of the electronic device in the low power consumption positioning mode, the following operations are further performed:

Obtain network location data and mode trigger conditions for low-power positioning mode;

If the network location data matches the mode trigger condition, execute the step of acquiring the device location data of the electronic device in a low-power location mode, where the location accuracy corresponding to the low-power location mode is higher than The location accuracy corresponding to the network location data.

In one embodiment, the processor 1001 specifically performs the following operations when executing the acquisition of device location data using the low power consumption positioning mode:

Obtaining first location data of the electronic device by using a first positioning method;

Determining at least one second location data for the electronic device based on the first location data in a second positioning manner, where the positioning power consumption corresponding to the second positioning manner is smaller than the positioning power consumption corresponding to the first positioning manner.

In one embodiment, when the processor 1001 executes the acquisition of at least one second location data for the electronic device based on the first location data in a way of pedestrian navigation reckoning and fusion, specifically perform the following operations:

In one embodiment, the processor 1001 also performs the following operations:

Performing position correction processing on the second position data by using the first positioning method.

In one embodiment, when the processor 1001 performs the position correction process on the second position data by using the first positioning method, specifically perform the following operations:

In one embodiment, the processor 1001 specifically performs the following operations when executing the target processing task corresponding to the control low power consumption controller to perform the target service operation:

In one embodiment, when the processor 1001 executes the target processing task corresponding to the target service operation of controlling the low power consumption controller and the application processor, it specifically performs the following operations:

Obtain the task status parameters corresponding to the low-power controller;

In one embodiment, the processor 1001 divides the target processing task corresponding to the target service operation into the first processing task and When processing the second task, specifically perform the following operations:

In one embodiment, the processor 1001 also performs the following operations:

The third processing task is executed by the application processor.

Those of ordinary skill in the art can understand that all or part of the processes in the methods of the above embodiments can be implemented through computer programs to instruct related hardware, and the programs can be stored in a computer-readable storage medium. During execution, it may include the processes of the embodiments of the above-mentioned methods. Wherein, the storage medium may be a magnetic disk, an optical disk, a read-only memory or a random access memory, and the like.

The above disclosures are only preferred embodiments of the present application, which certainly cannot limit the scope of the present application. Therefore, equivalent changes made according to the claims of the present application still fall within the scope of the present application.

Claims

A geofence control method applied to an electronic device, wherein the electronic device includes a low power consumption controller and an application processor, and the method includes:

Identify targeted business operations for geofencing;

controlling the low power consumption controller to perform fence service processing on the geo-fence in response to the target service operation, and the power consumption of the low power consumption controller is less than the power consumption of the application processor.
The method according to claim 1, wherein said determining a target business operation for a geofence comprises:

A fence service request on the application processor is acquired, and a target service operation for the geofence is determined based on the fence service request.
The method according to claim 1, wherein the controlling the low power consumption controller to perform fence service processing on the geo-fence in response to the target service operation comprises:

In response to the target service operation, controlling a low power consumption controller to perform a target processing task for the geo-fence;

The target processing task includes at least one of a geo-fence registration task, a geo-fence detection task, a geo-fence update task, a geo-fence trigger task, a geo-fence management task, and a geo-fence detection task.
The method according to claim 3, wherein the target processing task is a geofence detection task,

Said controlling the low power consumption controller to execute the target processing task for said geo-fence, including:

Controlling the low power consumption controller to acquire geofence data of the geofence detection task from the application processor, and controlling the low power consumption controller to perform geofence positioning based on the geofence data.
The method according to claim 4, wherein said geofence positioning based on said geofence data comprises:

The device location data of the electronic device is acquired by adopting a low power consumption positioning mode, and based on the device location data, it is detected whether the electronic device enters a range corresponding to the geo-fence.
The method according to claim 5, wherein, before acquiring the device location data of the electronic device in the low power consumption positioning mode, further comprising:

Obtain network location data and mode trigger conditions for low-power positioning mode;

If the network location data matches the mode trigger condition, execute the step of acquiring the device location data of the electronic device in a low-power location mode, where the location accuracy corresponding to the low-power location mode is higher than The location accuracy corresponding to the network location data.
The method according to claim 5, wherein said acquiring device location data using a low power consumption positioning mode comprises:

Obtaining first location data of the electronic device by using a first positioning method;

Determining at least one second location data for the electronic device based on the first location data in a second positioning manner, where the positioning power consumption corresponding to the second positioning manner is smaller than the positioning power consumption corresponding to the first positioning manner.
The method according to claim 7, wherein said acquiring at least one second position data for the electronic device based on the first position data by means of pedestrian navigation reckoning fusion comprises:

Obtaining movement acceleration data based on the first position data, inputting the movement acceleration data into a neural network-based navigation calculation model, outputting movement velocity data, and determining position displacement data based on the movement velocity data;

determining second location data for the electronic device based on the first location data and the location displacement data;

The second position data is used as the next first position data, and the step of acquiring movement acceleration data based on the first position data is performed.
The method according to claim 8, wherein the method further comprises:

Performing position correction processing on the second position data by using the first positioning method.
The method according to claim 8, wherein the performing position correction processing on the second position data by using the first positioning method comprises:

Based on the position correction period and/or the reference travel distance, simultaneously start the first positioning method to obtain the third position data of the electronic device, and perform position correction processing on the second position data based on the third position data.
The method according to claim 3, wherein the controlling the low power consumption controller to execute the target processing task corresponding to the target service operation comprises:

controlling the low power consumption controller to execute the target processing task corresponding to the target service operation; and/or,

The application processor is used as the coprocessor of the low power consumption controller, and the low power consumption controller and the application processor are controlled to jointly execute the target processing task corresponding to the target service operation.
The method according to claim 11, wherein the controlling the low power consumption controller and the application processor to jointly execute the target processing task corresponding to the target service operation comprises:

Obtain the task status parameters corresponding to the low-power controller;

dividing the target processing task corresponding to the target business operation into a first processing task and a second processing task based on the task state parameter, the task amount of the first processing task being greater than the task amount of the second processing task;

controlling the low power consumption controller to execute the first processing task, and controlling the application processor to execute the second processing task.
The method according to claim 12, wherein the task state parameter is the amount of surplus resources;

The dividing the target processing task corresponding to the target business operation into a first processing task and a second processing task based on the task status parameter includes:

Acquiring the historical resource overhead of the target processing task corresponding to the target business operation;

Based on the amount of historical resource overhead and the amount of surplus resources, the target processing task is divided into a first processing task and a second processing task.
The method according to claim 11, wherein the method further comprises:

monitoring the task execution state of the low-power controller, and determining a third processing task from the target processing tasks corresponding to the low-power controller based on the task execution state;

The third processing task is executed by the application processor.
A geofence control device, wherein the device comprises:

A business determination module for determining target business operations for geofences;

The service processing module is configured to control the low-power controller to perform fence service processing on the geo-fence in response to the target service operation, and the power consumption of the low-power controller is less than that of the application processor.
The device according to claim 15, wherein the service determination module includes:

The service determination unit is configured to acquire a fence service request on the application processor, and determine a target service operation for the geo-fence based on the fence service request.
The device according to claim 15, wherein the service processing module includes:

a service control unit, configured to, in response to the target service operation, control the low power consumption controller to execute the target processing task for the geo-fence;

The target processing task includes at least one of a geo-fence registration task, a geo-fence detection task, a geo-fence update task, a geo-fence trigger task, a geo-fence management task, and a geo-fence detection task.
The device according to claim 17, wherein the service control unit comprises:

A fence detection subunit, configured to control the low power controller to acquire geofence data of the geofence detection task from the application processor, and control the low power controller to perform geofence based on the geofence data position.
A computer storage medium, wherein the computer storage medium stores a plurality of instructions, and the instructions are suitable for being loaded by a processor and executing the method steps according to any one of claims 1-14.
An electronic device, comprising: a processor and a memory; wherein, the memory stores a computer program, and the computer program is adapted to be loaded by the processor and execute the method steps according to any one of claims 1-14.