CN108270921B - Falling information detection method and related product - Google Patents
Falling information detection method and related product Download PDFInfo
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- CN108270921B CN108270921B CN201810051094.3A CN201810051094A CN108270921B CN 108270921 B CN108270921 B CN 108270921B CN 201810051094 A CN201810051094 A CN 201810051094A CN 108270921 B CN108270921 B CN 108270921B
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- 238000004590 computer program Methods 0.000 claims description 13
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04M—TELEPHONIC COMMUNICATION
- H04M1/00—Substation equipment, e.g. for use by subscribers
- H04M1/72—Mobile telephones; Cordless telephones, i.e. devices for establishing wireless links to base stations without route selection
- H04M1/724—User interfaces specially adapted for cordless or mobile telephones
- H04M1/72448—User interfaces specially adapted for cordless or mobile telephones with means for adapting the functionality of the device according to specific conditions
- H04M1/72454—User interfaces specially adapted for cordless or mobile telephones with means for adapting the functionality of the device according to specific conditions according to context-related or environment-related conditions
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01P—MEASURING LINEAR OR ANGULAR SPEED, ACCELERATION, DECELERATION, OR SHOCK; INDICATING PRESENCE, ABSENCE, OR DIRECTION, OF MOVEMENT
- G01P15/00—Measuring acceleration; Measuring deceleration; Measuring shock, i.e. sudden change of acceleration
- G01P15/18—Measuring acceleration; Measuring deceleration; Measuring shock, i.e. sudden change of acceleration in two or more dimensions
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04M—TELEPHONIC COMMUNICATION
- H04M2250/00—Details of telephonic subscriber devices
- H04M2250/12—Details of telephonic subscriber devices including a sensor for measuring a physical value, e.g. temperature or motion
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Abstract
The embodiment of the application discloses a method for detecting falling information and a related product, wherein the method comprises the following steps: when the electronic equipment is detected to enter a falling state, acquiring holding posture data and operating data of the electronic equipment; acquiring an unintentional falling probability value and an intentional falling probability value according to the holding posture data and the operation data; determining that the electronic device is in an unintentional fall state when the unintentional fall probability value is greater than or equal to the intentional fall probability value. By the adoption of the method and the device, the accuracy of judging whether the drop state is an intentional drop state or an unintentional drop state can be improved.
Description
Technical Field
The application relates to the technical field of electronic equipment, and mainly relates to a fall information detection method and a related product.
Background
In recent years, with the development of electronic device technology, electronic devices such as large-screen mobile phones and tablet computers have become more and more popular. In the process of daily use of the electronic equipment, the electronic equipment is inevitably dropped. In order to avoid the excessive economic loss of users caused by falling, the merchants often provide screen breaking or other insurance services, and therefore, how to distinguish whether the electronic equipment is in an intentional falling state or an unintentional falling state is a technical problem to be solved by those skilled in the art.
Disclosure of Invention
The embodiment of the application provides a falling information detection method and a related product, and can improve the accuracy of judging whether an intentional falling state or an unintentional falling state.
In a first aspect, an embodiment of the present application provides a method for detecting fall information, including:
when the electronic equipment is detected to enter a falling state, acquiring holding posture data and operating data of the electronic equipment;
acquiring an unintentional falling probability value and an intentional falling probability value according to the holding posture data and the operation data;
determining that the electronic device is in an unintentional fall state when the unintentional fall probability value is greater than or equal to the intentional fall probability value.
In a second aspect, an embodiment of the present application provides an electronic device, including a processor, and a gravity sensor connected to the processor, wherein:
the gravity sensor is used for detecting whether the electronic equipment enters a falling state or not;
the processor is used for acquiring holding posture data and operating data of the electronic equipment when the electronic equipment enters a falling state; acquiring an unintentional falling probability value and an intentional falling probability value according to the holding posture data and the operation data; determining that the electronic device is in an unintentional fall state when the unintentional fall probability value is greater than or equal to the intentional fall probability value.
In a third aspect, an embodiment of the present application provides a device for detecting fall information, including:
the electronic equipment comprises an acquisition unit, a display unit and a control unit, wherein the acquisition unit is used for acquiring holding posture data and operating data of the electronic equipment when the electronic equipment is detected to enter a falling state; acquiring an unintentional falling probability value and an intentional falling probability value according to the holding posture data and the operation data;
the determining unit is used for determining that the electronic equipment is in an unintentional falling state when the unintentional falling probability value is larger than or equal to the intentional falling probability value.
In a fourth aspect, an embodiment of the present application provides another fall information detection method, which is applied to an electronic device including a processor and a gravity sensor connected to the processor, wherein:
the gravity sensor detects whether the electronic equipment enters a falling state or not;
the processor acquires holding posture data and operating data of the electronic equipment when the electronic equipment enters a falling state; acquiring an unintentional falling probability value and an intentional falling probability value according to the holding posture data and the operation data; determining that the electronic device is in an unintentional fall state when the unintentional fall probability value is greater than or equal to the intentional fall probability value.
In a fifth aspect, an embodiment of the present application provides another electronic device, including a processor, a memory, a communication interface, and one or more programs, where the one or more programs are stored in the memory and configured to be executed by the processor, and the program includes instructions for some or all of the steps described in the first aspect.
In a sixth aspect, the present application provides a computer-readable storage medium, where the computer-readable storage medium stores a computer program, where the computer program makes a computer perform some or all of the steps as described in the first aspect of the present application.
In a seventh aspect, this application embodiment provides a computer program product, where the computer program product comprises a non-transitory computer-readable storage medium storing a computer program, the computer program being operable to cause a computer to perform some or all of the steps as described in the first aspect of this application embodiment. The computer program product may be a software installation package.
The embodiment of the application has the following beneficial effects:
after the falling information detection method and the related products are adopted, when the electronic equipment is detected to enter the falling state, the holding posture data and the operation data of the electronic equipment are obtained, the unintentional falling probability value and the intentional falling probability value are obtained according to the holding posture data and the operation data, when the unintentional falling probability value is larger than or equal to the intentional falling probability value, the electronic equipment is determined to be in the unintentional falling state, and otherwise, the electronic equipment is determined to be in the intentional falling state. The electronic equipment falling state judging method comprises the steps of acquiring holding posture data of a user holding the electronic equipment when the electronic equipment falls and operation data of the electronic equipment in current operation, analyzing the holding posture data and the operation data to obtain the possibility of an unintentional falling state and the possibility of an intentional falling state, judging the falling state of the electronic equipment with high probability from the unintentional falling state and the intentional falling state, improving the accuracy of judging the intentional falling state or the unintentional falling state, and facilitating different operations according to the unintentional falling state or the intentional falling state.
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In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present application, and for those skilled in the art, other drawings can be obtained according to the drawings without creative efforts.
Wherein:
fig. 1 is a schematic flowchart of a method for detecting fall information according to an embodiment of the present disclosure;
fig. 1A is a schematic diagram of a gravity sensor according to an embodiment of the present disclosure;
fig. 2 is a schematic flowchart of another fall information detection method provided in an embodiment of the present application;
fig. 3 is a schematic structural diagram of a fall information detection apparatus according to an embodiment of the present application;
fig. 4 is a schematic structural diagram of an electronic device according to an embodiment of the present disclosure;
fig. 5 is a schematic flowchart of another fall information detection method provided in an embodiment of the present application;
fig. 6 is a schematic structural diagram of another electronic device according to an embodiment of the present application.
Detailed Description
In order to make the technical solutions of the present application better understood, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are only a part of the embodiments of the present application, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.
The terms "first," "second," and the like in the description and claims of the present application and in the above-described drawings are used for distinguishing between different objects and not for describing a particular order. Furthermore, the terms "include" and "have," as well as any variations thereof, are intended to cover non-exclusive inclusions. For example, a process, method, system, article, or apparatus that comprises a list of steps or elements is not limited to only those steps or elements listed, but may alternatively include other steps or elements not listed, or inherent to such process, method, article, or apparatus.
Reference herein to "an embodiment" means that a particular feature, structure, or characteristic described in connection with the embodiment can be included in at least one embodiment of the application. The appearances of the phrase in various places in the specification are not necessarily all referring to the same embodiment, nor are separate or alternative embodiments mutually exclusive of other embodiments. It is explicitly and implicitly understood by one skilled in the art that the embodiments described herein can be combined with other embodiments.
The electronic devices involved in the embodiments of the present application may include various handheld devices, vehicle-mounted devices, wearable devices, computing devices or other processing devices connected to a wireless modem with wireless communication functions, as well as various forms of User Equipment (UE), Mobile Stations (MS), terminal equipment (terminal), and so on. For convenience of description, the above-mentioned devices are collectively referred to as electronic devices.
The embodiment of the application provides a falling information detection method and a related product, and can improve the accuracy of judging whether an intentional falling state or an unintentional falling state. Embodiments of the present application will be described below with reference to the accompanying drawings.
Referring to fig. 1, fig. 1 is a schematic flow chart of a method for detecting fall information according to an embodiment of the present disclosure. As shown in fig. 1, includes:
101: when the electronic equipment is detected to enter a falling state, the holding posture data and the operation data of the electronic equipment are obtained.
The method for detecting the falling state is not limited, the gravity acceleration can be obtained through the gravity sensor, and if the gravity acceleration is matched with the preset gravity acceleration, the electronic equipment is determined to be in a weightless state; the electronic equipment can also be judged through three axial accelerations detected by the gravity sensor, and when the duration of the state that the three axial accelerations are all smaller than the first threshold value is longer than the preset duration, the electronic equipment is determined to be in a falling state.
The gravity sensor (G-sensor) is used for detecting the direction and magnitude of acceleration, and is equivalent to detecting the motion state of the electronic device, the function of the gravity sensor is relatively simple to understand, changes of acceleration force, such as shaking, falling, rising, falling and other movement changes can be mainly sensed and converted into electric signals by the gravity sensor, and then the functions with good program design can be completed after calculation and analysis of the microprocessor.
Referring to fig. 1A, the acceleration direction includes three axes perpendicular to each other: an X-axis, a Y-axis, and a Z-axis. Wherein, the X axis and the Y axis are parallel to the plane of the electronic device 100, the X axis is the width direction of the electronic device 100, the Y axis is the length direction of the electronic device 100, and the Z axis is perpendicular to the plane of the electronic device 100.
In the present application, the acceleration in the X-axis direction is taken as the lateral acceleration, the acceleration in the Y-axis direction is taken as the longitudinal acceleration, and the acceleration in the Z-axis direction is taken as the gravitational acceleration. The unit of acceleration value is m/s2The gravitational acceleration is generally 9.8m/s2。
The first threshold and the preset time period are not limited. Because the gravity sensor comprises the three-axis rotor and the supporting part of the rotor, when the electronic equipment falls, the electronic equipment is in a free-falling body state, the rotor in the electronic equipment and the supporting part of the rotor are both in the free-falling body state, the supporting part is not deformed, and the output three axial accelerations are all zero. Considering that the electronic equipment may involve environmental factors such as wind force, air resistance, magnetic force and the like in the falling process, the first threshold is set, and if the duration of the state that the accelerations in the three axial directions are all smaller than the first threshold is longer than the preset duration, the electronic equipment is determined to fall, otherwise, the electronic equipment does not fall.
It should be noted that the gravity sensor in the electronic device may have other structures, and if the structure of the gravity sensor changes, the method for the electronic device to determine whether the electronic device falls may also change correspondingly with the structure of the gravity sensor, which is not limited herein as long as the gravity sensor can sense the free-fall motion of the electronic device.
If the electronic equipment is detected not to be in the falling state, continuously executing the step of detecting whether the electronic equipment is in the falling state; and if the electronic equipment is detected to be in a falling state, acquiring holding posture data and operating data of the electronic equipment when the falling state is detected.
The holding posture data is data of the electronic equipment held by a user when the electronic equipment falls, and can comprise holding gestures, holding areas, holding force and the like; the operation data is data currently operated when the electronic device falls, and may include foreground application, time value, network bandwidth, system occupied resources, contextual model, and the like.
102: and acquiring an unintentional falling probability value and an intentional falling probability value according to the holding posture data and the operation data.
The unintentional falling probability value is the possibility that the electronic equipment is in an unintentional falling state, and the intentional falling probability value is the possibility that the electronic equipment is in an intentional falling state. For example, the holding posture data is data of the electronic device held by the user when the electronic device falls, the operation data is data of the current operation of the electronic device when the electronic device falls, and the holding posture data and the operation data are analyzed to obtain an unintentional falling probability value and an intentional falling probability value.
The method for acquiring the unintentional falling probability value and the intentional falling probability value is not limited, if the holding posture data comprises a plurality of first dimension data, the operation data comprises a plurality of second dimension data, and optionally, a plurality of first matching values are acquired from a matching value between each of the plurality of first dimension data and the plurality of second dimension data and a first feature data corresponding to a prestored unintentional falling state; obtaining a plurality of second matching values by obtaining a matching value between each of the plurality of first dimensional data and the plurality of second dimensional data and second feature data corresponding to a pre-stored intentional falling state; and acquiring the unintentional falling probability value according to the preset weight value and the first matching values corresponding to each of the plurality of first dimension data and the plurality of second dimension data, and acquiring the intentional falling probability value according to the preset weight value and the second matching values corresponding to each of the plurality of first dimension data and the plurality of second dimension data.
The first dimension data may be the holding gesture, holding area, holding strength, and the like, and the second dimension data may be the foreground application, time value, network bandwidth, system occupied resources, contextual model, and the like; the first characteristic data is the characteristic data corresponding to the pre-stored unintentional falling state, and the second characteristic data is the characteristic data corresponding to the pre-stored intentional falling state.
The preset weight of each dimension data is not limited, and optionally, a plurality of target association values are obtained by obtaining association values between at least two dimension data in the plurality of first dimension data and the plurality of second dimension data; and determining a preset weight value of each dimension data in the first dimension data and the second dimension data according to the target association values.
Because each dimension data may have a certain relevance with other dimension data, for example: if the electronic equipment is in a vibration state, the holding area is small, and the holding force is small, the electronic equipment is easy to fall off unintentionally; if the time is the work and rest time of the user or the adjacent rest time, the holding force is small, and the unintentional falling is easy to cause; if the holding force is large and the operation data includes a large amount of emotion data, the user is prone to falling intentionally. When the preset weight is determined according to the correlation value between the dimension data, the effectiveness of the preset weight can be improved, and the accuracy of the unintentional falling probability value and the intentional falling probability value can be improved conveniently.
It can be understood that a matching value between each of the plurality of first dimensional data and the plurality of second dimensional data and the first characteristic data and the second characteristic data is respectively obtained, and then the unintentional falling probability value and the intentional falling probability value can be obtained by combining the preset weight of each of the plurality of first dimensional data and the plurality of second dimensional data.
103: determining that the electronic device is in an unintentional fall state when the unintentional fall probability value is greater than or equal to the intentional fall probability value.
In the method shown in fig. 1, when it is detected that the electronic device enters a falling state, holding posture data and operating data of the electronic device are acquired, an unintentional falling probability value and an intentional falling probability value are acquired according to the holding posture data and the operating data, and when the unintentional falling probability value is greater than or equal to the intentional falling probability value, it is determined that the electronic device is in an unintentional falling state, otherwise, the electronic device is in an intentional falling state. The electronic equipment falling state judging method comprises the steps of obtaining holding posture data of a user holding the electronic equipment when the electronic equipment falls and operation data of the electronic equipment in current operation, analyzing the holding posture data and the operation data to obtain the possibility of an unintentional falling state and the possibility of an intentional falling state, judging the falling state of the electronic equipment with high probability from the unintentional falling state and the intentional falling state, improving the accuracy of judging the intentional falling state or the unintentional falling state, and facilitating different operations according to the unintentional falling or the intentional falling.
Referring to fig. 2, fig. 2 is a schematic flow chart of a fall information detection method according to an embodiment of the present application. As shown in fig. 2, includes:
201: when the electronic equipment is detected to enter a falling state, the holding posture data and the operation data of the electronic equipment are obtained.
202: and acquiring an unintentional falling probability value and an intentional falling probability value according to the holding posture data and the operation data.
203: determining that the electronic device is in an unintentional fall state when the unintentional fall probability value is greater than or equal to the intentional fall probability value.
The steps 201-203 can refer to the embodiment shown in fig. 1, and are not limited herein.
204: and when the falling state of the electronic equipment is detected to be finished, the falling data of the electronic equipment is acquired.
The method for detecting the end of the falling state is not limited in the present application, and when at least one of the three axial accelerations is greater than a second threshold value, it is determined that the falling state of the electronic device is ended.
Wherein the second threshold is not limited, for example, the second threshold is twice the gravity acceleration, i.e. 19.6m/s2. The electronic equipment continuously obtains three axial accelerations through the gravity sensor, then compares the three axial accelerations with a second threshold value respectively, and when at least one of the three axial accelerations is judged to be larger than a second preset value, absolute values of the three axial accelerations are obtained. For example, the magnitude of the lateral acceleration obtained is 0.02m/s2The longitudinal acceleration is 0.01m/s2The gravity acceleration is 25m/s2Then the gravity acceleration is greater than the second threshold value of 19.6m/s2At this time, it may be determined that the electronic device collides with the ground or another object, that is, the falling state is ended.
If the electronic equipment is detected to be in the falling state and is ended, continuing to execute the step of detecting whether the falling state of the electronic equipment is ended; and if the falling state of the electronic equipment is detected to be finished, acquiring falling data of the electronic equipment.
The falling data may include falling height, detection results of falling states (whether the falling states are unintentional falling states or intentional falling states), falling time, falling paths, reaction data of users in the falling process, and the like. The application is not limited as to how fall data is acquired.
205: and when the falling height is larger than a third threshold value, detecting whether the appointed hardware of the electronic equipment is abnormal or not to obtain a detection result.
In the present application, the designated hardware of the electronic device is not limited, and may include peripherals of the electronic device, such as a touch screen, a headset, a plurality of sensors, and the like. The method for detecting whether the designated hardware is abnormal is not limited, and the state of the designated hardware is a normal state if the designated hardware executes the preset detection program corresponding to the designated hardware, or is an abnormal state if the designated hardware executes the preset detection program corresponding to the designated hardware.
The third threshold is not limited, and when the falling height is larger than the third threshold, the specified hardware of the electronic equipment is detected, so that the power consumption of the electronic equipment caused by multiple detections is effectively avoided. And obtaining a detection result when the detection is finished, wherein the detection result at least comprises whether the specified hardware is abnormal or not, and can also comprise a specific abnormal module in the specified hardware.
206: and when the specified hardware is abnormal, generating a detection report according to the detection result and the fall data, and sending the detection report to a server.
In the application, if the designated hardware is abnormal, a detection report is generated according to the detection result and the falling data, and the detection report is sent to the server, so that the server can quickly acquire the falling information of the user (for example, the falling height, the falling time, the damage condition of the electronic equipment, and the judgment of the accidental falling or the intentional falling) through the detection report, and when the user carries the electronic equipment to maintain at the designated maintenance point, the electronic equipment can be quickly maintained only by checking the corresponding detection report, thereby improving the maintenance efficiency.
In addition, the reservation can be carried out according to the detection report so as to avoid the technical problem of poor convenience caused by the shortage of the designated hardware to be replaced when the user arrives at the maintenance point.
Optionally, starting a self-checking program of the designated hardware; and re-detecting whether the specified hardware is abnormal or not, and ending if the specified hardware is normal. If the designated hardware (such as some sensors) can be recovered to be normal through the self-checking program, a detection report does not need to be sent to the server, the load of the server is reduced, and the fault recovery capability of the designated hardware is improved.
In the method shown in fig. 2, when it is detected that the electronic device enters a falling state, holding posture data of a user holding the electronic device when the electronic device falls and operation data of the electronic device in current operation are acquired, the holding posture data and the operation data are analyzed to obtain the possibility of an unintentional falling state and an intentional falling state, an unintentional falling probability value and an intentional falling probability value are obtained, when the unintentional falling probability value is greater than or equal to the intentional falling probability value, the electronic device is determined to be in the unintentional falling state, otherwise, the electronic device is determined to be in the intentional falling state. The falling state of the electronic equipment with higher probability is judged from an unintentional falling state and an intentional falling state, so that the accuracy of judging whether the intentional falling state or the unintentional falling state is improved, and different operations can be conveniently carried out according to the unintentional falling state or the intentional falling state. And when the falling state is finished, the falling data of the electronic equipment is acquired, and the designated hardware of the electronic equipment is detected when the falling height is greater than a third threshold value, so that the power consumption of the electronic equipment caused by multiple detections is effectively avoided. And if the specified hardware is abnormal, sending a detection report generated according to the detection result and the drop data to the server so that the server can analyze the detection report and backup the drop condition.
Referring to fig. 3, fig. 3 is a schematic structural diagram of a fall information detection apparatus according to an embodiment of the present disclosure, which is consistent with the embodiments shown in fig. 1 and fig. 2. As shown in fig. 3, the apparatus 300 includes:
the acquiring unit 301 is configured to acquire holding posture data and operating data of the electronic device when it is detected that the electronic device enters a falling state; and acquiring an unintentional falling probability value and an intentional falling probability value according to the holding posture data and the operation data.
A determining unit 302, configured to determine that the electronic device is in an unintentional falling state when the unintentional falling probability value is greater than or equal to the intentional falling probability value.
In one possible example, the holding posture data includes a plurality of first dimension data, the operation data includes a plurality of second dimension data, and the obtaining unit 301 is specifically configured to obtain a plurality of first matching values between each of the plurality of first dimension data and the plurality of second dimension data and the first feature data corresponding to the pre-stored unintentional falling state; obtaining a plurality of second matching values by obtaining a matching value between each of the plurality of first dimensional data and the plurality of second dimensional data and second feature data corresponding to a pre-stored intentional falling state; acquiring the unintentional falling probability value according to a preset weight value corresponding to each of the plurality of first dimensional data and the plurality of second dimensional data and the plurality of first matching values; and acquiring the intentional drop probability value according to a preset weight value corresponding to each of the plurality of first dimensional data and the plurality of second matching values.
In a possible example, the obtaining unit 301 is further configured to obtain a plurality of target association values obtained by association values between at least two dimension data of the plurality of first dimension data and the plurality of second dimension data; the determining unit 302 is further configured to determine a preset weight value of each of the plurality of first dimension data and the plurality of second dimension data according to the plurality of target associated values.
In a possible example, the obtaining unit 301 is further configured to obtain accelerations of the electronic device in three mutually perpendicular axial directions; the determining unit 302 is further configured to determine that the electronic device is in a falling state when the duration of a state in which all the three axial accelerations are smaller than a first threshold is longer than a preset duration; and when at least one acceleration in the three axial directions is larger than a second threshold value, determining that the falling state of the electronic equipment is finished.
In one possible example, the obtaining unit 301 is further configured to obtain fall data of the electronic device when detecting that a fall state of the electronic device is ended, where the fall data includes a fall height; when the falling height is larger than a third threshold value, detecting whether the designated hardware of the electronic equipment is abnormal or not to obtain a detection result; the apparatus 300 further comprises a generating unit 303 and a transmitting unit 304, wherein:
the generating unit 303 is configured to generate a detection report according to the detection result and the drop data when the specified hardware is abnormal;
the sending unit 304 is configured to send the detection report to a server.
In the apparatus shown in fig. 3, when it is detected that the electronic device enters a falling state, holding posture data and operation data of the electronic device are acquired, an unintentional falling probability value and an intentional falling probability value are acquired according to the holding posture data and the operation data, and when the unintentional falling probability value is greater than or equal to the intentional falling probability value, it is determined that the electronic device is in an unintentional falling state, otherwise, the electronic device is in an intentional falling state. The electronic equipment falling state judging method comprises the steps of acquiring holding posture data of a user holding the electronic equipment when the electronic equipment falls and operation data of the electronic equipment in current operation, analyzing the holding posture data and the operation data to obtain the possibility of an unintentional falling state and the possibility of an intentional falling state, judging the falling state of the electronic equipment with high probability from the unintentional falling state and the intentional falling state, improving the accuracy of judging the intentional falling state or the unintentional falling state, and facilitating different operations according to the unintentional falling state or the intentional falling state.
Referring to fig. 4, fig. 4 is a schematic structural diagram of an electronic device according to an embodiment of the present disclosure, which is consistent with the embodiments shown in fig. 1 and fig. 2. As shown in fig. 4, the electronic device 400 includes a processor 410, and a gravity sensor 420 and a memory 430 connected to the processor 410.
In the present application, the gravity sensor 420 is used to detect whether the electronic device 400 enters a falling state; the processor 410 is configured to obtain holding posture data and operation data of the electronic device 400 when the electronic device 400 enters a falling state; acquiring an unintentional falling probability value and an intentional falling probability value according to the holding posture data and the operation data; determining that the electronic device 400 is in an unintentional fall state when the unintentional fall probability value is greater than or equal to the intentional fall probability value.
In one possible example, the holding posture data includes a plurality of first dimension data, the operation data includes a plurality of second dimension data, and the memory 430 is configured to store a preset weight corresponding to each of the plurality of first dimension data and the plurality of second dimension data; in the aspect that the processor 410 acquires the unintentional falling probability value and the intentional falling probability value according to the holding posture data and the operation data, the processor 410 is specifically configured to acquire a matching value between each of the plurality of first dimensional data and the plurality of second dimensional data and first feature data corresponding to a prestored unintentional falling state, so as to obtain a plurality of first matching values; acquiring a matching value between each of the plurality of first dimensional data and the plurality of second dimensional data and second feature data corresponding to a pre-stored intentional falling state to obtain a plurality of second matching values; acquiring the unintentional falling probability value according to a preset weight value corresponding to each of the plurality of first dimensional data and the plurality of second dimensional data and the plurality of first matching values; and acquiring the intentional drop probability value according to a preset weight value corresponding to each of the plurality of first dimensional data and the plurality of second matching values.
In one possible example, before the processor 410 obtains the unintentional falling probability value according to the preset weight value and the first matching values corresponding to each of the first dimensional data and the second dimensional data, the processor 410 is further configured to obtain an association value between at least two of the first dimensional data and the second dimensional data, so as to obtain a target association value; and determining a preset weight value of each dimension data in the first dimension data and the second dimension data according to the target association values.
In one possible example, the memory 430 is further configured to store a first threshold, a preset time length and a second threshold; the gravity sensor 420 is further configured to acquire accelerations of the electronic device 400 in three mutually perpendicular axial directions; the processor 410 is further configured to determine that the electronic device 400 is in a falling state when the duration of the state in which all of the three axial accelerations are smaller than the first threshold is longer than the preset duration; determining that the falling state of the electronic device 400 is finished when at least one of the accelerations in the three axial directions is greater than the second threshold value.
In one possible example, the memory 430 is further configured to store a third threshold; the processor 410 is further configured to, when detecting that the falling state of the electronic device 400 is over, obtain falling data of the electronic device 400, where the falling data includes a falling height; when the falling height is greater than the third threshold, detecting whether the designated hardware of the electronic device 400 is abnormal, and obtaining a detection result; and when the specified hardware is abnormal, generating a detection report according to the detection result and the fall data, and sending the detection report to a server.
As shown in fig. 4, in the electronic device, when it is detected that the electronic device enters a falling state, holding posture data and operation data of the electronic device are obtained, an unintentional falling probability value and an intentional falling probability value are obtained according to the holding posture data and the operation data, and when the unintentional falling probability value is greater than or equal to the intentional falling probability value, it is determined that the electronic device is in an unintentional falling state, otherwise, the electronic device is in an intentional falling state. The electronic equipment falling detection method comprises the steps of obtaining holding posture data of a user holding the electronic equipment when the electronic equipment falls and operation data of the electronic equipment in current operation, analyzing the holding posture data and the operation data to obtain the possibility of an unintentional falling state and an intentional falling state, judging the falling state of the electronic equipment with high probability from the unintentional falling state and the intentional falling state, improving the accuracy of judging the intentional falling state or the unintentional falling state, and facilitating different operations according to the unintentional falling state or the intentional falling state.
Referring to fig. 5, fig. 5 is a flowchart illustrating another fall information detection method proposed by the present application, and the method is applied to the electronic device described in fig. 4, consistent with the embodiments shown in fig. 1 and fig. 2. Wherein:
501: the gravity sensor detects whether the electronic device enters a falling state.
502: and the processor acquires holding posture data and operating data of the electronic equipment when the electronic equipment enters a falling state.
503: and the processor acquires an unintentional falling probability value and an intentional falling probability value according to the holding posture data and the operation data.
504: the processor determines that the electronic device is in an unintentional drop state when the unintentional drop probability value is greater than or equal to the intentional drop probability value.
In one possible example, the grip posture data includes a plurality of first dimension data, the operational data includes a plurality of second dimension data, and the processor obtains an unintentional fall probability value and an intentional fall probability value from the grip posture data and the operational data, including:
the memory stores a preset weight corresponding to each of the plurality of first dimension data and the plurality of second dimension data;
the processor acquires a plurality of first matching values obtained by matching values between each dimension data in the plurality of first dimension data and the plurality of second dimension data and first feature data corresponding to a pre-stored unintentional falling state; obtaining a plurality of second matching values by obtaining a matching value between each of the plurality of first dimensional data and the plurality of second dimensional data and second feature data corresponding to a pre-stored intentional falling state; acquiring the unintentional falling probability value according to a preset weight value corresponding to each of the plurality of first dimensional data and the plurality of second dimensional data and the plurality of first matching values; and acquiring the intentional drop probability value according to a preset weight value corresponding to each of the plurality of first dimensional data and the plurality of second matching values.
In one possible example, before the processor obtains the unintentional falling probability value according to the preset weight value and the first matching values corresponding to each of the first dimensional data and the second dimensional data, the method further includes:
the processor obtains correlation values between at least two dimension data in the first dimension data and the second dimension data to obtain a plurality of target correlation values; and determining a preset weight value of each dimension data in the first dimension data and the second dimension data according to the target association values.
In one possible example, the method further comprises:
the memory stores a first threshold, a preset time length and a second threshold;
the gravity sensor acquires the acceleration of the electronic equipment in three mutually vertical axial directions; when the duration of the state that the three axial accelerations are all smaller than the first threshold is longer than the preset duration, the processor determines that the electronic equipment is in a falling state; and when at least one acceleration in the three axial directions is larger than the second threshold value, determining that the falling state of the electronic equipment is finished.
In one possible example, the method further comprises:
the memory stores a third threshold;
the processor acquires fall data of the electronic equipment when detecting that the fall state of the electronic equipment is finished, wherein the fall data comprises a fall height; when the falling height is larger than the third threshold value, detecting whether the designated hardware of the electronic equipment is abnormal or not to obtain a detection result; and when the specified hardware is abnormal, generating a detection report according to the detection result and the fall data, and sending the detection report to a server.
In the method shown in fig. 5, when it is detected that the electronic device enters a falling state, holding posture data and operating data of the electronic device are acquired, an unintentional falling probability value and an intentional falling probability value are acquired according to the holding posture data and the operating data, and when the unintentional falling probability value is greater than or equal to the intentional falling probability value, it is determined that the electronic device is in an unintentional falling state, otherwise, the electronic device is in an intentional falling state. The electronic equipment falling detection method comprises the steps of obtaining holding posture data of a user holding the electronic equipment when the electronic equipment falls and operation data of the electronic equipment in current operation, analyzing the holding posture data and the operation data to obtain the possibility of an unintentional falling state and the possibility of an intentional falling state, judging whether the electronic equipment falls in the unintentional falling state or the intentional falling state according to the falling state of the electronic equipment with high probability, and improving the accuracy of judging whether the electronic equipment falls in the intentional falling state or in the unintentional falling state, so that different operations can be performed according to the unintentional falling state or the intentional falling state.
Referring to fig. 6, fig. 6 is a schematic structural diagram of another electronic device according to an embodiment of the present disclosure, which is consistent with the embodiments shown in fig. 1 and fig. 2. As shown in fig. 6, the electronic device 600 includes a processor 610, a memory 620, a communication interface 630, and one or more programs 640, wherein the one or more programs 640 are stored in the memory 620 and configured to be executed by the processor 610, the programs 640 including instructions for performing the steps of:
when the electronic equipment is detected to enter a falling state, acquiring holding posture data and operating data of the electronic equipment;
acquiring an unintentional falling probability value and an intentional falling probability value according to the holding posture data and the operation data;
determining that the electronic device is in an unintentional fall state when the unintentional fall probability value is greater than or equal to the intentional fall probability value.
In one possible example, the grip posture data comprises a plurality of first dimension data, the operational data comprises a plurality of second dimension data, and the program 640 is specifically configured to execute the following steps in the acquiring of the unintentional fall probability value and the intentional fall probability value according to the grip posture data and the operational data:
acquiring a matching value between each of the plurality of first dimensional data and the plurality of second dimensional data and first feature data corresponding to a pre-stored unintentional falling state to obtain a plurality of first matching values;
acquiring a matching value between each of the plurality of first dimensional data and the plurality of second dimensional data and second feature data corresponding to a pre-stored intentional falling state to obtain a plurality of second matching values;
acquiring the unintentional falling probability value according to a preset weight value corresponding to each of the plurality of first dimensional data and the plurality of second dimensional data and the plurality of first matching values;
and acquiring the intentional drop probability value according to a preset weight value corresponding to each of the plurality of first dimensional data and the plurality of second matching values.
In one possible example, before the obtaining the unintentional drop probability value according to the preset weight value and the first matching values corresponding to each of the first dimension data and the second dimension data, the program 640 is specifically configured to execute the following steps:
obtaining correlation values between at least two pieces of dimensional data in the plurality of first dimensional data and the plurality of second dimensional data to obtain a plurality of target correlation values;
and determining a preset weight value of each dimension data in the first dimension data and the second dimension data according to the target association values.
In one possible example, the program 640 is further for instructions to perform the steps of:
acquiring accelerations of the electronic equipment in three mutually perpendicular axial directions;
when the duration of the state that the three axial accelerations are all smaller than the first threshold is longer than a preset duration, determining that the electronic equipment is in a falling state;
and when at least one acceleration in the three axial directions is larger than a second threshold value, determining that the falling state of the electronic equipment is finished.
In one possible example, the program 640 is further for instructions to perform the steps of:
when the falling state of the electronic equipment is detected to be finished, falling data of the electronic equipment are obtained, wherein the falling data comprise falling height;
when the falling height is larger than a third threshold value, detecting whether the designated hardware of the electronic equipment is abnormal or not to obtain a detection result;
and when the specified hardware is abnormal, generating a detection report according to the detection result and the fall data, and sending the detection report to a server.
As shown in fig. 6, in the electronic device, when it is detected that the electronic device enters a falling state, holding posture data and operation data of the electronic device are obtained, an unintentional falling probability value and an intentional falling probability value are obtained according to the holding posture data and the operation data, and when the unintentional falling probability value is greater than or equal to the intentional falling probability value, it is determined that the electronic device is in an unintentional falling state, otherwise, the electronic device is in an intentional falling state. The electronic equipment falling state judging method comprises the steps of acquiring holding posture data of a user holding the electronic equipment when the electronic equipment falls and operation data of the electronic equipment in current operation, analyzing the holding posture data and the operation data to obtain the possibility of an unintentional falling state and the possibility of an intentional falling state, judging the falling state of the electronic equipment with high probability from the unintentional falling state and the intentional falling state, improving the accuracy of judging the intentional falling state or the unintentional falling state, and facilitating different operations according to the unintentional falling state or the intentional falling state.
Embodiments of the present application also provide a computer storage medium, where the computer storage medium stores a computer program for causing a computer to execute a part or all of the steps of any one of the methods as described in the method embodiments, and the computer includes an electronic device.
Embodiments of the application also provide a computer program product comprising a non-transitory computer readable storage medium storing a computer program operable to cause a computer to perform some or all of the steps of any of the methods as recited in the method embodiments. The computer program product may be a software installation package and the computer comprises the electronic device.
It should be noted that, for simplicity of description, the above-mentioned method embodiments are described as a series of acts or combination of acts, but those skilled in the art will recognize that the present application is not limited by the order of acts described, as some steps may occur in other orders or concurrently depending on the application. Further, those skilled in the art should also appreciate that the embodiments described in the specification are preferred embodiments and that the acts and modules referred to are not necessarily required in this application.
In the embodiments, the descriptions of the respective embodiments have respective emphasis, and for parts that are not described in detail in a certain embodiment, reference may be made to related descriptions of other embodiments.
In the embodiments provided in the present application, it should be understood that the disclosed apparatus may be implemented in other manners. For example, the above-described embodiments of the apparatus are merely illustrative, and for example, a division of a unit is merely a logical division, and an actual implementation may have another division, for example, a plurality of units or components may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection of some interfaces, devices or units, and may be an electric or other form.
Units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.
In addition, functional units in the embodiments of the present application may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit can be realized in a form of hardware or a form of software functional unit.
The integrated unit, if implemented in the form of a software functional unit and sold or used as a stand-alone product, may be stored in a computer readable memory. Based on such understanding, the technical solution of the present application may be substantially implemented or a part of or all or part of the technical solution contributing to the prior art may be embodied in the form of a software product stored in a memory, and including several instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method of the embodiments of the present application. And the aforementioned memory comprises: various media capable of storing program codes, such as a usb disk, a read-only memory (ROM), a Random Access Memory (RAM), a removable hard disk, a magnetic or optical disk, and the like.
The foregoing detailed description of the embodiments of the present application has been presented to illustrate the principles and implementations of the present application, and the above description of the embodiments is only provided to help understand the method and the core concept of the present application; meanwhile, for a person skilled in the art, according to the idea of the present application, there may be variations in the specific embodiments and application scope, and in summary, the content of the present specification should not be construed as a limitation to the present application.
Claims (16)
1. A method for detecting falling information is characterized by comprising the following steps:
when the electronic equipment is detected to enter a falling state, acquiring holding posture data and operating data of the electronic equipment;
acquiring an unintentional falling probability value and an intentional falling probability value according to the holding posture data and the operation data;
determining that the electronic device is in an unintentional fall state when the unintentional fall probability value is greater than or equal to the intentional fall probability value.
2. The method of claim 1, wherein the grip posture data comprises a plurality of first dimension data, the operational data comprises a plurality of second dimension data, and the obtaining an unintentional fall probability value and an intentional fall probability value from the grip posture data and the operational data comprises:
acquiring a matching value between each of the plurality of first dimensional data and the plurality of second dimensional data and first feature data corresponding to a pre-stored unintentional falling state to obtain a plurality of first matching values;
acquiring a matching value between each of the plurality of first dimensional data and the plurality of second dimensional data and second feature data corresponding to a pre-stored intentional falling state to obtain a plurality of second matching values;
acquiring the unintentional falling probability value according to a preset weight value corresponding to each of the plurality of first dimensional data and the plurality of second dimensional data and the plurality of first matching values;
and acquiring the intentional drop probability value according to a preset weight value corresponding to each of the plurality of first dimensional data and the plurality of second matching values.
3. The method of claim 2, wherein prior to the obtaining the unintentional drop probability value according to the preset weight value and the first matching values corresponding to each of the first dimension data and the second dimension data, the method further comprises:
obtaining correlation values between at least two pieces of dimensional data in the plurality of first dimensional data and the plurality of second dimensional data to obtain a plurality of target correlation values;
and determining a preset weight value of each dimension data in the first dimension data and the second dimension data according to the target association values.
4. The method according to any one of claims 1-3, further comprising:
acquiring accelerations of the electronic equipment in three mutually perpendicular axial directions; when the duration of the state that the three axial accelerations are all smaller than the first threshold is longer than a preset duration, determining that the electronic equipment is in a falling state; and when at least one acceleration in the three axial directions is larger than a second threshold value, determining that the falling state of the electronic equipment is finished.
5. The method according to any one of claims 1-3, further comprising:
when the falling state of the electronic equipment is detected to be finished, falling data of the electronic equipment are obtained, wherein the falling data comprise falling height;
when the falling height is larger than a third threshold value, detecting whether the designated hardware of the electronic equipment is abnormal or not to obtain a detection result;
and when the specified hardware is abnormal, generating a detection report according to the detection result and the fall data, and sending the detection report to a server.
6. The method of claim 4, further comprising:
when the falling state of the electronic equipment is detected to be finished, falling data of the electronic equipment are obtained, wherein the falling data comprise falling height;
when the falling height is larger than a third threshold value, detecting whether the designated hardware of the electronic equipment is abnormal or not to obtain a detection result;
and when the specified hardware is abnormal, generating a detection report according to the detection result and the fall data, and sending the detection report to a server.
7. An electronic device, comprising: processor, with the gravity sensor that the processor is connected, wherein:
the gravity sensor is used for detecting whether the electronic equipment enters a falling state or not;
the processor is used for acquiring holding posture data and operating data of the electronic equipment when the electronic equipment enters a falling state; acquiring an unintentional falling probability value and an intentional falling probability value according to the holding posture data and the operation data; determining that the electronic device is in an unintentional fall state when the unintentional fall probability value is greater than or equal to the intentional fall probability value.
8. The electronic device of claim 7, wherein the holding gesture data comprises a plurality of first dimension data, the operation data comprises a plurality of second dimension data, and the electronic device further comprises a memory coupled to the processor for storing a preset weight corresponding to each of the plurality of first dimension data and the plurality of second dimension data;
in the aspect that the processor acquires an unintentional falling probability value and an intentional falling probability value according to the holding posture data and the operation data, the processor is specifically configured to acquire a matching value between each of the plurality of first dimensional data and the plurality of second dimensional data and first feature data corresponding to a prestored unintentional falling state, so as to obtain a plurality of first matching values; acquiring a matching value between each of the plurality of first dimensional data and the plurality of second dimensional data and second feature data corresponding to a pre-stored intentional falling state to obtain a plurality of second matching values; acquiring the unintentional falling probability value according to a preset weight value corresponding to each of the plurality of first dimensional data and the plurality of second dimensional data and the plurality of first matching values; and acquiring the intentional drop probability value according to a preset weight value corresponding to each of the plurality of first dimensional data and the plurality of second matching values.
9. The electronic device of claim 8, wherein before the processor obtains the unintentional falling probability value according to the preset weight value and the first matching values corresponding to each of the first dimensional data and the second dimensional data, the processor is further configured to obtain a correlation value between at least two of the first dimensional data and the second dimensional data to obtain a target correlation values; and determining a preset weight value of each dimension data in the first dimension data and the second dimension data according to the target association values.
10. The electronic device according to any of claims 7-9, wherein the electronic device further comprises a memory coupled to the processor, and the memory is further configured to store the first threshold, the preset duration, and the second threshold;
the gravity sensor is also used for acquiring the acceleration of the electronic equipment in three mutually vertical axial directions;
the processor is further configured to determine that the electronic device is in a falling state when the duration of the state in which all of the three axial accelerations are smaller than the first threshold is longer than the preset duration; and when at least one acceleration in the three axial directions is larger than the second threshold value, determining that the falling state of the electronic equipment is finished.
11. The electronic device of any of claims 7-9, wherein the electronic device further comprises a memory coupled to the processor, and wherein the memory is further configured to store a third threshold value;
the processor is further configured to acquire fall data of the electronic device when detecting that a fall state of the electronic device is ended, where the fall data includes a fall height; when the falling height is larger than the third threshold value, detecting whether the designated hardware of the electronic equipment is abnormal or not to obtain a detection result; and when the specified hardware is abnormal, generating a detection report according to the detection result and the fall data, and sending the detection report to a server.
12. The electronic device of claim 10, wherein the memory is further configured to store a third threshold;
the processor is further configured to acquire fall data of the electronic device when detecting that a fall state of the electronic device is ended, where the fall data includes a fall height; when the falling height is larger than the third threshold value, detecting whether the designated hardware of the electronic equipment is abnormal or not to obtain a detection result; and when the specified hardware is abnormal, generating a detection report according to the detection result and the fall data, and sending the detection report to a server.
13. A fall information detection device, comprising:
the electronic equipment comprises an acquisition unit, a display unit and a control unit, wherein the acquisition unit is used for acquiring holding posture data and operating data of the electronic equipment when the electronic equipment is detected to enter a falling state; acquiring an unintentional falling probability value and an intentional falling probability value according to the holding posture data and the operation data;
the determining unit is used for determining that the electronic equipment is in an unintentional falling state when the unintentional falling probability value is larger than or equal to the intentional falling probability value.
14. A fall information detection method is applied to an electronic device comprising a processor and a gravity sensor connected with the processor, wherein:
the gravity sensor detects whether the electronic equipment enters a falling state or not;
the processor acquires holding posture data and operating data of the electronic equipment when the electronic equipment enters a falling state; acquiring an unintentional falling probability value and an intentional falling probability value according to the holding posture data and the operation data; determining that the electronic device is in an unintentional fall state when the unintentional fall probability value is greater than or equal to the intentional fall probability value.
15. An electronic device comprising a processor, a memory, a communication interface, and one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the processor, the programs comprising instructions for performing the steps of the method of any of claims 1-6.
16. A computer-readable storage medium for storing a computer program, wherein the computer program causes a computer to perform the method according to any one of claims 1-6.
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| CN109068006B (en) * | 2018-09-29 | 2021-04-02 | Oppo广东移动通信有限公司 | Drop reporting method, related equipment and storage medium |
| US11585828B2 (en) * | 2019-02-01 | 2023-02-21 | Seiko Epson Corporation | Sensor system and sensor drop determination method |
| CN110381196B (en) * | 2019-06-17 | 2022-04-26 | 深圳盈达机器视觉技术有限公司 | Control method for falling protection of mobile device and mobile device |
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| WO2006060077A1 (en) * | 2004-12-01 | 2006-06-08 | Freescale Semiconductor, Inc. | System and method for fall detection |
| CN201430692Y (en) * | 2009-06-04 | 2010-03-24 | 北京天安信通科技有限责任公司 | Wireless mobile terminal with fall alarm prompt and pedometer function |
| CN103493113A (en) * | 2011-04-29 | 2014-01-01 | 皇家飞利浦有限公司 | Method for detecting potential falls and a fall detector |
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| WO2006060077A1 (en) * | 2004-12-01 | 2006-06-08 | Freescale Semiconductor, Inc. | System and method for fall detection |
| CN201430692Y (en) * | 2009-06-04 | 2010-03-24 | 北京天安信通科技有限责任公司 | Wireless mobile terminal with fall alarm prompt and pedometer function |
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