CN111310627B - Detection method and device of sensing device and electronic equipment - Google Patents
Detection method and device of sensing device and electronic equipment Download PDFInfo
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F2218/00—Aspects of pattern recognition specially adapted for signal processing
- G06F2218/12—Classification; Matching
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01V—GEOPHYSICS; GRAVITATIONAL MEASUREMENTS; DETECTING MASSES OR OBJECTS; TAGS
- G01V3/00—Electric or magnetic prospecting or detecting; Measuring magnetic field characteristics of the earth, e.g. declination, deviation
- G01V3/12—Electric or magnetic prospecting or detecting; Measuring magnetic field characteristics of the earth, e.g. declination, deviation operating with electromagnetic waves
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01V—GEOPHYSICS; GRAVITATIONAL MEASUREMENTS; DETECTING MASSES OR OBJECTS; TAGS
- G01V3/00—Electric or magnetic prospecting or detecting; Measuring magnetic field characteristics of the earth, e.g. declination, deviation
- G01V3/38—Processing data, e.g. for analysis, for interpretation, for correction
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01V—GEOPHYSICS; GRAVITATIONAL MEASUREMENTS; DETECTING MASSES OR OBJECTS; TAGS
- G01V8/00—Prospecting or detecting by optical means
- G01V8/10—Detecting, e.g. by using light barriers
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F2218/00—Aspects of pattern recognition specially adapted for signal processing
- G06F2218/08—Feature extraction
- G06F2218/10—Feature extraction by analysing the shape of a waveform, e.g. extracting parameters relating to peaks
Abstract
The embodiment of the application provides a detection method and device of a sensing device and electronic equipment, wherein the detection method of the sensing device comprises the following steps: acquiring sensing data sensed by a sensing device in a certain time period; acquiring fluctuation data corresponding to the sensing data, wherein the fluctuation data is used for indicating the fluctuation degree of the sensing data; the type of the sensing device is determined from the fluctuation data. Based on different fluctuation characteristics of the sensing data of the sensing devices, the type of the sensing device can be determined through the fluctuation data corresponding to the sensing data, and normal use of software and hardware is ensured in a hardware replacement scene.
Description
Technical Field
The embodiment of the application relates to the technical field of sensing detection, in particular to a detection method and device of a sensing device and electronic equipment.
Background
With the progress of science and technology, home appliances with screens are gradually popularized, and the home appliances gradually evolve into intelligent home appliances, so that corresponding intelligent services can be provided.
An application scenario may be: when a user approaches the household appliance, the display screen of the household appliance is lightened, the intelligent service operates, and the intelligent household appliance can interact with the user. The intelligent household appliance can be provided with a human sense module for detecting whether a user approaches the household appliance. Common human sensing modules include microwave modules and infrared modules.
At present, software is developed in a matched manner based on a hardware module, namely, a type of human sense module needs to be determined firstly, and then the software is developed based on the type of human sense module. In the scene of hardware replacement, the timely adjustment of software is not facilitated, and the normal use is affected.
Disclosure of Invention
The embodiment of the application provides a detection method and device of a sensing device and electronic equipment, and in a hardware replacement scene, normal use of software and hardware is ensured.
In a first aspect, an embodiment of the present application provides a detection method of a sensing device, including:
acquiring sensing data sensed by a sensing device in a certain time period;
acquiring fluctuation data corresponding to the sensing data; the fluctuation data is used for indicating the fluctuation degree of the sensing data;
and determining the type of the sensing device according to the fluctuation data.
Optionally, before the obtaining the fluctuation data corresponding to the sensing data, the method further includes:
dividing the sensing data into a first set and a second set, wherein the value of the data included in the first set is smaller than or equal to a preset threshold value, and the value of the data included in the second set is larger than or equal to the preset threshold value;
the obtaining the fluctuation data corresponding to the sensing data comprises the following steps:
obtaining fluctuation data respectively corresponding to the first set and the second set;
the determining the type of the sensing device according to the fluctuation data comprises the following steps:
and determining the type of the sensing device according to fluctuation data corresponding to a target set, wherein the target set comprises the first set and/or the second set.
Optionally, the fluctuation data corresponding to the first set includes an absolute value of a difference value between two adjacent data in the first set, and the fluctuation data corresponding to the second set includes an absolute value of a difference value between two adjacent data in the second set.
Optionally, the determining the type of the sensing device according to the fluctuation data corresponding to the target set includes:
acquiring the number of data with the median value of fluctuation data corresponding to the target set being larger than a first preset value;
and determining the type of the sensing device according to the number of the data with the median value of the fluctuation data corresponding to the target set being larger than a first preset value.
Optionally, the determining the type of the sensing device according to the number of the data with the median value of the fluctuation data corresponding to the target set being greater than the first preset value includes:
if the number of the data with the fluctuation data median larger than the first preset value corresponding to the target set is larger than the second preset value, determining the type of the sensing device as an infrared sensing device;
and if the number of the data with the fluctuation data median larger than the first preset value corresponding to the target set is smaller than the second preset value, determining the type of the sensing device as a microwave sensing device.
Optionally, the target set includes the first set and the second set, and the determining the type of the sensing device according to the fluctuation data corresponding to the target set includes:
determining the type of the sensing device according to the fluctuation data corresponding to the first set and the fluctuation data corresponding to the second set respectively;
if the type of the sensing device is the same and is the first type according to the fluctuation data corresponding to the first set and the fluctuation data corresponding to the second set, determining that the type of the sensing device is the first type; or,
if the types of the sensing devices are different according to the fluctuation data corresponding to the first set and the fluctuation data corresponding to the second set, determining the types of the sensing devices according to the set formed by the fluctuation data corresponding to the first set and the fluctuation data corresponding to the second set.
Optionally, the method further comprises:
repeating the steps of acquiring the sensing data and determining the type of the sensing device for N times, wherein N is a positive integer greater than 1;
if the type of the sensing device is the same and the sensing device is the first type, the type of the sensing device is determined to be the first type.
Optionally, the type of the sensing device includes an infrared sensing device and a microwave sensing device.
In a second aspect, an embodiment of the present application provides a detection device of a sensing device, including:
the first acquisition module is used for acquiring sensing data sensed by the sensing device in a certain time period;
the second acquisition module is used for acquiring fluctuation data corresponding to the sensing data; the fluctuation data is used for indicating the fluctuation degree of the sensing data;
and the determining module is used for determining the type of the sensing device according to the fluctuation data.
Optionally, the device further comprises a dividing module, wherein the dividing module is used for dividing the sensing data into a first set and a second set before the second acquisition module acquires the fluctuation data corresponding to the sensing data, the value of the data included in the first set is smaller than or equal to a preset threshold, and the value of the data included in the second set is larger than or equal to the preset threshold;
the second obtaining module is specifically configured to:
obtaining fluctuation data respectively corresponding to the first set and the second set;
the determining module is specifically configured to:
and determining the type of the sensing device according to fluctuation data corresponding to a target set, wherein the target set comprises the first set and/or the second set.
Optionally, the fluctuation data corresponding to the first set includes an absolute value of a difference value between two adjacent data in the first set, and the fluctuation data corresponding to the second set includes an absolute value of a difference value between two adjacent data in the second set.
Optionally, the determining module is specifically configured to:
acquiring the number of data with the median value of fluctuation data corresponding to the target set being larger than a first preset value;
and determining the type of the sensing device according to the number of the data with the median value of the fluctuation data corresponding to the target set being larger than a first preset value.
Optionally, the determining module is specifically configured to:
if the number of the data with the fluctuation data median larger than the first preset value corresponding to the target set is larger than the second preset value, determining the type of the sensing device as an infrared sensing device;
and if the number of the data with the fluctuation data median larger than the first preset value corresponding to the target set is smaller than the second preset value, determining the type of the sensing device as a microwave sensing device.
Optionally, the target set includes the first set and the second set, and the determining module is specifically configured to:
determining the type of the sensing device according to the fluctuation data corresponding to the first set and the fluctuation data corresponding to the second set respectively;
if the type of the sensing device is the same and is the first type according to the fluctuation data corresponding to the first set and the fluctuation data corresponding to the second set, determining that the type of the sensing device is the first type; or,
if the types of the sensing devices are different according to the fluctuation data corresponding to the first set and the fluctuation data corresponding to the second set, determining the types of the sensing devices according to the set formed by the fluctuation data corresponding to the first set and the fluctuation data corresponding to the second set.
Optionally, the method further comprises:
repeating the steps of acquiring the sensing data and determining the type of the sensing device for N times, wherein N is a positive integer greater than 1;
if the type of the sensing device is the same and the sensing device is the first type, the type of the sensing device is determined to be the first type.
Optionally, the type of the sensing device includes an infrared sensing device and a microwave sensing device.
In a third aspect, an embodiment of the present application provides an electronic device, including: a memory and a processor;
the memory is used for storing program instructions;
the processor is configured to invoke the program instructions stored in the memory to implement a method provided in any embodiment of the first aspect of the present application.
In a fourth aspect, embodiments of the present application provide a computer-readable storage medium comprising: a readable storage medium and a computer program for implementing the method provided by any embodiment of the first aspect of the present application.
In a fifth aspect, embodiments of the present application provide a program product comprising a computer program (i.e., executing instructions) stored in a readable storage medium. The computer program may be read from a readable storage medium by a processor executing the computer program for carrying out the method provided by any embodiment of the first aspect of the present application.
The embodiment of the application provides a detection method, a detection device and electronic equipment of a sensing device, wherein the type of the sensing device can be determined according to fluctuation data by acquiring sensing data sensed by the sensing device in a certain time period and acquiring the fluctuation data corresponding to the sensing data. The type of the sensing device is not required to be known in advance, the type of the sensing device can be determined according to fluctuation data corresponding to the sensing data, the software development and the decoupling of hardware products are realized, and the normal use of the software and the hardware is ensured in a hardware replacement scene.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions of the prior art, the drawings that are needed in the embodiments or the description of the prior art will be briefly described below, it will be obvious that the drawings in the following description are some embodiments of the present invention, and that other drawings can be obtained according to these drawings without inventive effort to a person skilled in the art.
Fig. 1 is a schematic diagram of an application scenario applicable to an embodiment of the present application;
FIG. 2 is a schematic view of a display interface of a display screen of the refrigerator of FIG. 1;
FIG. 3 is a flowchart of a method for detecting a sensing device according to an embodiment of the present disclosure;
fig. 4 is a schematic diagram of data collected by an infrared sensing device in a scene with a far object according to an embodiment of the present application;
fig. 5 is a schematic diagram of data collected by the microwave sensing device in a far-object scene according to an embodiment of the present application;
fig. 6 is a schematic diagram of data collected by an infrared sensing device in an object shaking scene according to an embodiment of the present disclosure;
fig. 7 is a schematic diagram of data collected by the microwave sensing device in an object shaking scene according to an embodiment of the present application;
FIG. 8 is a schematic structural diagram of a detection device of a sensing device according to an embodiment of the present disclosure;
fig. 9 is a schematic structural diagram of an electronic device according to an embodiment of the present application.
Detailed Description
For the purposes of making the objects, technical solutions and advantages of the embodiments of the present application more clear, the technical solutions of 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 apparent that the described embodiments are some embodiments of the present application, but not all embodiments. All other embodiments, which can be made by one of ordinary skill in the art without undue burden from the present disclosure, are within the scope of the present disclosure.
The software in the prior art is developed in a matched manner based on a hardware module, namely, it is required to determine which type of sensing device is adopted first, for example, determine to adopt an infrared sensing device, and then develop the software based on the infrared sensing device. In the scene of the replacement of the sensing device, the software is not convenient to adjust in time, and the normal use is affected.
Based on the technical problem, the embodiment of the application provides a detection method of a sensing device, the type of the sensing device is not required to be known in advance, the sensing data of the sensing device in different types have different fluctuation characteristics, the sensing data of the sensing device in a certain time period are acquired, the fluctuation data corresponding to the sensing data are acquired, and the type of the sensing device can be determined according to the fluctuation data. The method and the device have the advantages that the software development and the hardware product decoupling are realized, the universality of the software development is improved, and the normal use of the software and the hardware is ensured in the scene of hardware replacement.
The detection method of the sensing device can be applied to any product comprising the sensing device. Fig. 1 is a schematic diagram of an application scenario applicable to an embodiment of the present application. In fig. 1, the on-screen refrigerator 11 includes a display screen 12 and a sensing device (not shown) for detecting whether a person approaches the on-screen refrigerator 11. As shown in the upper part of fig. 1, when a person is far from the refrigerator 11 with a screen, the display screen 12 may not be displayed in order to save power. As shown in the lower part of fig. 1, as the distance between the person and the refrigerator 11 with the screen is getting closer, the approach of the person to the refrigerator 11 with the screen can be detected by the sensing data of the sensing device, and at this time, the display screen 12 can display data to facilitate man-machine interaction between the person and the refrigerator 11 with the screen. The content that can be displayed on the display 12 is not limited in this embodiment. Fig. 2 is a schematic view of a display interface of a display screen of the refrigerator of fig. 1. As shown in fig. 2, information about time, date, place, temperature, etc. may be displayed on the display 12.
Fig. 3 is a flowchart of a detection method of a sensing device according to an embodiment of the present application. In the detection method of the sensing device provided in this embodiment, the execution body may be a detection device or an electronic apparatus of the sensing device. As shown in fig. 3, the detection method of the sensing device provided in this embodiment may include:
s301, acquiring sensing data sensed by a sensing device in a certain time period.
Wherein the sensing device may be used to detect whether an object is close to the sensing device. Optionally, in order to improve stability and accuracy of the obtained sensing data, the sensing data in a certain period of time after the sensing device works normally may be obtained. For example, in the scenario shown in fig. 1, after the refrigerator is started up and operates stably, sensing data of a sensing device in the refrigerator may be collected for a certain period of time.
Alternatively, the types of sensing devices may include, but are not limited to, infrared sensing devices and microwave sensing devices.
In this embodiment, the specific value of a certain period of time is not limited, and the amount of sensing data is not limited. For example, 30 sensing data within 30 seconds may be acquired.
S302, obtaining fluctuation data corresponding to the sensing data.
Wherein the fluctuation data is used for indicating the fluctuation degree of the sensing data.
In particular, the type of sensing device is different, and the fluctuation characteristics of the sensed data are generally different, and may include, but are not limited to, maximum value, minimum value, fluctuation range, and fluctuation change speed of the sensed data. Therefore, by acquiring the fluctuation data corresponding to the sensing data, the type of the sensing device can be determined according to the fluctuation data.
Optionally, the fluctuation data corresponding to the sensing data may include at least one or a combination of at least more of the following: maximum value of the sensing data, minimum value of the sensing data, average value of the sensing data, value range of the sensing data, difference value between two adjacent data in the sensing data, absolute value of difference value between two adjacent data in the sensing data and statistical distribution of the sensing data. Wherein at least a plurality means two or more.
In the following, the sensing data and the fluctuation data are exemplarily described in connection with different types of sensing devices and different scenes, but the types of sensing devices, the sensing data and the fluctuation data are not limited. For consistency, the examples shown in fig. 4 to 7 each show 10 sets of sensing data, with 30 sensing data per set. In order to intuitively show fluctuations in the sensor data, the sensor data of 3 groups, that is, group 1, group 2, and group 3, are shown graphically, wherein the abscissa in the graph represents the data number, specifically 1 to 30, and the ordinate represents the value of the sensor data.
In one example, referring to fig. 4, fig. 4 is a schematic diagram of data collected by an infrared sensing device in a far-object scene according to an embodiment of the present application. Fig. 4 (a) shows 10 sets of sensing data. Fig. 4 (b) shows 3 sets of sensing data of set 1, set 2 and set 3. As can be seen, for an infrared sensing device, in a scene where an object is far from the infrared sensing device, the fluctuation characteristics of the sensed data may be expressed as: the values of the sensed data relatively fluctuate widely, with the values of the sensed data typically being within 100. Fig. 4 (c) shows fluctuation data corresponding to each of group 1, group 2, and group 3, which is a difference between adjacent two data in the sensed data.
In another example, referring to fig. 5, fig. 5 is a schematic diagram of data collected by a microwave sensing device in a far scene of an object according to an embodiment of the present application. Fig. 5 (a) shows 10 sets of sensing data. Fig. 5 (b) shows the 3 sets of sensing data of set 1, set 2 and set 3. It can be seen that, for a microwave sensing device, in a scenario where an object is far from the infrared sensing device, the fluctuation characteristics of the sensing data may be expressed as: the values of the sensed data are relatively small in fluctuation, the values of the sensed data are usually within 5, and most are concentrated around 0. Fig. 5 (c) shows fluctuation data corresponding to each of group 1, group 2, and group 3, which is the absolute value of the difference between adjacent two data in the sense data.
In another example, referring to fig. 6, fig. 6 is a schematic diagram of data collected by an infrared sensing device in an object shaking scene according to an embodiment of the present application. Fig. 6 (a) shows 10 sets of sensing data. Fig. 6 (b) shows 3 sets of sensing data of set 1, set 2 and set 3. It can be seen that, for the infrared sensing device in a scene where the object is swayed, the fluctuation characteristic of the sensing data can be expressed as: the value of the sensing data relatively fluctuates more, and the closer the object is to the infrared sensing device, the larger the value of the sensing data. Fig. 6 (c) shows fluctuation data corresponding to each of group 1, group 2, and group 3, which is the absolute value of the difference between adjacent two data in the sense data.
In another example, referring to fig. 7, fig. 7 is a schematic diagram of data collected by the microwave sensing device in an object shaking scene according to an embodiment of the present application. Fig. 7 (a) shows 10 sets of sensing data. Fig. 7 (b) shows the 3 sets of sensing data of set 1, set 2 and set 3. It can be seen that, for a microwave sensing device in a scene of shaking an object, the fluctuation characteristic of the sensing data can be expressed as: the values of the sensed data are typically concentrated in both high and low value regions and have continuity. The high values typically range between 750-800 and the low values typically range from 0-3. In the data set region, the values of the sensed data are small relative to the wave. In this example, the fluctuation data may be a statistical distribution of the sensing data. For example, taking group 1 data as an example, the fluctuation data may be: the ratio of the sensing data in the value range of 0-3 is 1/3, and the ratio of the sensing data in the value range of 785-790 is 2/3.
S303, determining the type of the sensing device according to the fluctuation data.
It can be seen that, according to the detection method of the sensing device provided by the embodiment, based on that the sensing data of different types of sensing devices have different fluctuation characteristics, the type of the sensing device can be determined according to the fluctuation data by acquiring the sensing data within a certain period of time and acquiring the fluctuation data corresponding to the sensing data. Compared with the prior art, the detection method of the sensing device does not need to know the type of the sensing device in advance, carries out specific software development based on the specific sensing device, and determines the type of the sensing device by acquiring the sensing data of the sensing device, so that the universality of software development is improved for the software development and decoupling of hardware products, and in a hardware replacement scene, different software is adopted according to different hardware, so that the normal use of the software and the hardware is ensured.
Optionally, before acquiring the fluctuation data corresponding to the sensing data in S302, the method may further include:
the sensing data is divided into a first set and a second set. The value of the data included in the first set is smaller than or equal to a preset threshold value, and the value of the data included in the second set is larger than or equal to the preset threshold value.
Accordingly, in S302, acquiring the fluctuation data corresponding to the sensing data may include:
and acquiring fluctuation data corresponding to the first set and the second set respectively.
In S303, determining the type of the sensing device according to the fluctuation data may include:
and determining the type of the sensing device according to the fluctuation data corresponding to the target set. The target set includes the first set and/or the second set.
Specifically, in general, the closer an object is to the sensing device, the larger the value of the sensed data, and the farther the object is from the sensing device, the smaller the value of the sensed data. When the object shakes, the distance between the object and the sensing device changes at any time, and the value of the sensing data also changes. And dividing the sensing data in a certain period of time into two sets according to the magnitude relation between the value of the sensing data and a preset threshold value. The first set includes data with a value less than or equal to a preset threshold value corresponding to a scene of the object farther from the sensing device, and the second set includes data with a value greater than or equal to a preset threshold value corresponding to a scene of the object nearer to the sensing device. Based on different scenarios, three schemes for determining the type of sensing device are included. A scheme is as follows: in a scenario where the object is further from the sensing device, the type of the sensing device is determined from the fluctuation data corresponding to the first set. Another scheme is as follows: in a scene where the object is closer to the sensing device, determining the type of the sensing device according to the fluctuation data corresponding to the second set. Yet another scheme is: comprehensively considering the scenes of the object which is closer to and farther from the sensing device, and jointly determining the type of the sensing device according to the fluctuation data respectively corresponding to the first set and the second set.
By dividing the sensing data within a certain period of time into two sets and determining the type of the sensing device based on different scenes, the accuracy of determining the type of the sensing device is improved.
Note that, in this embodiment, the value of the preset threshold is not limited. For example, the preset threshold may be 100.
Optionally, in one possible implementation, the first set of fluctuation data includes an absolute value of a difference between two adjacent data in the first set, and the second set of fluctuation data includes an absolute value of a difference between two adjacent data in the second set.
Optionally, determining the type of the sensing device according to the fluctuation data corresponding to the target set may include:
and acquiring the number of the data with the median value of the fluctuation data corresponding to the target set being larger than a first preset value.
And determining the type of the sensing device according to the number of the data with the median value of the fluctuation data corresponding to the target set being larger than the first preset value.
Specifically, for both the first set and the second set, the corresponding fluctuation data is the absolute value of the difference between two adjacent data, and the larger the absolute value is, the larger the fluctuation of the sensing data is. Therefore, the type of the sensing device can be determined according to the number of the data with the fluctuation data median larger than the first preset value corresponding to the target set and the fluctuation characteristics of the sensing data of the sensing devices of various types. Wherein the target set comprises the first set and/or the second set. When the target set includes the first set and the second set, the number (denoted as K) of data whose fluctuation data median value is greater than the first preset value corresponding to the target set is the sum of the number (denoted as K1) of data whose fluctuation data median value is greater than the first preset value corresponding to the first set and the number (denoted as K2) of data whose fluctuation data median value is greater than the first preset value corresponding to the second set, that is, k=k1+k2.
It should be noted that, in this embodiment, the specific value of the first preset value is not limited. For example, the first preset value may be 5.
Optionally, determining the type of the sensing device according to the number of data with the median value of the fluctuation data corresponding to the target set being greater than the first preset value may include:
if the number of the data with the median value larger than the first preset value in the fluctuation data corresponding to the target set is larger than the second preset value, determining that the type of the sensing device is an infrared sensing device.
If the number of the data with the median value larger than the first preset value in the fluctuation data corresponding to the target set is smaller than the second preset value, determining the type of the sensing device as a microwave sensing device.
Specifically, the number of the data with the median value of the fluctuation data corresponding to the target set larger than the first preset value is larger than the second preset value, which indicates that the fluctuation of the sensing data is larger, and the type of the sensing device can be determined to be an infrared sensing device. On the contrary, the fluctuation of the sensing data is smaller, and the type of the sensing device can be determined to be a microwave sensing device.
For example. Assuming that the preset threshold is 100, the first preset value and the second preset value are both 5. See the fluctuation data shown in fig. 5 (c). For the wave data corresponding to the group 1, the target set may be a first set, and if the number of data with a value greater than 5 in the wave data (29) corresponding to the first set is 0, the type of the sensing device may be determined to be a microwave sensing device. See the fluctuation data shown in fig. 6 (c). For the fluctuation data corresponding to the group 1, the target set may be a first set and a second set, and the number of data with a value greater than 5 in the fluctuation data (29) corresponding to the first set and the second set is 23, and then the type of the sensing device may be determined to be an infrared sensing device.
It should be noted that, in this embodiment, the specific value of the second preset value is not limited.
Optionally, the target set includes a first set and a second set, and determining the type of the sensing device according to the fluctuation data corresponding to the target set may include:
and determining the type of the sensing device according to the fluctuation data corresponding to the first set and the fluctuation data corresponding to the second set.
And if the type of the sensing device is the same as the first type according to the fluctuation data corresponding to the first set and the fluctuation data corresponding to the second set, determining that the type of the sensing device is the first type. Or,
if the types of the sensing devices are different according to the fluctuation data corresponding to the first set and the fluctuation data corresponding to the second set, the types of the sensing devices are determined according to the set formed by the fluctuation data corresponding to the first set and the fluctuation data corresponding to the second set.
Specifically, the type of the sensing device may be determined according to the fluctuation data corresponding to the first set, and the type of the sensing device may be determined according to the fluctuation data corresponding to the second set. The accuracy of determining the type of sensing device is improved if the type of sensing device determined by the first set and the second set is the same. If the types of the sensing devices determined through the first set and the second set are different, the types of the sensing devices are further determined according to the aggregate sets of the fluctuation data corresponding to the first set and the second set, and accuracy of determining the types of the sensing devices is improved.
The type of the sensing device is determined according to the fluctuation data corresponding to the first set, the type of the sensing device is determined according to the fluctuation data corresponding to the second set, and the type of the sensing device is determined according to the set composed of the fluctuation data corresponding to the first set and the fluctuation data corresponding to the second set, which can be referred to the above-mentioned method for determining the type of the sensing device according to the fluctuation data corresponding to the target set, and the principle is similar and will not be repeated here.
Optionally, the detection method of the sensing device provided in this embodiment may further include:
the steps of acquiring the sensing data and determining the type of the sensing device are repeated N times, N being a positive integer greater than 1.
If the type of the sensing device is the same and the sensing device is the first type, the type of the sensing device is determined to be the first type.
Specifically, in consideration of randomness of the sensing data in a certain period of time, there may be a judgment error, and therefore, the type of the sensing device is determined by acquiring the sensing data in different periods of time multiple times, and if the types of the sensing devices determined multiple times are the same, accuracy of determining the type of the sensing device is improved.
In this embodiment, the value of N is not limited. For example, the value of N is 3.
Fig. 8 is a schematic structural diagram of a detection device of a sensing device according to an embodiment of the present application. The detection device of the sensing device provided in this embodiment is used to execute the detection method of the sensing device provided in the embodiment shown in fig. 1 to 7. As shown in fig. 8, the detection device of the sensing device provided in this embodiment may include:
a first obtaining module 81, configured to obtain sensing data sensed by the sensing device during a certain period of time;
a second obtaining module 82, configured to obtain fluctuation data corresponding to the sensing data; the fluctuation data is used for indicating the fluctuation degree of the sensing data;
a determining module 83 for determining the type of the sensing device based on the fluctuation data.
Optionally, the system further includes a dividing module, where the dividing module is configured to divide the sensing data into a first set and a second set before the second obtaining module 82 obtains the fluctuation data corresponding to the sensing data, where a value of the data included in the first set is less than or equal to a preset threshold value, and a value of the data included in the second set is greater than or equal to the preset threshold value;
the second obtaining module 82 is specifically configured to:
obtaining fluctuation data respectively corresponding to the first set and the second set;
the determining module 83 is specifically configured to:
and determining the type of the sensing device according to fluctuation data corresponding to a target set, wherein the target set comprises the first set and/or the second set.
Optionally, the fluctuation data corresponding to the first set includes an absolute value of a difference value between two adjacent data in the first set, and the fluctuation data corresponding to the second set includes an absolute value of a difference value between two adjacent data in the second set.
Optionally, the determining module 83 is specifically configured to:
acquiring the number of data with the median value of fluctuation data corresponding to the target set being larger than a first preset value;
and determining the type of the sensing device according to the number of the data with the median value of the fluctuation data corresponding to the target set being larger than a first preset value.
Optionally, the determining module 83 is specifically configured to:
if the number of the data with the fluctuation data median larger than the first preset value corresponding to the target set is larger than the second preset value, determining the type of the sensing device as an infrared sensing device;
and if the number of the data with the fluctuation data median larger than the first preset value corresponding to the target set is smaller than the second preset value, determining the type of the sensing device as a microwave sensing device.
Optionally, the target set includes the first set and the second set, and the determining module 83 is specifically configured to:
determining the type of the sensing device according to the fluctuation data corresponding to the first set and the fluctuation data corresponding to the second set respectively;
if the type of the sensing device is the same and is the first type according to the fluctuation data corresponding to the first set and the fluctuation data corresponding to the second set, determining that the type of the sensing device is the first type; or,
if the types of the sensing devices are different according to the fluctuation data corresponding to the first set and the fluctuation data corresponding to the second set, determining the types of the sensing devices according to the set formed by the fluctuation data corresponding to the first set and the fluctuation data corresponding to the second set.
Optionally, the method further comprises:
repeating the steps of acquiring the sensing data and determining the type of the sensing device for N times, wherein N is a positive integer greater than 1;
if the type of the sensing device is the same and the sensing device is the first type, the type of the sensing device is determined to be the first type.
Optionally, the type of the sensing device includes an infrared sensing device and a microwave sensing device.
The detection device of the sensing device provided in this embodiment is used to execute the detection method of the sensing device provided in the embodiments shown in fig. 1 to 7, and the technical principle and the technical effect are similar, and are not repeated here.
Fig. 9 is a schematic structural diagram of an electronic device according to an embodiment of the present application. As shown in fig. 9, the electronic device may include a processor 91 and a memory 92. The memory 92 is configured to store instructions, and the processor 91 is configured to execute the instructions stored in the memory 92, so that the electronic device executes the detection method of the sensing device provided in the embodiment shown in fig. 1 to 7, and the technical principle and the technical effect are similar, and are not repeated herein.
Note that, the type and physical form of the electronic device are not limited in this embodiment. For example, the electronic device may be a processor, chip, etc. having data processing capabilities, or a device comprising a sensing means, such as a refrigerator with a screen, an air conditioner with a screen, etc. The present embodiment does not limit other components included in the electronic apparatus.
Those of ordinary skill in the art will appreciate that: all or part of the steps for implementing the method embodiments described above may be performed by hardware associated with program instructions. The foregoing program may be stored in a computer readable storage medium. The program, when executed, performs steps including the method embodiments described above; and the aforementioned storage medium includes: various media that can store program code, such as ROM, RAM, magnetic or optical disks.
Finally, it should be noted that: the above embodiments are only for illustrating the technical solution of the embodiments of the present invention, and are not limited thereto; although embodiments of the present invention have been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical scheme described in the foregoing embodiments can be modified or some or all of the technical features thereof can be replaced by equivalents; such modifications and substitutions do not depart from the spirit of the technical solutions according to the embodiments of the present invention.
Claims (13)
1. A method of detecting a sensing device, comprising:
acquiring sensing data sensed by a sensing device in a certain time period;
acquiring fluctuation data corresponding to the sensing data, wherein the fluctuation data is used for indicating the fluctuation degree of the sensing data; wherein the sensing data of the different types of sensing devices have different fluctuation characteristics;
determining the type of the sensing device according to the fluctuation data;
before the obtaining of the fluctuation data corresponding to the sensing data, the method further comprises the following steps:
dividing the sensing data into a first set and a second set, wherein the value of the data included in the first set is smaller than or equal to a preset threshold value, and the value of the data included in the second set is larger than or equal to the preset threshold value;
the obtaining the fluctuation data corresponding to the sensing data comprises the following steps:
obtaining fluctuation data respectively corresponding to the first set and the second set;
the determining the type of the sensing device according to the fluctuation data comprises the following steps:
and determining the type of the sensing device according to fluctuation data corresponding to a target set, wherein the target set comprises the first set and/or the second set.
2. The method of claim 1, wherein the first set of corresponding fluctuation data comprises an absolute value of a difference between two adjacent data in the first set, and the second set of corresponding fluctuation data comprises an absolute value of a difference between two adjacent data in the second set.
3. The method of claim 2, wherein determining the type of the sensing device based on the fluctuation data corresponding to the target set comprises:
acquiring the number of data with the median value of fluctuation data corresponding to the target set being larger than a first preset value;
and determining the type of the sensing device according to the number of the data with the median value of the fluctuation data corresponding to the target set being larger than a first preset value.
4. A method according to claim 3, wherein determining the type of the sensing device according to the number of data whose fluctuation data median is greater than a first preset value corresponding to the target set comprises:
if the number of the data with the fluctuation data median larger than the first preset value corresponding to the target set is larger than the second preset value, determining the type of the sensing device as an infrared sensing device;
and if the number of the data with the fluctuation data median larger than the first preset value corresponding to the target set is smaller than the second preset value, determining the type of the sensing device as a microwave sensing device.
5. The method of any of claims 1-4, wherein the set of targets comprises the first set and the second set, wherein determining the type of the sensing device based on the fluctuation data corresponding to the set of targets comprises:
determining the type of the sensing device according to the fluctuation data corresponding to the first set and the fluctuation data corresponding to the second set respectively;
if the type of the sensing device is the same and is the first type according to the fluctuation data corresponding to the first set and the fluctuation data corresponding to the second set, determining that the type of the sensing device is the first type; or,
if the types of the sensing devices are different according to the fluctuation data corresponding to the first set and the fluctuation data corresponding to the second set, determining the types of the sensing devices according to the set formed by the fluctuation data corresponding to the first set and the fluctuation data corresponding to the second set.
6. The method of any one of claims 1-4, further comprising:
repeating the steps of acquiring the sensing data and determining the type of the sensing device for N times, wherein N is a positive integer greater than 1;
if the type of the sensing device is the same and the sensing device is the first type, the type of the sensing device is determined to be the first type.
7. The method of any one of claims 1-4, wherein the types of sensing devices include infrared sensing devices and microwave sensing devices.
8. A sensing device detection device, comprising:
the first acquisition module is used for acquiring sensing data sensed by the sensing device in a certain time period;
the second acquisition module is used for acquiring fluctuation data corresponding to the sensing data, wherein the fluctuation data is used for indicating the fluctuation degree of the sensing data; wherein the sensing data of the different types of sensing devices have different fluctuation characteristics;
a determining module for determining the type of the sensing device according to the fluctuation data;
the device comprises a first acquisition module, a second acquisition module and a dividing module, wherein the first acquisition module is used for acquiring fluctuation data corresponding to sensing data, the dividing module is used for dividing the sensing data into a first set and a second set, the value of the data included in the first set is smaller than or equal to a preset threshold value, and the value of the data included in the second set is larger than or equal to the preset threshold value;
the second obtaining module is specifically configured to:
obtaining fluctuation data respectively corresponding to the first set and the second set;
the determining module is specifically configured to:
and determining the type of the sensing device according to fluctuation data corresponding to a target set, wherein the target set comprises the first set and/or the second set.
9. The apparatus of claim 8, wherein the first set of corresponding fluctuation data comprises an absolute value of a difference between two adjacent data in the first set, and the second set of corresponding fluctuation data comprises an absolute value of a difference between two adjacent data in the second set.
10. The apparatus of claim 9, wherein the determining module is specifically configured to:
acquiring the number of data with the median value of fluctuation data corresponding to the target set being larger than a first preset value;
and determining the type of the sensing device according to the number of the data with the median value of the fluctuation data corresponding to the target set being larger than a first preset value.
11. The apparatus of claim 10, wherein the determining module is specifically configured to:
if the number of the data with the fluctuation data median larger than the first preset value corresponding to the target set is larger than the second preset value, determining the type of the sensing device as an infrared sensing device;
and if the number of the data with the fluctuation data median larger than the first preset value corresponding to the target set is smaller than the second preset value, determining the type of the sensing device as a microwave sensing device.
12. An electronic device, comprising: a memory and a processor;
the memory is used for storing program instructions;
the processor for invoking the program instructions stored in the memory to implement the method of any of claims 1-7.
13. A computer-readable storage medium, comprising: a readable storage medium and a computer program for implementing the method according to any of claims 1-7.
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