CN113671489B - State reminding method and device, electronic equipment and computer readable storage medium - Google Patents
State reminding method and device, electronic equipment and computer readable storage medium Download PDFInfo
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Classifications
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S13/00—Systems using the reflection or reradiation of radio waves, e.g. radar systems; Analogous systems using reflection or reradiation of waves whose nature or wavelength is irrelevant or unspecified
- G01S13/88—Radar or analogous systems specially adapted for specific applications
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01L—MEASURING FORCE, STRESS, TORQUE, WORK, MECHANICAL POWER, MECHANICAL EFFICIENCY, OR FLUID PRESSURE
- G01L1/00—Measuring force or stress, in general
- G01L1/16—Measuring force or stress, in general using properties of piezoelectric devices
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01L—MEASURING FORCE, STRESS, TORQUE, WORK, MECHANICAL POWER, MECHANICAL EFFICIENCY, OR FLUID PRESSURE
- G01L1/00—Measuring force or stress, in general
- G01L1/18—Measuring force or stress, in general using properties of piezo-resistive materials, i.e. materials of which the ohmic resistance varies according to changes in magnitude or direction of force applied to the material
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01V—GEOPHYSICS; GRAVITATIONAL MEASUREMENTS; DETECTING MASSES OR OBJECTS; TAGS
- G01V9/00—Prospecting or detecting by methods not provided for in groups G01V1/00 - G01V8/00
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- G06N3/02—Neural networks
- G06N3/04—Architecture, e.g. interconnection topology
- G06N3/045—Combinations of networks
Abstract
The application provides a state reminding method and device, electronic equipment and a computer readable storage medium; wherein the method comprises the following steps: acquiring an electric signal generated by a target sensor, wherein the electric signal is obtained by converting pressure detected by the target sensor, and the pressure is generated by a target object at a target position; acquiring image data after the target object leaves the target position and determining whether the target object is in a target state based on the image data under the condition that the electric signal represents that the target object leaves the target position; and sending a state reminding message under the condition that the target object is in the target state. According to the application, the problems that the state reminding is not timely and inaccurate caused by monitoring the state of the old through the camera device in the prior art are solved.
Description
Technical Field
The application relates to the field of intelligent equipment, in particular to a state reminding method and device, electronic equipment and a computer readable storage medium.
Background
Along with the development of society, the social rhythm is gradually accelerated, the aging of population is continuously aggravated, and the pressure of young people is increased. The young people are busy working and do not care for the old people, so that more families select to send the old people into the nursing home, at present, the old people can be cared for through carers in the nursing home, but the old people cannot be cared for in real time, the old people can be monitored through the installation of the camera device, special personnel are required to monitor the old people before the display, and under the condition that the old people are more, the situation of the old people which needs help cannot be timely checked from the display can be caused, so that help cannot be timely provided for the old people which needs help.
In view of the above technical problems, no effective solution exists at present.
Disclosure of Invention
The embodiment of the application aims to provide a state reminding method and device, electronic equipment and a computer readable storage medium, so as to solve the problems that in the prior art, the state reminding is not timely and inaccurate due to the fact that the state of the old is monitored through a camera device. The specific technical scheme is as follows:
in a first aspect, a state reminding method is provided, including: acquiring an electric signal generated by a target sensor, wherein the electric signal is obtained by converting pressure detected by the target sensor, and the pressure is generated by a target object at a target position; acquiring image data after the target object leaves the target position and determining whether the target object is in a target state based on the image data under the condition that the electric signal represents that the target object leaves the target position; and sending a state reminding message under the condition that the target object is in the target state.
In a second aspect, a status alert device is provided, including: the acquisition module is used for acquiring an electric signal generated by the target sensor, wherein the electric signal is obtained by converting the pressure detected by the target sensor, and the pressure is generated by a target object at a target position; a processing module for acquiring image data of the target object after leaving the target position and determining whether the target object is in a target state based on the image data if the electrical signal is determined to characterize the target object leaving the target position; and the sending module is used for sending a state reminding message under the condition that the target object is in the target state.
In a third aspect, there is also provided a computer readable storage medium having instructions stored therein which, when run on a computer, cause the computer to perform the method of the first aspect described above.
In a fourth aspect, there is also provided a computer program product containing instructions which, when run on a computer, cause the computer to perform the method of the first aspect described above.
According to the application, the electric signal generated by the target object at the target position can be obtained through the target sensor, whether the target object leaves the target position is judged according to the electric signal, whether the target object is in a target state is further determined, and if the target object is in the target state, a state reminding message is sent. If the target state is a dangerous state or a help seeking state, a state reminding message is sent, so that the related personnel of the target object can be timely and accurately reminded, the safety guarantee of the target object is improved, and the problem that the state reminding is not timely and accurate due to the fact that the state of the old is monitored through the camera device in the prior art is solved.
Drawings
FIG. 1 is a flow chart of a status alert method according to an embodiment of the present application;
FIG. 2 is a schematic diagram of a CNN-based decision fall according to an embodiment of the present application;
FIG. 3 is a schematic structural diagram of a status reminding device according to an embodiment of the application;
fig. 4 is a schematic structural diagram of an electronic device according to an embodiment of the present application.
Detailed Description
The technical solutions in the embodiments of the present application will be described below with reference to the accompanying drawings in the embodiments of the present application.
The embodiment of the application provides a state reminding method, as shown in fig. 1, comprising the following steps:
102, acquiring an electric signal generated by a target sensor, wherein the electric signal is obtained by converting the pressure detected by the target sensor, and the pressure is the pressure generated by a target object at a target position;
it should be noted that, the target sensor in the embodiment of the present application is a sensor for detecting pressure, such as a piezoelectric thin film sensor; other sensors capable of detecting pressure may be used as the target sensor, such as piezoelectric pressure sensors, piezoresistive pressure sensors, and the like.
The target object in the embodiment of the application can be a user needing to be detected, such as a special crowd with inconvenient actions, a user with higher age or a user with lower age.
The target position may be a sleeping position on a bed, or may be a position on a sofa, i.e. the target sensor may be installed at a position where the user sleeps or lies down, so as to detect the pressure of the user on the position, and further determine whether the user leaves the position, if the target object generates pressure at the target position, the pressure may be converted into an electrical signal, so as to determine that the user leaves the position if the electrical signal is absent.
Step 104, under the condition that the electric signal is determined to represent that the target object leaves the target position, collecting image data of the target object after the target object leaves the target position, and determining whether the target object is in a target state or not based on the image data;
it should be noted that, the target state in the embodiment of the present application refers to a dangerous state where the target object is dangerous, a state where help is required, or other states where other people need to be reminded. The dangerous state of the target object is walking comparison, the target object is in a help-seeking state, such as a help-seeking action with longer duration in one place, and the potential dangerous state is present, such as a life state with more fuzzy consciousness, and the state that the target object leaves the target position and tries to leave when the door is opened, namely the door is opened is the target state.
And step 106, sending a state reminding message when the target object is in the target state.
It should be noted that, the reminding message may be a reminding by indoor broadcasting, or a reminding on a mobile phone of an associated person who sends the target object, or other manners. Specifically, one or more reminding modes can be set according to actual conditions.
Through the steps 102 to 106, the electric signal generated by the target object at the target position can be obtained through the target sensor, and then whether the target object leaves the target position is judged according to the electric signal, and further whether the target object is in the target state is determined, and if the target object is in the target state, a state reminding message is sent. If the target state is a dangerous state or a help seeking state, a state reminding message is sent, so that the related personnel of the target object can be timely and accurately reminded, the safety guarantee of the target object is improved, and the problem that the state reminding is not timely and accurate due to the fact that the state of the old is monitored through the camera device in the prior art is solved.
It should be noted that, the execution subject of the method steps in the embodiment of the present application may be an intelligent device, such as a mobile phone, a computer, or other devices, such as a processor. The intelligent device or processor may be wirelessly connected with the target sensor and may also be integrated with a neural network model for discriminating the target state.
In an embodiment of the present application, for the manner of determining that the electrical signal characterizes the target object leaving the target position in step 102, the method further may include:
step 11, performing low-pass filtering on the electric signal;
taking the example that the target object is on the bed, the piezoelectric film sensor is placed under the mattress or the pillow of the user, and whether the user gets up or not is judged through the change of the electric signals before and after getting up, specifically, an obvious falling edge and an obvious rising edge are formed at the initial moment, the piezoelectric film sensor is used for getting up and getting up, and after sleeping for a period of time, the piezoelectric film sensor is used for representing that the user body moves to get up.
Step 12, carrying out mean value shaping on the electric signal subjected to low-pass filtering to obtain a corresponding rectangular wave;
the average filtering is to filter out some high-frequency signals, the average shaping is to correct the signal waveform into rectangular waves, the rising edge is the time of getting in the bed of the user, and the detecting rising edge is to detect the getting out of the bed of the user.
Step 13, in the case of detecting a rising edge in the rectangular wave, determining that the target object leaves the target position.
Through the steps 11 to 13, the electric signal is detected based on the target sensor, so that whether the target object leaves the target position can be determined according to the electric signal, and whether the target object leaves the target position can be conveniently and rapidly determined.
In another optional implementation manner of the embodiment of the present application, for the manner of acquiring the image data of the target object after leaving the target position in step 104, the method may further include:
step 21, collecting multi-frame continuous signals after a target object leaves a target position;
step 22 converts the multi-frame continuous signal into image data.
In the embodiment of the application, the millimeter wave radar can be used for collecting multi-frame continuous signals after the target object leaves the target position, so that the image data after the target object leaves the target position is determined to monitor the state after getting up in real time, and compared with the monitoring of the camera device, the method and the device are more timely and accurate.
In another optional implementation manner of the embodiment of the present application, for the manner of determining whether the target object is the target state based on the image data referred to in the step 104, the method may further include:
step 31, inputting image data into a target neural network model;
and step 32, determining the probability that the target object is in the target state based on the target neural network model, and outputting a comparison result of the probability and a preset threshold, wherein the comparison result is used for representing whether the target object is in the target state or not.
The target neural network model may be a convolutional neural network (Convolutional Neural Networks, CNN), specifically, as shown in fig. 2, an image is sent into the CNN to perform feature extraction and discrimination, and if the probability of discriminating a fall is greater than a certain threshold, the fall is determined. The final output can be expressed as:
y＝Softmax(xi)i＝0,1,···n (1)
wherein xi in the formula (1) represents the feature of the ith frame image extracted by CNN, and y is the discrimination probability of each frame image. The equation (2) is a case where the output discrimination probability is equal to or greater than threshold, and the fall state is determined. For example, assume that the threshold is 0.8. Firstly training the CNN discrimination model, wherein the training can be based on a training sample, the training sample comprises a large number of images, the images comprise image data of different user activities, after the training is finished, a state image is input, the probability y of falling is output through a formula (1), in a formula (2), if the falling probability y is greater than or equal to a threshold value of 0.8, the user is judged to fall, otherwise, the user is judged not to fall.
The method for outputting the comparison result of the probability and the preset threshold in the step 32 may further include:
step 41, outputting a comparison result for representing that the target object is in the target state under the condition that the probability is larger than a preset threshold value;
and step 42, outputting a comparison result for representing that the target object is in a non-target state under the condition that the probability is less than or equal to a preset threshold value.
It should be noted that the preset threshold may be determined based on a training result of the neural network model. Therefore, the state of the target object of the user is automatically judged based on the neural network model, and the judgment is not needed to be performed before the image pickup device, so that the efficiency of target state monitoring is improved.
The present application will be illustrated below with reference to specific implementations of embodiments of the application. The concrete embodiment provides a state monitoring method, which adopts a piezoelectric film module to monitor the sleeping of a person in real time, a millimeter wave radar is used for monitoring the behavior state after getting up, and a CNN algorithm in deep learning is used for judging whether a fall occurs or not. The method specifically comprises the following steps:
step 201, monitoring the in-bed state of a target object in real time through a piezoelectric film sensor placed under a mattress or a pillow.
Specifically, after a target object gets on bed, the piezoelectric film module generates an electric signal change due to pressure change applied to the mattress or the pillow. And carrying out low-pass filtering, average value shaping and rising edge counting detection on the generated electric signals, and finally judging whether a user gets up or not according to the change of the electric signals. And after the user is judged to be up, starting the millimeter wave radar to monitor the user behavior.
Step 202, if the target object is detected to be up, turning on a millimeter wave radar for real-time monitoring, continuously transmitting signals by the millimeter wave radar for monitoring, processing the acquired echo signals by a signal processor, and converting the echo signals into point cloud data, wherein the point cloud data comprises a distance, an azimuth angle and a Doppler speed. Further, cluster analysis is carried out on the point cloud data, and multi-frame continuous images corresponding to the multi-frame continuous echo signals are obtained.
Step 203, tracking and positioning of a user are realized through a Kalman algorithm;
step 204, adopting buzzing alarm to remind surrounding people and remotely inform staff to rescue the target object when the CNN determines that the falling action occurs.
The CNN performs feature extraction on the input image data, the extracted features include the posture, the height and the like of a person, then the extracted features are used for judging, the final output is the probability of falling or not through calculation of a softmax function, for example, a piece of image data, and after the CNN is subjected to feature extraction, the output is judged to judge that the probability of falling of the user is 90%.
Through this concrete implementation, adopt piezoelectric film module to carry out real-time monitoring to the gesture when sleeping, millimeter wave radar is used for monitoring the behavior after getting up, utilizes deep learning CNN technique to judge whether to take place to fall down, has improved the judgement rate of accuracy.
Based on fig. 1, an embodiment of the present application further provides a status reminding device, as shown in fig. 3, where the status reminding device includes:
an acquisition module 32, configured to acquire an electrical signal generated by the target sensor, where the electrical signal is obtained by converting a pressure detected by the target sensor, and the pressure is a pressure generated by the target object at the target position;
a processing module 34, configured to, in a case where it is determined that the electrical signal characterizes that the target object leaves the target position, collect image data after the target object leaves the target position, and determine whether the target object is in a target state based on the image data;
and a sending module 36, configured to send a state alert message when the target object is in the target state.
By the device provided by the embodiment of the application, the electric signal generated by the target object at the target position can be acquired through the target sensor, whether the target object leaves the target position is judged according to the electric signal, whether the target object is in the target state is further determined, and if the target object is in the target state, a state reminding message is sent. If the target state is a dangerous state or a help seeking state, a state reminding message is sent, so that the related personnel of the target object can be timely and accurately reminded, the safety guarantee of the target object is improved, and the problem that the state reminding is not timely and accurate due to the fact that the state of the old is monitored through the camera device in the prior art is solved.
Optionally, the apparatus of the embodiment of the present application may further include: the filtering module is used for carrying out low-pass filtering on the electric signals; the shaping module is used for carrying out mean value shaping on the electric signal subjected to low-pass filtering to obtain a corresponding rectangular wave; and the determining module is used for determining that the target object leaves the target position under the condition that the rising edge in the rectangular wave is detected.
Optionally, the processing module 34 of the embodiment of the present application may further include: the acquisition unit is used for acquiring multi-frame continuous signals after the target object leaves the target position; and a conversion unit for converting the multi-frame continuous signal into image data.
Optionally, the processing module 34 of the embodiment of the present application may further include: an input unit for inputting image data into a target neural network model; the processing unit is used for determining the probability that the target object is in the target state based on the target neural network model and outputting a result according to the comparison result of the probability and a preset threshold value, wherein the result comparison result is used for representing whether the target object is in the target state or not.
Optionally, the processing unit of the embodiment of the present application includes: the first output subunit is used for outputting a comparison result used for representing that the target object is in the target state under the condition that the probability is larger than a preset threshold value; and the second output subunit is used for outputting a comparison result used for representing that the target object is in a non-target state under the condition that the probability is smaller than or equal to a preset threshold value.
The embodiment of the application also provides an electronic device, as shown in fig. 4, which comprises a processor 401, a communication interface 402, a memory 403 and a communication bus 404, wherein the processor 401, the communication interface 402 and the memory 403 complete communication with each other through the communication bus 404,
a memory 403 for storing a computer program;
the processor 401, when configured to execute the program stored in the memory 403, implements the method steps in fig. 1, and functions similar to the method steps in fig. 1, which are not described herein again.
The communication bus mentioned by the above terminal may be a peripheral component interconnect standard (Peripheral Component Interconnect, abbreviated as PCI) bus or an extended industry standard architecture (Extended Industry Standard Architecture, abbreviated as EISA) bus, etc. The communication bus may be classified as an address bus, a data bus, a control bus, or the like. For ease of illustration, only one thick line is shown in fig. 4, but not only one bus or one type of bus.
The communication interface is used for communication between the terminal and other devices.
The memory may include random access memory (Random Access Memory, RAM) or non-volatile memory (non-volatile memory), such as at least one disk memory. Optionally, the memory may also be at least one memory device located remotely from the aforementioned processor.
The processor may be a general-purpose processor, including a central processing unit (Central Processing Unit, CPU for short), a network processor (Network Processor, NP for short), etc.; but also digital signal processors (Digital Signal Processing, DSP for short), application specific integrated circuits (Application Specific Integrated Circuit, ASIC for short), field-programmable gate arrays (Field-Programmable Gate Array, FPGA for short) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components.
In yet another embodiment of the present application, a computer readable storage medium is provided, in which instructions are stored, which when run on a computer, cause the computer to perform the state alert method according to any of the above embodiments.
In yet another embodiment of the present application, a computer program product containing instructions that, when run on a computer, cause the computer to perform the status alert method of any of the above embodiments is also provided.
In the above embodiments, it may be implemented in whole or in part by software, hardware, firmware, or any combination thereof. When implemented in software, may be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions. When loaded and executed on a computer, produces a flow or function in accordance with embodiments of the present application, in whole or in part. The computer may be a general purpose computer, a special purpose computer, a computer network, or other programmable apparatus. The computer instructions may be stored in or transmitted from one computer-readable storage medium to another, for example, by wired (e.g., coaxial cable, optical fiber, digital Subscriber Line (DSL)), or wireless (e.g., infrared, wireless, microwave, etc.). The computer readable storage medium may be any available medium that can be accessed by a computer or a data storage device such as a server, data center, etc. that contains an integration of one or more available media. The usable medium may be a magnetic medium (e.g., floppy Disk, hard Disk, magnetic tape), an optical medium (e.g., DVD), or a semiconductor medium (e.g., solid State Disk (SSD)), etc.
It is noted that relational terms such as first and second, and the like are used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Moreover, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising one … …" does not exclude the presence of other like elements in a process, method, article, or apparatus that comprises the element.
In this specification, each embodiment is described in a related manner, and identical and similar parts of each embodiment are all referred to each other, and each embodiment mainly describes differences from other embodiments. In particular, for system embodiments, since they are substantially similar to method embodiments, the description is relatively simple, as relevant to see a section of the description of method embodiments.
The foregoing description is only of the preferred embodiments of the present application and is not intended to limit the scope of the present application. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application are included in the protection scope of the present application.
Claims (8)
1. A method for status alert, comprising:
acquiring an electric signal generated by a target sensor, wherein the electric signal is obtained by converting pressure detected by the target sensor, and the pressure is generated by a target object at a target position;
acquiring image data after the target object leaves the target position and determining whether the target object is in a target state based on the image data under the condition that the electric signal represents that the target object leaves the target position;
sending a state reminding message under the condition that the target object is in the target state;
wherein the determining whether the target object is a target state based on the image data includes: inputting the image data into a target neural network model; determining the probability of the target object in the target state based on the target neural network model, and outputting a comparison result of the probability and a preset threshold, wherein the comparison result is used for representing whether the target object is in the target state;
outputting a comparison result of the probability and a preset threshold value, wherein the comparison result comprises the following steps: outputting a comparison result for representing the target object as the target state under the condition that the probability is larger than the preset threshold value; and outputting a comparison result used for representing that the target object is in a non-target state under the condition that the probability is smaller than or equal to the preset threshold value.
2. The method of claim 1, wherein the determining that the electrical signal characterizes the target object leaving the target location comprises:
low-pass filtering the electrical signal;
performing average value shaping on the electric signal subjected to low-pass filtering to obtain a corresponding rectangular wave;
in the event that a rising edge in the rectangular wave is detected, it is determined that the target object leaves the target position.
3. The method of claim 1, wherein the acquiring image data of the target object after leaving the target location comprises:
collecting multi-frame continuous signals of the target object after leaving the target position;
the multi-frame continuous signal is converted into the image data.
4. A status alert device comprising:
the acquisition module is used for acquiring an electric signal generated by the target sensor, wherein the electric signal is obtained by converting the pressure detected by the target sensor, and the pressure is generated by a target object at a target position;
a processing module for acquiring image data of the target object after leaving the target position and determining whether the target object is in a target state based on the image data if the electrical signal is determined to characterize the target object leaving the target position;
the sending module is used for sending a state reminding message under the condition that the target object is in the target state;
wherein the processing module comprises: an input unit for inputting the image data into a target neural network model; the processing unit is used for determining the probability of the target object in the target state based on the target neural network model and outputting a comparison result of the probability and a preset threshold, wherein the comparison result is used for representing whether the target object is in the target state or not;
the processing unit is further configured to output a comparison result for representing that the target object is in the target state when the probability is greater than the preset threshold; and outputting a comparison result used for representing that the target object is in a non-target state under the condition that the probability is smaller than or equal to the preset threshold value.
5. The apparatus of claim 4, wherein the apparatus further comprises:
the filtering module is used for carrying out low-pass filtering on the electric signal;
the shaping module is used for carrying out mean value shaping on the electric signal subjected to low-pass filtering to obtain a corresponding rectangular wave;
and the determining module is used for determining that the target object leaves the target position under the condition that the rising edge in the rectangular wave is detected.
6. The apparatus of claim 4, wherein the processing module comprises:
the acquisition unit is used for acquiring multi-frame continuous signals after the target object leaves the target position;
and a conversion unit configured to convert the multi-frame continuous signal into the image data.
7. The electronic equipment is characterized by comprising a processor, a communication interface, a memory and a communication bus, wherein the processor, the communication interface and the memory are communicated with each other through the communication bus;
a memory for storing a computer program;
a processor for implementing the method of any of claims 1-3 when executing a program stored on a memory.
8. A computer readable storage medium, on which a computer program is stored, characterized in that the program, when being executed by a processor, implements the method according to any of claims 1-3.
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| CN202110909754.9A CN113671489B (en) | 2021-08-09 | 2021-08-09 | State reminding method and device, electronic equipment and computer readable storage medium |
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| CN202110909754.9A CN113671489B (en) | 2021-08-09 | 2021-08-09 | State reminding method and device, electronic equipment and computer readable storage medium |
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