CN113671489A - State reminding method and device, electronic equipment and computer readable storage medium - Google Patents
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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; under the condition that the electric signal is determined to represent that the target object leaves the target position, acquiring 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; and sending a state reminding message under the condition that the target object is in the target state. Through this application, solved among the prior art and monitored the old person's state through camera device, can lead to the state to remind untimely and unsafe problem.
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
With the development of society, the social rhythm is gradually accelerated, the aging of population is continuously intensified, and the pressure of young people is increased. Young people are more busy in work, the absentee is taken care of the old person, therefore more and more family select to send into the old person and send into the asylum for the aged, at present, can take care of the old person through the nurse worker in the asylum for the aged, but also can not take care of the old person in real time, then can monitor the old person through installation camera device, but present control also needs to have special personnel to monitor before the display, under the more condition of the old person, can lead to can't in time looking over the old person's that needs the help situation in the display, lead to can't in time to providing help to the old person who needs the help.
In view of the above technical problems, no effective solution exists at present.
Disclosure of Invention
An object of the embodiments of the present application is to provide a state reminding method and apparatus, an electronic device, and a computer-readable storage medium, so as to solve the problem in the prior art that the state reminding is not timely and inaccurate when the state of the elderly is monitored by a camera device. The specific technical scheme is as follows:
in a first aspect, a status 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; under the condition that the electric signal is determined to represent that the target object leaves the target position, acquiring 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; and sending a state reminding message under the condition that the target object is in the target state.
In a second aspect, a status reminding device is provided, which includes: the acquisition module is used for 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; the processing module is used for acquiring image data after the target object leaves the target position under the condition that the electric signal represents that 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; and the sending module is used for sending the 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 stored therein instructions, which, when run on a computer, cause the computer to perform the method of the first aspect.
In a fourth aspect, there is also provided a computer program product comprising instructions which, when run on a computer, cause the computer to perform the method of the first aspect described above.
By the method and the device, 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 or not is judged according to the electric signal, whether the target object is in the target state or not is further determined, and if the target object is in the target state, the state reminding message is sent. If the target state indicates that the target object is in a dangerous state or in a help seeking state, a state reminding message is sent, related personnel of the target object can be timely and accurately reminded, and the safety guarantee of the target object is improved, so that the problems that state reminding is not timely and inaccurate due to the fact that the state of old people is monitored through a camera in the prior art are 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 CNN-based tumble determination according to an embodiment of the present application;
FIG. 3 is a schematic structural diagram of a status notification 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 application.
Detailed Description
The technical solutions in the embodiments of the present application will be described below with reference to the drawings in the embodiments of the present application.
An embodiment of the present application provides a state reminding method, as shown in fig. 1, the method includes the steps of:
102, 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;
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 film sensor; other sensors capable of detecting pressure may also be used as the target sensor, such as a piezoelectric pressure sensor, a piezoresistive pressure sensor, and the like.
The target object in the embodiment of the present application may be a user that needs to be detected, such as a special crowd with inconvenient actions, a user with a relatively large age, or a user with a relatively small age.
The target position may be a sleeping position on a bed or a position on a sofa, that is, the target sensor may be installed in a position where a user sleeps or lies down to detect a pressure of the user on the position, and further determine whether the user leaves the position, if the target object generates a pressure in the target position, the pressure is converted into an electrical signal to determine that the user is in the target position, and if the target object does not generate an electrical signal, the target object leaves the position.
104, under the condition that the electric signal represents that the target object leaves the target position, acquiring image data of the target object after leaving the target position, and determining whether the target object is in a target state or not based on the image data;
the target state in the embodiment of the present application refers to a dangerous state in which the target object is dangerous, a state in which the target object needs to ask for help, or another state in which people need to be reminded. The dangerous state of the target object is walking relatively, a curve set and the like, the target object is in a state of asking for help, such as a help-asking action lasting for a long time in one place, and a potentially dangerous state exists, such as the target object is in a life state with fuzzy consciousness, and the target object leaves the target position and tries to go out when opening a door, namely the state of opening the door is the target state.
And 106, sending a state reminding message under the condition that the target object is in the target state.
It should be noted that the reminding message may be a reminding message sent by indoor broadcasting, or a reminding message sent by a mobile phone of a person associated with the target object, or other means. 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, so that 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 indicates that the target object is in a dangerous state or in a help seeking state, a state reminding message is sent, related personnel of the target object can be timely and accurately reminded, and the safety guarantee of the target object is improved, so that the problems that state reminding is not timely and inaccurate due to the fact that the state of old people is monitored through a camera in the prior art are solved.
It should be noted that, the execution main body 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 to the target sensor and may also be integrated with a neural network model for discriminating the state of the target.
In this embodiment, regarding the manner of determining the electrical signal representing the target object leaving the target location in step 102, the method may further include:
step 11, low-pass filtering the electric signal;
taking the target object on the bed as an example, the piezoelectric film sensor is placed under a user mattress or a pillow, whether the user gets up is judged through the change of electric signals before and after getting up, specifically, an obvious falling edge and an obvious rising edge exist at the initial moment and represent the user getting up and getting up, and an obvious rising edge exists after a period of sleep and represents the user moving up.
Step 12, performing mean shaping on the electric signals subjected to low-pass filtering to obtain corresponding rectangular waves;
the mean filtering is to filter some high-frequency signals, mean shaping is to modify the signal waveform into a rectangular wave, the rising edge is the time when the user gets into the bed, and the detection of the rising edge is to detect the user getting out of the bed.
And step 13, determining that the target object leaves the target position when the rising edge in the rectangular wave is detected.
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 determined conveniently and quickly.
In another optional implementation manner of this embodiment of this application, for the manner of acquiring the image data after the target object leaves the target location, which is referred to in the above step 104, further may include:
step 21, collecting multi-frame continuous signals after the target object leaves the target position;
and step 22, converting the multi-frame continuous signals into image data.
In the embodiment of the application, the multi-frame continuous signals of the target object leaving the target position can be collected through the millimeter wave radar, and then the image data of the target object leaving the target position is determined to monitor the state after getting up in real time, so that the monitoring is more timely and accurate compared with that of a camera device.
In another optional implementation manner of the embodiment of the present application, regarding the manner of determining whether the target object is in the target state based on the image data in 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.
The target Neural network model may be a Convolutional Neural Network (CNN), specifically, as shown in fig. 2, the image is sent to the CNN for feature extraction and discrimination, and if the probability of the fall is judged to be greater than a certain threshold, the fall is judged. 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 of image extracted by CNN, and y is the discrimination probability of each frame of image. Equation (2) is a case where the output discrimination probability is equal to or greater than a threshold value, it is determined that the vehicle is in a fallen state. For example, assume that the threshold is 0.8. Firstly, a CNN (CNN) discrimination model is trained, 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 at a certain moment is input, the probability y of falling is output through a formula (1), and in a formula (2), if the falling probability y is more than or equal to a threshold value of 0.8, the user is judged to fall, otherwise, the user does not fall.
Wherein, the method for outputting the comparison result between the probability and the preset threshold value in the step 32 further includes:
step 41, outputting a comparison result for representing that the target object is in the target state under the condition that the probability is greater than a preset threshold value;
and 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 the training result of the neural network model. Therefore, the state of the user target object is automatically judged based on the neural network model, manual judgment before the camera device is not needed, and the efficiency of monitoring the target state is improved.
The present application will now be described by way of example with reference to the following specific embodiments of examples thereof. The specific implementation mode provides a state monitoring method, the piezoelectric film module is adopted to monitor the sleep of a person in real time, the millimeter wave radar is used for monitoring the behavior state after getting up, and the CNN algorithm in deep learning is utilized to judge whether falling occurs. The method comprises the following steps:
step 201, monitoring the in-bed state of a target object in real time through a piezoelectric film sensor placed below a mattress or a pillow.
Wherein, particularly, when the target object is put into bed, the piezoelectric film module generates the electric signal change due to the pressure change suffered by the mattress or the pillow. Low-pass filtering, mean value shaping and rising edge detection counting are carried out on the generated electric signals, and whether the user gets up is judged according to the change of the electric signals. And when the user is judged to get up, starting the millimeter wave radar to monitor the user behavior.
Step 202, if it is monitored that the target object gets up, the millimeter wave radar is turned on to perform real-time monitoring, the millimeter wave radar continuously sends signals to perform monitoring, collected echo signals are processed by the signal processor and converted into point cloud data, and the point cloud data comprises a distance, an azimuth angle and a Doppler speed. Further, carrying out cluster analysis on the point cloud data to obtain a plurality of continuous images corresponding to the plurality of continuous echo signals.
Step 203, tracking and positioning of the user is realized through a Kalman algorithm;
and 204, adopting a buzzing alarm to remind surrounding people and remotely inform working personnel to take measures for rescuing the target object under the condition that the CNN judges that the falling behavior occurs.
The CNN performs feature extraction on input image data, where the extracted features include human postures, heights, and the like, and then determines by using the extracted features, and through calculation of a softmax function, the final output is the probability of whether the user falls, for example, a piece of picture data, and after the CNN performs feature extraction, the output is determined as the probability of determining that the user falls being 90%.
Through this embodiment, adopt piezoelectric film module to carry out real-time monitoring to the gesture when sleeping, the millimeter wave radar is used for monitoring the action after getting up, utilizes the deep learning CNN technique to judge whether take place to tumble, 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, the device includes:
the acquiring module 32 is 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;
the processing module 34 is configured to, in a case where it is determined that the electrical signal represents that the target object leaves the target position, acquire image data of the target object after leaving 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 the state reminding message when the target object is in the target state.
By the device, 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 or not is judged according to the electric signal, whether the target object is in the target state or not is further determined, and if the target object is in the target state, the state reminding message is sent. If the target state indicates that the target object is in a dangerous state or in a help seeking state, a state reminding message is sent, related personnel of the target object can be timely and accurately reminded, and the safety guarantee of the target object is improved, so that the problems that state reminding is not timely and inaccurate due to the fact that the state of old people is monitored through a camera in the prior art are solved.
Optionally, the apparatus according to the embodiment of the present application may further include: the filtering module is used for carrying out low-pass filtering on the electric signal; the shaping module is used for performing mean shaping on the electric signals subjected to the low-pass filtering to obtain corresponding rectangular waves; 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 further includes: 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 plurality of frames of continuous signals into image data.
Optionally, the processing module 34 of the embodiment of the present application further includes: an input unit for inputting image data into the target neural network model; and 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, wherein the result comparison result is used for representing whether the target object is in the target state.
Optionally, the processing unit in this embodiment of the present application includes: the first output subunit is used for outputting a comparison result for representing that the target object is in a target state under the condition that the probability is greater than a preset threshold value; and the second output subunit is used for 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 the preset threshold value.
The embodiment of the present application further provides an electronic device, as shown in fig. 4, which includes a processor 401, a communication interface 402, a memory 403, and a communication bus 404, where the processor 401, the communication interface 402, and the memory 403 complete mutual communication 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 the functions of the method steps are similar to those of the method steps in fig. 1, and are not described again here.
The communication bus mentioned in the above terminal may be a Peripheral Component Interconnect (PCI) bus, an Extended Industry Standard Architecture (EISA) bus, or the like. The communication bus may be divided into an address bus, a data bus, a control bus, etc. For ease of illustration, only one thick line is shown in FIG. 4, but this does not indicate only one bus or one type of bus.
The communication interface is used for communication between the terminal and other equipment.
The Memory may include a Random Access Memory (RAM) or a 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 processor.
The Processor may be a general-purpose Processor, and includes a Central Processing Unit (CPU), a Network Processor (NP), and the like; the Integrated Circuit may also be a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), a Field Programmable Gate Array (FPGA) or other Programmable logic device, a discrete Gate or transistor logic device, or a discrete hardware component.
In another embodiment provided by the present application, a computer-readable storage medium is further provided, in which instructions are stored, and when the instructions are executed on a computer, the computer is caused to execute the state reminding method in any one of the above embodiments.
In yet another embodiment provided by the present application, there is also provided a computer program product containing instructions which, when run on a computer, cause the computer to perform the state reminding method of any of the above embodiments.
In the above embodiments, the implementation may be wholly or partially realized 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, cause the processes or functions described in accordance with the embodiments of the application to occur, in whole or in part. The computer may be a general purpose computer, a special purpose computer, a network of computers, or other programmable device. The computer instructions may be stored in a computer readable storage medium or transmitted from one computer readable storage medium to another, for example, from one website site, computer, server, or data center to another website site, computer, server, or data center via wired (e.g., coaxial cable, fiber optic, Digital Subscriber Line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.). The computer-readable storage medium can be any available medium that can be accessed by a computer or a data storage device, such as a server, a data center, etc., that incorporates one or more of the 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)), among others.
It is noted that, herein, relational terms such as first and second, and the like may be 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. Also, 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 an … …" does not exclude the presence of other identical elements in a process, method, article, or apparatus that comprises the element.
All the embodiments in the present specification are described in a related manner, and the same and similar parts among the embodiments may be referred to each other, and each embodiment focuses on the differences from the other embodiments. In particular, for the system embodiment, since it is substantially similar to the method embodiment, the description is simple, and for the relevant points, reference may be made to the partial description of the method embodiment.
The above description is only for the preferred embodiment of the present application, and is not intended to limit the scope of the present application. Any modification, equivalent replacement, improvement and the like made within the spirit and principle of the present application are included in the protection scope of the present application.
Claims (10)
1. A state reminding method is characterized by comprising 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;
under the condition that the electric signal is determined to represent that the target object leaves the target position, acquiring 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;
and sending a state reminding message under the condition that the target object is in the target state.
2. The method of claim 1, wherein said determining that the electrical signal characterizes the target object as leaving the target location comprises:
low pass filtering the electrical signal;
performing mean shaping on the electric signals subjected to low-pass filtering to obtain corresponding rectangular waves;
determining that the target object leaves the target position if a rising edge in the rectangular wave is detected.
3. The method of claim 1, wherein said acquiring image data after said target object leaves said target location comprises:
collecting multi-frame continuous signals after the target object leaves the target position;
converting the plurality of frames of continuous signals into the image data.
4. The method of claim 1, wherein the determining whether the target object is in a target state based on the image data comprises:
inputting the image data into a target neural network model;
and determining the probability of the target object being 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.
5. The method of claim 4, wherein outputting the comparison result of the probability with a preset threshold comprises:
under the condition that the probability is larger than the preset threshold value, outputting a comparison result for representing that the target object is in the target state;
and 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 the preset threshold.
6. A status alert device, comprising:
the acquisition module is used for 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;
the processing module is used for acquiring image data after the target object leaves the target position under the condition that the electric signal represents that 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;
and the sending module is used for sending the state reminding message under the condition that the target object is in the target state.
7. The apparatus of claim 6, further comprising:
the filtering module is used for carrying out low-pass filtering on the electric signal;
the shaping module is used for performing mean shaping on the electric signals subjected to the low-pass filtering to obtain corresponding rectangular waves;
a determination module for determining that the target object leaves the target position when a rising edge in the rectangular wave is detected.
8. The apparatus of claim 6, wherein the processing module comprises:
the acquisition unit is used for acquiring multi-frame continuous signals after the target object leaves the target position;
a conversion unit configured to convert the plurality of frames of continuous signals into the image data.
9. An electronic device is characterized by comprising a processor, a communication interface, a memory and a communication bus, wherein the processor and the communication interface are used for realizing mutual communication by the memory through the communication bus;
a memory for storing a computer program;
a processor for implementing the method steps of any one of claims 1 to 5 when executing a program stored in the memory.
10. A computer-readable storage medium, on which a computer program is stored which, when being executed by a processor, carries out the method steps of any one of claims 1 to 5.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110909754.9A CN113671489B (en) | 2021-08-09 | 2021-08-09 | State reminding method and device, electronic equipment and computer readable storage medium |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
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