CN116110193A - Intelligent nursing method and device, electronic equipment and storage medium - Google Patents
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Abstract
The application provides an intelligent nursing method, an intelligent nursing device, electronic equipment and a storage medium, and relates to the technical field of intelligent Internet of things, wherein the method comprises the following steps: acquiring N first time lengths of a target object in a target state, and acquiring environmental parameters and first initial time related to the first time lengths, wherein the target state is a home departure state or a home state of the target object, the first initial time is a starting time of the first time length, and N is an integer greater than or equal to 1; acquiring a first correction factor corresponding to the environmental parameter and a second correction factor corresponding to the first initial moment, and acquiring a second time length based on the first time length, the first correction factor and the second correction factor; and determining the early warning duration based on the second duration. The technical scheme of the application solves the problem that the risk of missed judgment or misjudgment is caused by unreasonable setting of the fixed threshold in the existing intelligent nursing system.
Description
Technical Field
The application relates to the technical field of intelligent Internet of things, in particular to an intelligent nursing method, an intelligent nursing device, electronic equipment and a storage medium.
Background
With the development of economy, the aging problem is increasingly serious, and the trip safety problem of the empty nest old is also an increasingly focused problem of society. The empty nest old people are extremely easy to have various problems in the traveling or long-time home process due to the lack of child accompaniment. When the old people have the problems of not being resident for a long time and not being returned for a long time, children, guardianship and friends of the old people are difficult to find in the first time, so that the old people are difficult to rescue and care in the first time. Therefore, the monitoring of travel and home time of the old is particularly important. The existing intelligent monitoring system generally prejudges risks existing in the travel or the house of the old through setting a fixed threshold value and informs relatives of the old or community staff to check on the gate. Because the fixed threshold value is set too high or too low, missed judgment or false judgment is easy to occur, and the nursing effect is limited.
Disclosure of Invention
The embodiment of the application provides an intelligent nursing method, an intelligent nursing device, electronic equipment and a medium, which are used for solving the problem that the risk of missed judgment or misjudgment is caused by unreasonable fixed threshold setting in the existing intelligent nursing system.
In order to solve the technical problems, the application is realized as follows:
in a first aspect, embodiments of the present application provide an intelligent care method, the method comprising:
acquiring N first time lengths of a target object in a target state, and acquiring environmental parameters and first initial time related to the first time lengths, wherein the target state is a home departure state or a home state of the target object, the first initial time is a starting time of the first time length, and N is an integer greater than or equal to 1;
acquiring a first correction factor corresponding to the environmental parameter and a second correction factor corresponding to the first initial moment, and acquiring a second time length based on the first time length, the first correction factor and the second correction factor;
and determining an early warning duration based on the second duration, wherein the early warning duration is used for outputting early warning information when the third duration of the target object in the target state is longer than the early warning duration.
Optionally, the obtaining the first correction factor corresponding to the environmental parameter includes:
under the condition that the environment parameters are matched with preset environment parameters, determining that the first correction factor is larger than a first threshold value;
and under the condition that the environment parameters are not matched with the preset environment parameters, determining that the first correction factor is smaller than the first threshold value.
Optionally, the obtaining the second correction factor corresponding to the first initial time includes:
acquiring the second correction factor smaller than a second threshold value under the condition that the first initial time is earlier than a preset time;
acquiring the second correction factor equal to a second threshold value under the condition that the first initial time is consistent with the preset time;
and under the condition that the first initial time is later than the preset time, acquiring the second correction factor which is larger than the second threshold value.
Optionally, after determining the early warning duration based on the second duration, the method further includes:
acquiring a monitoring picture comprising the target object;
acquiring a second initial moment of the target object in the monitoring picture;
and acquiring the third duration based on the second initial time.
Optionally, after the obtaining the third duration based on the second initial time, the method further includes:
outputting early warning information under the condition that the third time length of the target object in the target state is longer than the early warning time length;
verifying the target state of the target object based on the early warning information to determine whether the target object is in a target state;
and under the condition that the target object is not in the target state, acquiring a third correction factor, and correcting the early warning duration based on the third correction factor.
In a second aspect, embodiments of the present application further provide an intelligent care device, the device comprising:
the acquisition module is used for acquiring N first time lengths of a target object in a target state, and acquiring environmental parameters and first initial time related to the first time length, wherein the target state is a state of leaving home or a state of living home of the target object, the first initial time is the initial time of the first time length, and N is an integer greater than or equal to 1;
the correction module is used for acquiring a first correction factor corresponding to the environmental parameter and a second correction factor corresponding to the first initial moment, and acquiring a second time length based on the first time length, the first correction factor and the second correction factor;
the determining module is used for determining an early warning duration based on the second duration, wherein the early warning duration is used for outputting early warning information when the third duration of the target object in the target state is longer than the early warning duration.
Optionally, the correction module is configured to:
under the condition that the environment parameters are matched with preset environment parameters, determining that the first correction factor is larger than a first threshold value;
and under the condition that the environment parameters are not matched with the preset environment parameters, determining that the first correction factor is smaller than the first threshold value.
Optionally, the correction module is configured to: acquiring the second correction factor smaller than a second threshold value under the condition that the first initial time is earlier than a preset time;
acquiring the second correction factor equal to a second threshold value under the condition that the first initial time is consistent with the preset time;
and under the condition that the first initial time is later than the preset time, acquiring the second correction factor which is larger than the second threshold value.
In a third aspect, embodiments of the present application further provide an electronic device, including a processor and a memory, where the memory stores a program or instructions executable on the processor, and the program or instructions implement the steps of the intelligent care method according to the first aspect when executed by the processor.
In a fourth aspect, embodiments of the present application further provide a computer readable storage medium, where a program or instructions are stored, which when executed by a processor, implement the steps of the intelligent care method according to the first aspect.
In the embodiment of the application, the time length of the target object in the target state is determined, and the environmental parameters which are related to the time length and influence the target object in the target state and the initial time of the time length are used for acquiring the corresponding correction factors based on the parameters, so that the early warning time length for early warning the target object in the target state is obtained. The early warning time length takes multiple factors into consideration, and can be applied to different target objects in different target states, so that the accuracy of risk identification is improved, and risk misjudgment and missed judgment are reduced.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings that are needed in the description of the embodiments of the present application will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present application, and that other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
FIG. 1 is one of the flowcharts of a method for intelligent care provided in an embodiment of the present application;
FIG. 2 is a map of a deep convolutional neural network;
FIG. 3 is a second flowchart of a smart care method according to an embodiment of the present disclosure;
fig. 4 is a schematic structural diagram of an intelligent care device according to an embodiment of the present application;
fig. 5 is a schematic structural diagram of an electronic device according to an embodiment of the present application.
Detailed Description
The following description of the embodiments of the present application will be made clearly and fully with reference to the accompanying drawings, in which it is evident that the embodiments described are some, but not all, of the embodiments of the present application. Accordingly, one of ordinary skill in the art will recognize that various changes and modifications of the embodiments described herein can be made without departing from the scope and spirit of the present disclosure. Also, descriptions of well-known functions and constructions are omitted in the following description for clarity and conciseness. All other embodiments, which can be made by one of ordinary skill in the art based on the embodiments herein without making any inventive effort, are intended to be within the scope of the present application.
The embodiment of the application provides a method. Referring to fig. 1, fig. 1 is a flowchart of an intelligent nursing method according to an embodiment of the present application, as shown in fig. 1, including the following steps:
It should be noted that, the target object may be an object to be cared for, such as an old person, a child, a pet, etc., and the target state may be a state in which the object leaves home or is at home, or a state in which the object leaves a certain fixed place and returns to a certain fixed place. The first initial time may be an initial time of a duration. The environmental parameters may be temperature, illuminance, visibility, etc. of the environment in which the target object is located. For example, when the weather temperature of the elderly coming out of the home is too low or overheated, the physical state of the elderly is affected, and it is difficult to get home or go out of the home on time according to the movement level at the proper temperature.
In the above step, N first durations of the target object in the target state are first obtained, that is, durations of a plurality of target objects in the target state in the past are obtained, and the basic data of the target object in the target state can be measured through a plurality of specific duration data. And adjusting the early warning time length based on the first time length so as to acquire the early warning time length of the target object in the target state, and adjusting the early warning time length based on the existing data, thereby reducing the possibility of risk misjudgment or missed judgment.
For example, due to different weather conditions, the time nodes of the old going out of the home may be different, and the risk level of the old in the same leaving time may be different, so the original leaving time of the old cannot be used as the value for measuring the risk, which may easily cause risk misjudgment or missed judgment. If the risk threshold is set too low, the risk of too high misjudgment exists, and too much behavior is judged to be risk, so that the cost of the gate-on investigation of the relatives of the old and the community staff is increased. At the same time, too many prejudgments will also cause trouble to the relatives of the old, and too high risk threshold values will easily judge the truly risky behavior as safe behavior, resulting in missing the opportunity to know and solve the problem at the first time.
It will be appreciated that the first correction factor corresponding to the above-mentioned environmental parameter and the second correction factor corresponding to the first initial time may be introduced as correction weights, so as to perform correction adjustment on the first time length. The first correction factor may be determined to be a specific value in case the weather temperature is high or low when the elderly leaves home, and is not suitable for outdoor activities. Alternatively, the first correction factor may be determined as another specific value when the weather temperature is appropriate and the human body feels comfortable when the old is away from home. The two data sets are different in size, the influence on the early warning duration determined based on the correction factors is different, the influence of the former correction factor on the early warning duration is larger, and the influence of the latter correction factor on the early warning duration is smaller.
Likewise, the specific data setting of the second correction factor corresponding to the first initial time may be determined according to the morning and evening of the first initial time. For example, the first correction factor may be set to a larger value when the first initial time of the elderly's departure from home is too late, and the first correction factor may be set to a smaller value when the first initial time of the elderly's departure from home is early. At this time, the second correction factor having a larger value has a larger influence on the first period, and the second correction factor having a smaller value has a smaller influence on the first period. The first time length can be adjusted and corrected based on the first correction factor and the second correction factor, so that the second time length which can accurately reflect that the target object is in the target state is obtained, the risk misjudgment and missed judgment of the target object in the target state are reduced, and the risk identification accuracy is improved.
In this embodiment of the present application, the early warning duration determined based on the second duration may be an average value of a plurality of second durations, and specifically the early warning duration may be obtained through the following formula:
wherein, the liquid crystal display device comprises a liquid crystal display device,
indicate->
Early warning time length of the target object;
Specifically, the early warning duration of the target object can be determined through the formula, the first duration is corrected according to the environment parameter and the initial time when the target object is in the target state to obtain the second duration, and the early warning duration is obtained based on the processing of the second duration. And finally, calculating a third time length when the target object is actually in the target state, and after the time length of the target object in the target state is longer than the early warning time length, indicating that the risk of the target object is more likely, and timely outputting early warning information is needed so as to be convenient for timely finding out the risk solution problem. Therefore, the obtained early warning time can be used as a risk early warning threshold for judging whether the target object is in the target state, and the possible risk of the target object can be reflected more accurately and sensitively.
Optionally, the obtaining the first correction factor corresponding to the environmental parameter includes:
under the condition that the environment parameters are matched with preset environment parameters, determining that the first correction factor is larger than a first threshold value;
and under the condition that the environment parameters are not matched with the preset environment parameters, determining that the first correction factor is smaller than the first threshold value.
Optionally, the obtaining the second correction factor corresponding to the first initial time includes:
acquiring the second correction factor smaller than a second threshold value under the condition that the first initial time is earlier than a preset time;
acquiring the second correction factor equal to a second threshold value under the condition that the first initial time is consistent with the preset time;
and under the condition that the first initial time is later than the preset time, acquiring the second correction factor which is larger than the second threshold value.
It should be understood that, in the present application, the first correction factor and the second correction factor may be obtained based on the environmental parameter and the first initial time, and the second time period may be obtained based on the first correction factor, the second correction factor and the first time period, specifically, the second time period may be obtained by the following formula:
wherein, the liquid crystal display device comprises a liquid crystal display device,
is a first correction factor;
In one embodiment of the present application, the first correction factors with different values may be determined according to different environmental parameters, and the second correction factors with different values may also be determined according to different first initial moments. When the environmental parameter matches with the preset environmental parameter, it indicates that the environmental parameter in the target state has a smaller influence on the target object at this time, so that the first correction factor may be set to have a smaller value, so as to have a smaller influence on the first time correction.
For example, the illumination intensity varies at different times of the day, with the illumination intensity at night being less for the daytime. And when an old man goes out in the daytime compared with going out at night, the risk that the daytime goes out is lower than the risk that the night goes out, so that the first correction factor of the daytime goes out is approximately 1, the first correction factor corresponding to the night goes out can be set to be a value larger than 1, the influence of different environment parameters on the target object in a target state can be introduced more accurately, and the original early warning threshold value is corrected to obtain early warning duration capable of reflecting the risk of the target object. Likewise, when an old person leaves home too late, which may have more risk than an earlier person, the second correction factor may be set to a value greater than 1 when the second initial time is too late, and may be set to a value approximately 1 when the second initial time is earlier. By the formula, the influence possibly caused by environmental parameters, second initial time and the like on the target state of the target object can be considered, so that the second duration capable of accurately judging the risk is acquired.
Optionally, after determining the early warning duration based on the second duration, the method further includes:
acquiring a monitoring picture comprising the target object;
acquiring a second initial moment of the target object in the monitoring picture;
and acquiring the third duration based on the second initial time.
In a specific embodiment of the present application, after determining the early warning duration, whether the target object has a risk may be determined by using the early warning duration as a risk threshold, first, a time when the target object starts to be in a certain target state may be obtained, and a third duration when the target object is in the target state may be calculated with the time as an initial time. For example, the third time period may be a time period when the old man leaves home on the same day, and when the old man does not enter home within the early warning time period, that is, the third time period when the old man leaves home is longer than the early warning time period, the old man leaves home too long is determined to have higher risk, and early warning information may be output.
It should be noted that, the monitoring image of the target object is obtained, so that the initial time when the target object starts to be in the target state, that is, the second initial time, is obtained based on the monitoring image. The method comprises the steps of obtaining a monitoring picture by adopting face recognition, feature recognition and other modes, specifically, tracking the face in the monitoring picture, searching a face image meeting a certain size and definition, and then recognizing a static image meeting the above conditions and an existing photo of a target object to determine the moment of the target object in monitoring. The monitoring can be arranged at the positions of the entrance and the exit of the residential district of the target object, the entrance and the exit of the corridor of the target object, the entrance and the exit of the house, the street entrance and the exit of the community and the like, so that the time when the target object starts to be in the target state can be conveniently and quickly acquired.
As shown in fig. 2, the face recognition can be specifically realized through a deep convolutional neural network, wherein each layer in the convolutional neural network is composed of a plurality of two-dimensional planes, each plane is composed of a plurality of independent neurons, the neurons of two adjacent layers are connected with each other, and the neurons of the same layer are not connected with each other.
Optionally, after the obtaining the third duration based on the second initial time, the method further includes:
outputting early warning information under the condition that the third time length of the target object in the target state is longer than the early warning time length;
verifying the target state of the target object based on the early warning information to determine whether the target object is in a target state;
and under the condition that the target object is not in the target state, acquiring a third correction factor, and correcting the early warning duration based on the third correction factor.
In still another embodiment of the present application, it may further be determined whether the third duration is greater than the early warning duration after the third duration is acquired. And when the third time exceeds the early warning time, the target object is in the target state for too long, and early warning information can be output. And then, receiving the early warning information by the family members of the target objects or the staff of the communities, and verifying the actual state of the target objects by the family members or the staff of the communities to obtain an actual verification result. If the verification is correct, the early warning duration is maintained until the early warning information is output next time. If the detection is found to belong to the risk misjudgment, the early warning duration is adjusted and corrected by introducing a third correction factor. In this way, the verification can be performed by outputting the actual situation after the early warning information, and the third correction factor is determined based on the verification result, and the value setting of the third correction factor can specifically refer to the value setting of the first correction factor. Therefore, the early warning time length can be corrected and adjusted through the third correction factor, and the accuracy of risk identification of the target object in the target state is improved.
As shown in fig. 3, fig. 3 is a second flowchart of an intelligent nursing method according to an embodiment of the present application, where specific steps of the intelligent nursing method are as follows:
step 208, a third correction factor is obtained, and the early warning duration is corrected based on the third correction factor.
The steps are the nursing process of the target object, and the risk early warning threshold value, namely the early warning duration of the target object in the target state under different scenes can be obtained through adjusting and correcting the duration of the target object in the target state. Meanwhile, the early warning duration is continuously adjusted based on the verification result after early warning, so that the accuracy of early warning identification on the risk of the target object in the target state is improved, and the possibility of risk pre-judgment or missed judgment is reduced.
Referring to fig. 4, an embodiment of the present application further provides a smart care device, where the smart care device 300 includes:
the acquiring module 301 is configured to acquire N first durations of a target object in a target state, and acquire an environmental parameter and a first initial time related to the first duration, where the target state is an away-from-home state or a home state of the target object, and the first initial time is a starting time of the first duration, and N is an integer greater than or equal to 1;
the correction module 302 is configured to obtain a first correction factor corresponding to the environmental parameter and a second correction factor corresponding to the first initial time, and obtain a second time length based on the first time length, the first correction factor, and the second correction factor;
the determining module 303 determines an early warning duration based on the second duration, where the early warning duration is used to output early warning information when the third duration that the target object is in the target state is longer than the early warning duration.
Optionally, the correction module 302 is configured to:
under the condition that the environment parameters are matched with preset environment parameters, determining that the first correction factor is larger than a first threshold value;
and under the condition that the environment parameters are not matched with the preset environment parameters, determining that the first correction factor is smaller than the first threshold value.
Optionally, the correction module 302 is configured to: acquiring the second correction factor smaller than a second threshold value under the condition that the first initial time is earlier than a preset time;
acquiring the second correction factor equal to a second threshold value under the condition that the first initial time is consistent with the preset time;
and under the condition that the first initial time is later than the preset time, acquiring the second correction factor which is larger than the second threshold value.
Optionally, the determining module 303 is further configured to:
acquiring a monitoring picture comprising the target object;
acquiring a second initial moment of the target object in the monitoring picture;
and acquiring the third duration based on the second initial time.
It should be understood that, when the intelligent care device 300 in the embodiment of the present application is operated, each process in the embodiment of the intelligent care method can be implemented, and the beneficial effects in the embodiment can be achieved, which is not repeated herein.
Referring to fig. 5, the embodiment of the present application further provides an electronic device 400, including a processor 401, a memory 402, and a computer program stored in the memory 402 and capable of running on the processor 401, where the computer program when executed by the processor 401 implements each process of the above embodiment of the intelligent nursing method, and the same technical effects can be achieved, and for avoiding repetition, a detailed description is omitted herein.
The embodiment of the application further provides a computer readable storage medium, on which a computer program is stored, which when executed by a processor, implements each process of the above-mentioned intelligent nursing method embodiment, and can achieve the same technical effects, so that repetition is avoided, and no further description is provided herein. Wherein the computer readable storage medium is selected from Read-Only Memory (ROM), random access Memory (Random Access Memory, RAM), magnetic disk or optical disk.
It should be noted that, in this document, 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.
It should be appreciated that various forms of the flows shown above may be used to reorder, add, or delete steps. For example, the steps described in this application may be performed in parallel or sequentially or in a different order, and the specific embodiments described above are merely illustrative, and not restrictive, and many versions may be made by those having ordinary skill in the art, without departing from the spirit and scope of the present application, which is protected by the claims, as long as the desired results of the disclosed solution are achieved.
Claims (10)
1. An intelligent care method, comprising:
acquiring N first time lengths of a target object in a target state, and acquiring environmental parameters and first initial time related to the first time lengths, wherein the target state is a home departure state or a home state of the target object, the first initial time is a starting time of the first time length, and N is an integer greater than or equal to 1;
acquiring a first correction factor corresponding to the environmental parameter and a second correction factor corresponding to the first initial moment, and acquiring a second time length based on the first time length, the first correction factor and the second correction factor;
and determining an early warning duration based on the second duration, wherein the early warning duration is used for outputting early warning information when the third duration of the target object in the target state is longer than the early warning duration.
2. The method of claim 1, wherein the obtaining the first correction factor corresponding to the environmental parameter comprises:
under the condition that the environment parameters are matched with preset environment parameters, determining that the first correction factor is larger than a first threshold value;
and under the condition that the environment parameters are not matched with the preset environment parameters, determining that the first correction factor is smaller than the first threshold value.
3. The method of claim 1, wherein the obtaining the second correction factor corresponding to the first initial time comprises:
acquiring the second correction factor smaller than a second threshold value under the condition that the first initial time is earlier than a preset time;
acquiring the second correction factor equal to a second threshold value under the condition that the first initial time is consistent with the preset time;
and under the condition that the first initial time is later than the preset time, acquiring the second correction factor which is larger than the second threshold value.
4. The method of claim 1, wherein after determining the pre-warning duration based on the second duration, further comprising:
acquiring a monitoring picture comprising the target object;
acquiring a second initial moment of the target object in the monitoring picture;
and acquiring the third duration based on the second initial time.
5. The method of claim 4, wherein the acquiring the third duration based on the second initial time further comprises:
outputting early warning information under the condition that the third time length of the target object in the target state is longer than the early warning time length;
verifying the target state of the target object based on the early warning information to determine whether the target object is in a target state;
and under the condition that the target object is not in the target state, acquiring a third correction factor, and correcting the early warning duration based on the third correction factor.
6. An intelligent care device, comprising:
the acquisition module is used for acquiring N first time lengths of a target object in a target state, and acquiring environmental parameters and first initial time related to the first time length, wherein the target state is a state of leaving home or a state of living home of the target object, the first initial time is the initial time of the first time length, and N is an integer greater than or equal to 1;
the correction module is used for acquiring a first correction factor corresponding to the environmental parameter and a second correction factor corresponding to the first initial moment, and acquiring a second time length based on the first time length, the first correction factor and the second correction factor;
the determining module is used for determining an early warning duration based on the second duration, wherein the early warning duration is used for outputting early warning information when the third duration of the target object in the target state is longer than the early warning duration.
7. The apparatus of claim 6, wherein the correction module is to:
under the condition that the environment parameters are matched with preset environment parameters, determining that the first correction factor is larger than a first threshold value;
and under the condition that the environment parameters are not matched with the preset environment parameters, determining that the first correction factor is smaller than the first threshold value.
8. The apparatus of claim 6, wherein the correction module is to: acquiring the second correction factor smaller than a second threshold value under the condition that the first initial time is earlier than a preset time;
acquiring the second correction factor equal to a second threshold value under the condition that the first initial time is consistent with the preset time;
and under the condition that the first initial time is later than the preset time, acquiring the second correction factor which is larger than the second threshold value.
9. An electronic device comprising a processor and a memory storing a program or instructions executable on the processor, which when executed by the processor, implement the intelligent care method steps of any of claims 1-5.
10. A computer readable storage medium, characterized in that it has stored thereon a program or instructions which, when executed by a processor, implement the intelligent care method steps of any of claims 1-5.
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