CN112767202A - Remote monitoring platform and monitoring method - Google Patents
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Abstract
The invention discloses a remote monitoring platform and a monitoring method, wherein the system comprises: the intelligent wearable equipment comprises a central processing unit, intelligent wearable equipment, a sound acquisition module and a database module, wherein the intelligent wearable equipment, the sound acquisition module and the database module are respectively connected with the central processing unit; the database module is used for storing time information and content information related to the current learning course of the user; the intelligent wearable device and the sound acquisition module are respectively used for acquiring physiological parameters and loudness values of sound of a user and respectively sending the physiological parameters and the loudness values to the central processing unit; the central processing unit is used for judging that the user is in an abnormal learning state according to the fact that the physiological parameter exceeds a first preset threshold value, or judging that the user is in an abnormal learning state according to the fact that the loudness value exceeds a second preset threshold value. The remote monitoring platform provided by the invention can scientifically and effectively judge whether the students are in an effective learning state, reduces the detection cost and simultaneously improves the accuracy of the detection result.
Description
Technical Field
The invention relates to the technical field of network monitoring, in particular to a remote monitoring platform and a monitoring method.
Background
With the gradual maturity of network technology, the way of network teaching is also becoming more and more popular. Especially during epidemic situations, networked educational management has grown exponentially. The network teaching method has the advantages of simplicity, convenience, no need of offline arrangement and no need of gathering the users to the same site for learning; the user can participate in learning only through intelligent electronic equipment, and the mode is flexible and is not time-dependent and place-dependent. But the shortcoming is also obvious, because long-range teaching, to the quality of teaching difficult control, the phenomenon that the student is not concentrated appears in class very easily, some students can directly adopt the mode of hanging up even, and the quality of teaching will be influenced between these behaviors.
Aiming at the defects of network teaching, the prior art provides a monitoring system aiming at the learning state, and the system mainly judges whether the learning state is consistent with the normal state of attending class by monitoring the face of a student, positioning eyes and analyzing facial expressions. However, this method requires the use of face detection and positioning technology, which is costly and difficult to implement, and meanwhile, the detection result obtained through expression analysis may affect the accuracy of the detection result due to the large difference between different learners.
Disclosure of Invention
In order to solve the problems in the prior art, the invention provides a remote monitoring platform and a monitoring method, wherein the platform can scientifically and effectively judge whether a student is in a learning state or not by collecting physiological sign data of the user and sound data in the learning state, so that the detection cost is reduced, and meanwhile, the accuracy of a detection result is improved.
In order to overcome the above-mentioned drawbacks in the prior art, an embodiment of the present invention provides a remote monitoring platform, including:
the intelligent wearable equipment comprises a central processing unit, intelligent wearable equipment, a sound acquisition module and a database module, wherein the intelligent wearable equipment, the sound acquisition module and the database module are respectively connected with the central processing unit; wherein the content of the first and second substances,
the database module is used for storing time information and content information related to the current learning course of the user;
the intelligent wearable device and the sound acquisition module are respectively used for acquiring physiological parameters and loudness values of sound of a user and respectively sending the physiological parameters and the loudness values to the central processing unit;
the central processing unit is used for judging that the user is in an abnormal learning state according to the fact that the physiological parameter exceeds a first preset threshold value, or judging that the user is in an abnormal learning state according to the fact that the loudness value exceeds a second preset threshold value.
Preferably, the remote monitoring platform further comprises: and the notification module is used for sending prompt information to the mobile terminal when the central processing unit detects that the user is in the abnormal learning state.
Preferably, the remote monitoring platform further comprises: and the video monitoring module is used for triggering a starting instruction through the notification module when the central processing unit detects that the user is in the abnormal learning state, shooting the current learning state of the user, and sending the shot video to the mobile terminal.
Preferably, the remote monitoring platform further comprises: and the electronic fence module is used for locking a safe activity area for the user to learn, and sending prompt information to the mobile terminal when the central processing unit detects that the user is in an abnormal learning state.
Preferably, the electronic fence module collects the position information of the user by using an infrared sensor, wherein the infrared sensor is arranged at the boundary of the safe activity area.
Preferably, the remote monitoring platform further comprises: and the voice reminding module is used for reminding the user through voice when the user is in the learning abnormal state so as to adjust the current learning state.
Preferably, the intelligent wearable device comprises a physiological parameter detection module, a motion parameter detection module and an environmental parameter detection module;
the physiological parameter detection module is used for collecting physiological parameters of a user, including heart rate, blood pressure and body temperature;
the motion parameter detection module is used for acquiring motion parameters of a user, and the motion parameters comprise the acceleration of the upper limb of the user in each direction and the activity frequency of the upper limb;
the environment parameter detection module is used for collecting indoor environment parameters including temperature, humidity and brightness of a user.
Preferably, the intelligent wearable device further comprises an electrocardiogram acquisition module, which is used for acquiring an electrocardiogram signal of the user and sending the electrocardiogram signal to the central processing unit, and the central processing unit analyzes the electrocardiogram signal according to an electrocardiogram analysis method to determine whether the user is in an abnormal learning state, wherein the electrocardiogram analysis method comprises HRV time domain analysis and QRS wave algorithm.
An embodiment of the present invention further provides a remote monitoring method, including:
acquiring physiological parameters and loudness values of sound of a user;
when the physiological parameter exceeds a first preset threshold value, judging that the user is in an abnormal learning state; or, when the loudness value exceeds a second preset threshold value, determining that the user is in an abnormal learning state.
Preferably, the remote monitoring method further includes:
the method comprises the steps of locking a safe activity area learned by a user, arranging a plurality of infrared sensors on the boundary of the safe activity area, and sending prompt information to the mobile terminal when the user exceeds the boundary.
Compared with the prior art, the embodiment of the invention has the beneficial effects that:
(1) by collecting physiological sign data of a user and sound data in a learning state, whether the student is in the learning state can be judged scientifically and effectively, the detection cost is reduced, and meanwhile, the accuracy of a detection result is improved;
(2) by arranging the notification module, the learning state can be timely fed back to a guardian of the user;
(3) by locking the learning safety region, whether the user is in the learning region can be judged in time;
(4) through electrocardiogram data and analysis thereof, the learning state of the user is more accurately analyzed;
(5) the video shooting function is triggered when the user is in the abnormal learning state, the abnormal state is shot, and the shot abnormal state is fed back to the guardian of the user in time.
Drawings
Fig. 1 is a schematic structural diagram of a remote monitoring platform according to an embodiment of the present invention;
FIG. 2 is a schematic structural diagram of a remote monitoring platform according to another embodiment of the present invention;
FIG. 3 is a schematic structural diagram of a remote monitoring platform according to another embodiment of the present invention;
fig. 4 is a schematic structural diagram of a remote monitoring platform with an electronic fence function according to an embodiment of the present invention;
fig. 5 is a schematic structural diagram of a remote monitoring platform with a voice reminding function according to an embodiment of the present invention;
fig. 6 is a schematic structural diagram of an intelligent wearable device according to an embodiment of the present invention;
fig. 7 is a schematic structural diagram of an intelligent wearable device according to another embodiment of the present invention;
fig. 8 is a schematic flow chart of a remote monitoring method according to an embodiment of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
It should be understood that the step numbers used herein are for convenience of description only and are not intended as limitations on the order in which the steps are performed.
It is to be understood that the terminology used in the description of the invention herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. As used in the specification of the present invention and the appended claims, the singular forms "a," "an," and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise.
It should be understood that the mobile terminal in the embodiment of the present invention includes a Smart Phone (e.g., an Android Phone, an iOS Phone, etc.), Smart glasses, a Smart watch, a Smart bracelet, a tablet computer, a notebook computer, a personal digital assistant, etc. that are capable of performing wireless communication.
The terms "comprises" and "comprising" indicate the presence of the described features, integers, steps, operations, elements, and/or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and/or groups thereof.
The term "and/or" refers to and includes any and all possible combinations of one or more of the associated listed items.
Referring to fig. 1, an embodiment of the present invention provides a remote monitoring platform, including:
the system comprises a central processing unit 1, intelligent wearable equipment 2, a sound acquisition module 3 and a database module 4, wherein the intelligent wearable equipment, the sound acquisition module 3 and the database module 4 are respectively connected with the central processing unit 1; wherein the content of the first and second substances,
the database module 4 is used for storing time information and content information related to the current learning course of the user;
the intelligent wearable device 2 and the sound collection module 3 are respectively used for collecting physiological parameters and loudness values of sounds of a user and respectively sending the physiological parameters and the loudness values to the central processing unit 1;
the central processing unit 1 is used for judging that the user is in an abnormal learning state according to the fact that the physiological parameter exceeds a first preset threshold value, or judging that the user is in an abnormal learning state according to the fact that the loudness value exceeds a second preset threshold value.
It should be noted that network teaching is very popular in our lives. The method has the advantages that the method is simple and convenient, off-line arrangement is not needed, and users do not need to gather to the same site for learning; the user can participate in learning only through intelligent electronic equipment, and the mode is flexible and is not time-dependent and place-dependent. But the shortcoming is also obvious, because long-range teaching, to the quality of teaching difficult control, the phenomenon that the student is not concentrated appears in class very easily, some students can directly adopt the mode of hanging up even, and the quality of teaching will be influenced between these behaviors. Aiming at the defects of network teaching, the prior art method is to judge whether to accord with the normal state of listening to lessons by monitoring the faces of students, positioning eyes and analyzing facial expressions. However, this method is costly, has a great technical difficulty, and cannot ensure the accuracy of the detection result, so the purpose of this embodiment is to provide a scientific and effective monitoring system with low cost, easy implementation and good effect.
Specifically, in this embodiment, the central processing unit 1 is configured to perform data operation, and detect and determine the learning state of the student, for example, determine whether the sound collected by the sound collection module 3 is greater than a first preset threshold, and is greater than the first preset threshold, and is considered as a learning abnormal state, or determine whether the physiological parameter information of the intelligent wearable device 2 is in a normal range value, and whether the motion information is in a second preset threshold, and if the physiological parameter information exceeds the second preset threshold, it is considered as a learning abnormal state.
Further, the database module 4 is connected with the central processing unit 1, and is used for storing the current learning time information and the online learning course information of the students and the like as the data basis of the processor during operation.
Furthermore, the intelligent wearable device 2 is connected with the central processing unit 1 and is used for collecting physiological parameters, motion information, learning environment and other information of students; wherein intelligent wearing equipment 2 can be intelligent bracelet, intelligent wrist-watch, intelligent eyes etc. can select according to actual conditions, does not do the restriction here. Similarly, the sound collection module 3 is connected with the central processing unit 1 and is used for acquiring real-time sound information of students; in this embodiment, the loudness value of the sound is collected and then compared with a first preset threshold, where it should be noted that the loudness is determined by the amplitude of the sound at the receiving position, and for the same sound source, the farther the amplitude propagates, the smaller the loudness; when the propagation distance is constant, the larger the amplitude of the sound source is, the larger the loudness is. The magnitude of the loudness values can be resolved by amplitude.
According to the embodiment of the invention, through collecting the physiological sign data of the user and the sound data in the learning state, whether the student is in the learning state can be scientifically and effectively judged, the detection cost is reduced, and meanwhile, the accuracy of the detection result is improved.
Referring to fig. 2, in an exemplary embodiment, the remote monitoring platform further includes: and the notification module 5 is used for sending prompt information to the mobile terminal when the central processing unit 1 detects that the user is in the abnormal learning state. Wherein mobile terminal's user is student's guardian, for example the head of a family, and the head of a family can be at the long-range student on-line study condition of looking over the student of mobile terminal APP, conveniently carries out effectual study supervision to the student.
Referring to fig. 3, in an exemplary embodiment, the remote monitoring platform further includes: and the video monitoring module 6 is used for triggering a starting instruction through the notification module 5 when the central processing unit 1 detects that the user is in the abnormal learning state, shooting the current learning state of the user, and sending the shot video to the mobile terminal.
It should be noted that video monitoring module 6 is out of work under the general condition, in case central processing unit 1 detects that the student is in unusual study state, can trigger video monitoring module 6 through notifying module 5, pops out on-the-spot video monitoring immediately at APP backstage end, makes things convenient for guardian to know the on-the-spot condition very first time, can not disturb student's study like this, guarantees simultaneously that guardian knows the condition.
Referring to fig. 4, in an exemplary embodiment, the remote monitoring platform further includes: and the electronic fence module 7 is used for locking a safe activity area for the user to learn, and sending prompt information to the mobile terminal when the central processing unit 1 detects that the user is in an abnormal learning state. The electronic fence module 7 collects the position information of the user by adopting an infrared sensor, wherein the infrared sensor is arranged on the boundary of the safe activity area.
In this embodiment, the electronic fence module 7 may be an infrared position detection sensor disposed around the seat (the student can be detected by passing through the infrared position sensor) for detecting whether the student is still in the seat, and if not in the seat, the student may be notified of the parent APP end through the notification module 5, and the parent may view through the video monitoring module 6. The infrared sensor is a sensor that senses infrared rays emitted from a target and performs measurement using physical properties of the infrared rays. And can be classified into photon detectors and thermal detectors according to the detection mechanism.
Referring to fig. 5, in an exemplary embodiment, the remote monitoring platform further includes: and the voice reminding module 8 is used for reminding the user through voice when the user is in the learning abnormal state so as to adjust the current learning state.
It can be understood that the voice reminding module 8 is used for voice prompt, and the voice reminding module 8 can remind the student through the voice reminding module 8 when the student is not in the learning state. Of course, the guardian can set up the master switch of reminding at student's removal APP end, can close reminding, avoids influencing student's study. The voice reminding module 8 can also record the voice of the parent APP terminal, and then can play the voice reminding module 8 in real time to talk back and remind students.
Referring to fig. 6, in an exemplary embodiment, the smart wearable device 2 includes a physiological parameter detection module, a motion parameter detection module, and an environmental parameter detection module;
the physiological parameter detection module is used for detecting physiological parameters of students and can detect the heart rate, blood pressure and body temperature conditions of the students;
and the motion parameter detection module is used for detecting the motion parameters of the students. Acceleration like the each direction of arm to grasp each slight fluctuation of student, then monitor the study state unusually when the activity of student high frequency or activity of a large margin, can send the suggestion to head of a family APP end.
And the environment parameter detection module is used for detecting the indoor environment parameters of the student such as temperature, humidity, brightness and the like. Thereby judging whether the student is in the normal learning environment range.
Referring to fig. 7, in an exemplary embodiment, the intelligent wearable device 2 further includes an electrocardiogram acquisition module, configured to acquire an electrocardiogram signal of the user and send the electrocardiogram signal to the central processing unit 1, and the central processing unit 1 analyzes the electrocardiogram signal according to an electrocardiogram analysis method to determine whether the user is in an abnormal learning state, where the electrocardiogram analysis method includes HRV time domain analysis and QRS wave algorithm.
Referring to fig. 8, in an exemplary embodiment, a remote monitoring method is further provided, including:
s10, collecting the physiological parameters and the loudness value of the sound of the user;
s20, when the physiological parameter exceeds a first preset threshold value, judging that the user is in an abnormal learning state; or, when the loudness value exceeds a second preset threshold value, determining that the user is in an abnormal learning state.
It can be understood that, the physiological parameters of the user and the loudness value of the sound are collected and sent to the central processing unit 1, so that the central processing unit 1 performs data operation to detect and judge the learning state of the student, for example, judge whether the sound collected by the sound collection module 3 is greater than a first preset threshold value and is greater than a learning abnormal state, or judge whether the physiological parameter information of the intelligent wearable device 2 is in a normal range value and whether the motion information is in a second preset threshold value, and if the physiological parameter information exceeds the second preset threshold value, the learning abnormal state is considered.
Furthermore, the remote monitoring method further comprises the steps of locking a safety activity area learned by the user, arranging a plurality of infrared sensors on the boundary of the safety activity area, and sending prompt information to the mobile terminal when the user exceeds the boundary. In this embodiment, the electronic fence module 7 may be an infrared position detection sensor disposed around the seat (the student can be detected by passing through the infrared position sensor) for detecting whether the student is still in the seat, and if not in the seat, the student may be notified of the parent APP end through the notification module 5, and the parent may view through the video monitoring module 6. Therefore, the remote monitoring method of the embodiment can scientifically and effectively judge whether the student is in the learning state by collecting the physiological sign data of the user and the sound data in the learning state, and simultaneously remind the student guardian of knowing the learning condition of the student in time.
While the foregoing is directed to the preferred embodiment of the present invention, it will be understood by those skilled in the art that various changes and modifications may be made without departing from the spirit and scope of the invention.
Claims (10)
1. A remote monitoring platform, comprising:
the intelligent wearable equipment comprises a central processing unit, intelligent wearable equipment, a sound acquisition module and a database module, wherein the intelligent wearable equipment, the sound acquisition module and the database module are respectively connected with the central processing unit; wherein the content of the first and second substances,
the database module is used for storing time information and content information related to the current learning course of the user;
the intelligent wearable device and the sound acquisition module are respectively used for acquiring physiological parameters and loudness values of sound of a user and respectively sending the physiological parameters and the loudness values to the central processing unit;
the central processing unit is used for judging that the user is in an abnormal learning state according to the fact that the physiological parameter exceeds a first preset threshold value, or judging that the user is in an abnormal learning state according to the fact that the loudness value exceeds a second preset threshold value.
2. The remote monitoring platform of claim 1, further comprising: and the notification module is used for sending prompt information to the mobile terminal when the central processing unit detects that the user is in the abnormal learning state.
3. The remote monitoring platform of claim 2, further comprising: a video monitoring module for monitoring the video data,
when the central processing unit detects that the user is in the learning abnormal state, the central processing unit triggers a starting instruction through the notification module, shoots the current learning state of the user, and sends the shot video to the mobile terminal.
4. The remote monitoring platform according to any one of claims 2 or 3, further comprising: and the electronic fence module is used for locking a safe activity area for the user to learn, and sending prompt information to the mobile terminal when the central processing unit detects that the user is in an abnormal learning state.
5. The remote monitoring platform of claim 4, wherein the electronic fence module comprises an infrared sensor to collect location information of a user, wherein the infrared sensor is disposed at a boundary of the secure activity area.
6. The remote monitoring platform of claim 1, further comprising a voice alert module for alerting the user by voice when the user is in an abnormal learning state to adjust the current learning state.
7. The remote monitoring platform according to claim 1, wherein the smart wearable device comprises a physiological parameter detection module, a motion parameter detection module and an environmental parameter detection module;
the physiological parameter detection module is used for collecting physiological parameters of a user, including heart rate, blood pressure and body temperature;
the motion parameter detection module is used for acquiring motion parameters of a user, and the motion parameters comprise the acceleration of the upper limb of the user in each direction and the activity frequency of the upper limb;
the environment parameter detection module is used for collecting indoor environment parameters including temperature, humidity and brightness of a user.
8. The remote monitoring platform of claim 7, wherein the smart wearable device further comprises an electrocardiogram acquisition module to,
the method comprises the steps of obtaining an electrocardiogram signal of a user, sending the electrocardiogram signal to a central processing unit, and analyzing the electrocardiogram signal by the central processing unit according to an electrocardiogram analysis method to judge whether the user is in an abnormal learning state, wherein the electrocardiogram analysis method comprises HRV time domain analysis and QRS wave algorithm.
9. A remote monitoring method, comprising:
acquiring physiological parameters and loudness values of sound of a user;
when the physiological parameter exceeds a first preset threshold value, judging that the user is in an abnormal learning state; or, when the loudness value exceeds a second preset threshold value, determining that the user is in an abnormal learning state.
10. The remote monitoring method of claim 9, further comprising:
the method comprises the steps of locking a safe activity area learned by a user, arranging a plurality of infrared sensors on the boundary of the safe activity area, and sending prompt information to the mobile terminal when the user exceeds the boundary.
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| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114299769A (en) * | 2022-01-04 | 2022-04-08 | 华北理工大学 | Network teaching device |
| CN117670616A (en) * | 2023-12-18 | 2024-03-08 | 中国矿业大学 | Online learning state monitoring method and system based on image recognition and position matching |
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Application publication date: 20210507 |