Dual-carbon target education scene integrated management system based on Internet of Things

Abstract

The invention discloses a dual-carbon target education scene integrated management system based on the Internet of Things, and relates to the technical field of integrated management, and the system comprises an image collection and contour processing module which is used for collecting and processing contour data in real time; the contour in-out analysis module is used for carrying out symbol change detection on the contour data to obtain a contour in-out signal or a contour out-out signal; and the human body contour number counting and prompting module is used for prompting the closing of the indoor electrical equipment for only the last person or the person going out of the same batch in the room according to the contour entering signal or the contour going out signal. Through a three-dimensional coordinate system, gravity center coordinate symbol change and displacement vector analysis, a normal path is screened in combination with an access threshold value, and access of personnel is accurately judged; the human body contour ID is dynamically tracked, people going out are predicted, shutdown is reminded when no people are in the room and the equipment is started, energy waste is avoided, and the dual-carbon target is achieved.

Description

Technical Field

[0001] The present invention relates to the field of integrated management technology, and in particular to an Internet of Things-based dual-carbon target education scenario integrated management system. Background Art

[0002] Promoting the dual carbon goals in the field of education, shaping young people's low-carbon awareness through courses and practices, and reserving talents for the future low-carbon economy is not only an inevitable requirement for cultivating talents with green values and sustainable development capabilities, but also the responsibility of the education system itself as a high-energy-consuming public institution to achieve energy conservation and emission reduction and play a demonstration role. However, when teachers and students leave the classroom and forget to turn off the equipment, the equipment continues to consume power, which not only wastes energy, but also violates the educational concept of the dual carbon goals. Summary of the Invention

[0003] Technical problems solved

[0004] In response to the shortcomings of the existing technology, the present invention provides a dual-carbon goal education scenario integrated management system based on the Internet of Things, which solves the problem of continuous power consumption caused by teachers and students leaving school without turning off equipment, which not only causes energy waste but also deviates from the educational practice and concept of the dual-carbon goals.

[0005] Technical Solution

[0006] To achieve the above objectives, the present invention is implemented through the following technical solutions: a dual-carbon target education scenario integrated management system based on the Internet of Things, including the following specific modules: image acquisition and contour processing module: real-time acquisition and processing to obtain contour data; contour entry and exit analysis module: symbol change detection of contour data to obtain contour entry signal or contour exit signal; human contour quantity statistics and prompt module: according to the contour entry signal or contour exit signal, the last person left in the room or the same group of people leaving are prompted to turn off indoor electrical equipment.

[0007] Furthermore, the specific steps for obtaining the contour entry signal or the contour exit signal are as follows: the contour data includes outdoor contours, indoor contours and inlet and outlet contours, and a three-dimensional coordinate system is established with the center point of the inlet and outlet contours as the origin. The positive direction of the inlet and outlet contours pointing horizontally into the room is set as the normal vector, and a certain dimension of the three-dimensional coordinate system is parallel to the normal vector, and this dimension is recorded as the x-axis. The three-dimensional coordinates within the outdoor contour and the indoor contour are averaged to obtain the center of gravity of each contour. The contour entry signal is obtained by changing the sign of the center of gravity coordinate on the x-axis after the outdoor contour is moved into the room, and the contour exit signal can be obtained similarly.

[0008] Furthermore, the specific method of obtaining the contour entry signal is as follows: let the coordinate of the center of gravity of the outdoor contour on the x-axis be x1, and the coordinate of the center of gravity of the indoor contour on the x-axis be x2. When the product of x1 and x2 is less than zero according to the time series, the contour entry signal is obtained, and the dimension perpendicular to the normal vector is recorded as the y-axis. The displacement vector of the outdoor contour moving to the indoor intersects with the y-axis to obtain the contour continuous entry signal.

[0009] Furthermore, the specific method of obtaining the continuous contour entry signal is as follows: the displacement vector of the outdoor contour moving to the indoor in the time series intersects with the y-axis to obtain the intersection point P0, the center of gravity coordinates of the outdoor contour are set to P1 (x1, y1, z1), the center of gravity coordinates of the indoor contour are set to P2 (x2, y2, z2), and the displacement vector is obtained as p0=p1+t×(p2-p1), where p2-p1 represents t means starting from P1 Based on the movement ratio on the y-axis, a set of equations about t is established so that t satisfies both x = 0 and z = 0. The contour continuous entry signal is obtained. The interval of the inlet and outlet contours on the y-axis is set as the entry and exit threshold. The displacement vector of the outdoor contour moving to the indoor contour and passing through the entry and exit threshold is recorded as the contour normal continuous entry signal.

[0010] Furthermore, the specific method of obtaining the normal continuous contour entry signal is as follows: after experimentation, the lower limit of the entry and exit threshold is set as y 下 , the upper limit of the entry and exit threshold is y 上 , then under the premise that the displacement vector of the outdoor contour moving to the indoor contour intersects the y-axis in the time series, the coordinate range of the intersection point P0 on the y-axis is 下 with y 上 In between, the contour is obtained to enter the signal normally and continuously.

[0011] Furthermore, in the human body contour number statistics and prompt module, if a normal continuous contour entry signal is collected, it is recorded as entering the target contour, and the entering target contour is detected by the human body contour detection model. If the entering target contour is detected to be a human contour, an ID is added to the human contour, and the number of indoor IDs is counted. If the number of indoor IDs is greater than or equal to one, the power-on status of the indoor electrical equipment is monitored. If it is detected that the entering target contour is not a human contour, no operation is performed.

[0012] Furthermore, in the human body contour number statistics and prompt module, by the same token, if a normal and continuous contour outgoing signal is collected, it is recorded as an outgoing target contour. If the outgoing target contour is detected to have an ID, this ID is deleted, and the number of indoor IDs is updated, and it is predicted whether the subsequent outgoing target contour has an ID. If the outgoing target contour is predicted to have an ID, this ID is pre-deleted, and the number of indoor IDs is continued to be pre-updated until the predicted number of indoor IDs is equal to zero and the indoor electrical equipment is in the on state, then a reminder is issued indoors. If the predicted and detected outgoing target contours have no ID or the indoor electrical equipment is in the off state, no operation is performed.

[0013] Furthermore, the specific steps of predicting the target contour are as follows: the distance threshold that triggers the prediction of whether the subsequent target contour has an ID is set as the distance threshold, and the displacement vector of the target contour is recorded as The threshold of the displacement vector from the target contour to the inlet and outlet is set through experiments and recorded as the direction threshold. Any displacement vector within this direction threshold is recorded as Through and The cosine similarity calculation is performed, and the cosine similarity is equal to one. That is, the target contour is predicted if both the target contour is within the target distance threshold and the cosine similarity is equal to one.

[0014] Furthermore, the specific method of making the cosine similarity equal to one is as follows: Among them, 1 means the cosine similarity is equal to one, represents the displacement vector of the target contour, represents any displacement vector within the direction threshold, express The model, express Model.

[0015] Furthermore, the specific steps for predicting that the number of indoor IDs is equal to zero are as follows: when the outgoing target outline is detected to be a human outline, continue to perform outgoing interval time detection on the human outlines that simultaneously meet the outgoing target outline within the outgoing distance threshold and the cosine similarity equal to one, and obtain the outgoing interval time between the previous human outline and the next human outline, which is recorded as the interval time. After experiments, the same batch of time thresholds are set. If the interval time is within the same batch of time thresholds, when pre-updating the number of indoor IDs, the number of corresponding human outlines is subtracted at a time. If the interval time is not within the same batch of time thresholds, when pre-updating the number of indoor IDs, the number of human outlines is subtracted at a time as one, and the number of indoor IDs is pre-updated, and so on, until the predicted number of indoor IDs is equal to zero.

[0016] Beneficial effects

[0017] Compared with the prior art, the embodiments of the present invention have at least the following advantages or beneficial effects:

[0018] 1. Through the analysis of the three-dimensional coordinate system, the change of the center of gravity coordinate sign and the displacement vector, combined with the entry and exit thresholds, the normal path is screened, interference is eliminated, and the accuracy and reliability of the judgment of personnel entry and exit status are guaranteed.

[0019] 2. By dynamically tracking the human body contour ID, combined with distance, direction thresholds and interval time, it predicts the people who go out. When it detects that there is only one person left in the room or the same group of people are about to go out and the device is turned on, it will issue an educational scenario reminder to avoid energy waste and implement the dual carbon goals.

[0020] Of course, any product implementing the present invention does not necessarily need to achieve all of the advantages described above at the same time. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] Figure 1 This is the present invention: a structural diagram of a dual-carbon goal education scenario integrated management system based on the Internet of Things. DETAILED DESCRIPTION

[0022] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0023] It should be noted that, in this document, relational terms such as first and second are used only to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual relationship or order between these entities or operations. Moreover, the terms "include," "comprise," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that includes a list of elements includes not only those elements but also other elements not explicitly listed, or elements inherent to such process, method, article, or apparatus.

[0024] like Figure 1 As shown, the embodiment of the present invention provides an integrated management system for dual-carbon education scenarios based on the Internet of Things, which includes the following specific modules:

[0025] Image acquisition and contour processing module: Real-time image data is collected through cameras, which are arranged indoors and outdoors. Based on the Internet of Things technology, the indoor image data and the outdoor image data are networked and collaboratively calibrated, and the multi-source image data are spliced through image registration and fusion algorithms, such as the SIFT algorithm, which is used to splice multi-source image data and perform filtering and noise reduction on the image data, which helps to improve the quality of the image data. The image data is processed through image contour segmentation algorithms and contour motion tracking algorithms. Image contour segmentation algorithms, such as the Sobel algorithm, are used to divide the contours of human bodies or objects in image data. Contour motion tracking algorithms, such as the Lucas-Kanade optical flow method, are used to track the contour motion of human bodies or objects in image data to obtain contour data. The contour data includes outdoor contours, indoor contours, and inlet and outlet contours. The outdoor contour is moved indoors to become the indoor contour, the indoor contour is moved outdoors to become the outdoor contour, and the inlet and outlet contours are recorded as inlet and outlet.

[0026] Contour entry and exit analysis module: With the center point of the entrance and exit as the origin, a three-dimensional coordinate system of x-axis, y-axis and z-axis is established, the positive direction of the entrance and exit pointing to the room is set as the normal vector, and a dimension of the three-dimensional coordinate system is parallel to the normal vector, which is recorded as the x-axis. The three-dimensional coordinates of the outdoor contour and the indoor contour are averaged to obtain the center of gravity of each contour. Since the coordinate sign of the center of gravity of the outdoor contour on the x-axis is opposite to that of the previous coordinate after the coordinate of the center of gravity of the outdoor contour is moved to the room, the coordinate sign of the center of gravity on the x-axis changes after the outdoor contour is moved to the room, and the contour entry signal is obtained. The dimension perpendicular to the normal vector is recorded as the y-axis. The displacement vector moving into the room intersects with the y-axis to obtain a contour continuous entry signal, which avoids camera failure, causing the outdoor contour to suddenly appear indoors and then directly become the indoor contour. The interval of the entrance and exit on the y-axis is set as the entry and exit threshold. The displacement vector of the outdoor contour moving into the room and passing through the entry and exit threshold is recorded as the contour normal continuous entry signal, which avoids the outdoor contour entering the room from abnormal entrances and exits and being detected by this system. Abnormal entrances and exits refer to entrances and exits other than doors, which prevents situations other than dual-carbon target education from misleading this system. Similarly, the displacement vector of the indoor contour moving to the outdoors and passing through the entry and exit threshold is recorded as the contour normal continuous exit signal.

[0027] The specific method of obtaining the contour entry signal is as follows:

[0028] Assume that the coordinate of the center of gravity of the outdoor contour on the x-axis is x1, and the coordinate of the center of gravity of the indoor contour on the x-axis is x2. Since the center point of the entrance and exit is the origin, the signs of x1 and x2 are opposite. Then, according to the time series, the product of x1 and x2 is less than zero, and the contour entry signal is obtained.

[0029] The specific method of obtaining the contour continuous entry signal is as follows:

[0030] Since one of the characteristics of a vector is continuity, the displacement vector of the outdoor contour moving to the indoor contour intersects with the y-axis in the time series, and the intersection point P0 is obtained. Let the center of gravity coordinates of the outdoor contour be P1 (x1, y1, z1), and the center of gravity coordinates of the indoor contour be P2 (x2, y2, z2), so the displacement vector is The intersection point P0 means starting from P1 The movement ratio on the t is p0=p1+t×(p2-p1), where p2-p1 represents t means starting from P1 The movement ratio on the vertical axis, t ranges from zero to one. Since the intersection point P0 is 0 on both the x-axis and the z-axis, a set of equations about t is established so that t satisfies both x = 0 and z = 0. That is, the displacement vector of the outdoor contour moving to the indoor contour in the time series intersects with the y-axis, and the contour continuous entry signal is obtained.

[0031] The specific method of obtaining the normal continuous contour entry signal is as follows:

[0032] After experiment, the lower limit of the entry and exit threshold is set to y 下 , the upper limit of the entry and exit threshold is y 上 , then under the premise that the displacement vector of the outdoor contour moving to the indoor contour intersects the y-axis in the time series, the coordinate range of the intersection point P0 on the y-axis is 下 with y 上 In between, the contour is obtained to enter the signal normally and continuously.

[0033] Human contour number statistics and prompt module: If a normal continuous contour entry signal is collected, that is, the outdoor contour enters the room and becomes the indoor contour, it is recorded as the entering target contour, and the entering target contour is detected by the human contour detection model, such as the YOLO model, which is used to detect whether the entering target contour is a human contour. If the entering target contour is detected to be a human contour, an ID is added to the human contour to determine the uniqueness of the human contour, and the number of indoor IDs is counted. If the number of indoor IDs is greater than or equal to one, the on-state of the indoor electrical equipment is monitored. If the entering target contour is detected to be an object contour, no operation is performed. If a normal continuous contour exit signal is collected, it is recorded as the exiting target contour. If it is detected to be an exiting target contour, The target profile has an ID, delete this ID, and update the number of indoor IDs, and predict whether the subsequent target profile has an ID. If the target profile is predicted to have an ID, pre-delete this ID and continue to pre-update the number of indoor IDs until the predicted number of indoor IDs is equal to zero and the indoor electrical equipment is turned on. Then a reminder is issued indoors, reminding the last remaining person or group of people who are about to go out to turn off the equipment. This reminder is an educational scenario, educating teachers and students to remember to turn off indoor electrical equipment when leaving the classroom to avoid continuous power consumption of the equipment, not only to prevent energy waste, but also to prevent violation of the educational concept of the dual carbon goals. If the predicted and detected target profiles have no ID or the indoor electrical equipment is turned off, no operation is performed.

[0034] The specific steps to predict the target contour are as follows:

[0035] The experiment sets the distance threshold for triggering the prediction of whether the subsequent outgoing target contour has an ID, which is recorded as the outgoing distance threshold. It means that the distance from the current position of the human body contour to the entrance and exit is within the outgoing distance threshold, and the displacement vector of the outgoing target contour is recorded as The threshold of the displacement vector from the target contour to the inlet and outlet is set through experiments and recorded as the direction threshold. Any displacement vector within this direction threshold is recorded as Through and The cosine similarity calculation is performed, and the cosine similarity is equal to one. That is, the target contour is predicted if both the target contour is within the target distance threshold and the cosine similarity is equal to one.

[0036] The specific method for cosine similarity to be equal to one is as follows:

[0037]

[0038] Among them, 1 means the cosine similarity is equal to one, represents the displacement vector of the target contour, represents any displacement vector within the direction threshold, express The model, express Model.

[0039] The specific steps to predict the number of indoor IDs equal to zero are as follows:

[0040] When the outgoing target contour is detected to be a human contour, the outgoing interval time detection is continued for the human contours that meet the requirements of the outgoing target contour within the outgoing distance threshold and the cosine similarity equal to one, and the outgoing interval time between the previous human contour and the next human contour is obtained, which is recorded as the interval time. The same batch time threshold is set through experiments. If the interval time is within the same batch time threshold, it means the same batch of human contours. When pre-updating the number of indoor IDs, the number of corresponding human contours is subtracted at a time. If the interval time is not within the same batch time threshold, when pre-updating the number of indoor IDs, the number of human contours is subtracted at a time as one, and the number of indoor IDs is pre-updated, and so on, until the predicted number of indoor IDs is equal to zero, but the actual number of indoor IDs is one or N at this time, and this N represents the human contours that go out together in the same batch.

[0041] The preferred embodiments of the present invention disclosed above are intended only to help illustrate the present invention. These preferred embodiments do not exhaustively describe all details, nor do they limit the present invention to the specific embodiments described. Obviously, many modifications and variations are possible based on the contents of this specification. These embodiments are selected and described in detail in this specification to better explain the principles and practical applications of the present invention, thereby enabling those skilled in the art to better understand and utilize the present invention. The present invention is limited only by the claims and their full scope and equivalents.

Claims

1. An integrated management system for dual-carbon education scenarios based on the Internet of Things, characterized by: Includes the following specific modules: Image acquisition and contour processing module: used to acquire and process contour data in real time; Contour entry and exit analysis module: used to detect sign changes in contour data and obtain contour entry signals or contour exit signals; Human silhouette counting and prompting module: used to prompt the last person in the room or the last person in the same group to turn off indoor electrical equipment based on the silhouette entry signal or the silhouette exit signal.

2. The dual-carbon goal education scenario integrated management system based on the Internet of Things according to claim 1 is characterized by: The specific steps of obtaining the contour entry signal or the contour exit signal are: The contour data includes outdoor contours, indoor contours, and inlet and outlet contours. A three-dimensional coordinate system is established with the center point of the inlet and outlet contours as the origin. The positive direction of the inlet and outlet contours pointing horizontally into the room is set as the normal vector. A certain dimension of the three-dimensional coordinate system is parallel to the normal vector, and this dimension is recorded as the x-axis. The three-dimensional coordinates within the outdoor contour and the indoor contour are averaged to obtain the center of gravity of each contour. The sign of the center of gravity coordinate on the x-axis changes after the outdoor contour is moved into the room, and the contour entry signal is obtained. Similarly, the contour exit signal can be obtained.

3. The dual-carbon goal education scenario integrated management system based on the Internet of Things according to claim 2 is characterized by: The specific method of obtaining the contour entry signal is as follows: Assume that the coordinate of the center of gravity of the outdoor contour on the x-axis is x1, and the coordinate of the center of gravity of the indoor contour on the x-axis is x2. According to the time series, when the product of x1 and x2 is less than zero, the contour entry signal is obtained. The dimension perpendicular to the normal vector is recorded as the y-axis. The displacement vector of the outdoor contour moving to the indoor intersects with the y-axis, and the contour continuous entry signal is obtained.

4. The dual-carbon goal education scenario integrated management system based on the Internet of Things according to claim 3 is characterized by: The specific method of obtaining the contour continuous entry signal is as follows: In the time series, the displacement vector of the outdoor contour moving to the indoor intersects with the y-axis, and the intersection point P0 is obtained. Let the center of gravity coordinates of the outdoor contour be P1 (x1, y1, z1), and the center of gravity coordinates of the indoor contour be P2 (x2, y2, z2), and the displacement vector is obtained as Where p2-p1 represents t means starting from P1 Based on the movement ratio on the y-axis, a set of equations about t is established so that t satisfies both x = 0 and z = 0. The contour continuous entry signal is obtained. The interval of the inlet and outlet contours on the y-axis is set as the entry and exit threshold. The displacement vector of the outdoor contour moving to the indoor contour and passing through the entry and exit threshold is recorded as the contour normal continuous entry signal.

5. The dual-carbon goal education scenario integrated management system based on the Internet of Things according to claim 4 is characterized by: The specific method of obtaining the normal continuous entry signal of the contour is as follows: After experiment, the lower limit of the entry and exit threshold is set to y 下 , the upper limit of the entry and exit threshold is y 上 , then under the premise that the displacement vector of the outdoor contour moving to the indoor contour intersects the y-axis in the time series, the coordinate range of the intersection point P0 on the y-axis is 下 with y 上 In between, the contour is obtained to enter the signal normally and continuously.

6. The dual-carbon goal education scenario integrated management system based on the Internet of Things according to claims 1 to 5 is characterized by: In the human contour number statistics and prompt module, if a normal continuous contour entry signal is collected, it is recorded as the entry target contour. The entry target contour is detected by the human contour detection model. If the entry target contour is detected to be a human contour, the ID of the human contour is added, and the number of indoor IDs is counted. If the number of indoor IDs is greater than or equal to one, the power-on status of the indoor electrical equipment is monitored. If it is detected that the entry target contour is not a human contour, no operation is performed.

7. The dual-carbon goal education scenario integrated management system based on the Internet of Things according to claims 1 to 5 is characterized by: In the human body contour number statistics and prompt module, by the same token, if a normal and continuous contour outgoing signal is collected, it is recorded as an outgoing target contour. If the outgoing target contour is detected to have an ID, this ID is deleted, and the number of indoor IDs is updated, and it is predicted whether the subsequent outgoing target contour has an ID. If the outgoing target contour is predicted to have an ID, this ID is pre-deleted, and the number of indoor IDs is continued to be pre-updated until the predicted number of indoor IDs is equal to zero and the indoor electrical equipment is in the on state, a reminder is issued indoors. If the predicted and detected outgoing target contours have no ID or the indoor electrical equipment is in the off state, no operation is performed.

8. The dual-carbon goal education scenario integrated management system based on the Internet of Things according to claim 7 is characterized by: The specific steps of predicting the target contour are as follows: The experiment sets the distance threshold that triggers the prediction of whether the subsequent outgoing target contour has an ID, which is recorded as the outgoing distance threshold. The displacement vector of the outgoing target contour is recorded as The threshold of the displacement vector from the target contour to the inlet and outlet is set through experiments and recorded as the direction threshold. Any displacement vector within this direction threshold is recorded as Through and The cosine similarity calculation is performed, and the cosine similarity is equal to one. That is, the target contour is predicted if both the target contour is within the target distance threshold and the cosine similarity is equal to one.

9. The dual-carbon goal education scenario integrated management system based on the Internet of Things according to claim 8 is characterized by: The specific method of achieving cosine similarity equal to one is as follows: Among them, 1 means the cosine similarity is equal to one, represents the displacement vector of the target contour, represents any displacement vector within the direction threshold, express The model, express Model.

10. The dual-carbon goal education scenario integrated management system based on the Internet of Things according to claim 7 is characterized by: The specific steps of predicting that the number of indoor IDs is equal to zero are as follows: When the outgoing target contour is detected to be a human contour, the outgoing interval time detection is continued for the human contours that satisfy the outgoing target contour within the outgoing distance threshold and the cosine similarity equal to one, and the outgoing interval time between the previous human contour and the next human contour is obtained, which is recorded as the interval time. The same batch of time thresholds are set through experiments. If the interval time is within the same batch of time thresholds, the number of corresponding human contours is subtracted at a time when the number of indoor IDs is pre-updated. If the interval time is not within the same batch of time thresholds, the number of human contours is subtracted at a time when the number of indoor IDs is pre-updated, and the number of indoor IDs is pre-updated, and so on, until the predicted number of indoor IDs is equal to zero.

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