A classroom air conditioning power saving management system based on Internet of Things technology

Abstract

The present invention discloses a classroom air conditioning power saving management system based on the Internet of Things technology, which relates to the technical field of the Internet of Things, including an indoor number monitoring unit. Taking the air conditioning power saving management system for a self-study classroom as an example, the indoor number monitoring unit is used to deploy image monitoring equipment in the self-study classroom to realize the information collection of the number of students in the self-study classroom based on the collected image data, and collect the reservation information of the self-study classroom, and obtain the actual attendance rate information of the number of students who have made reservations based on the identified student number information. The present invention proposes a classroom air conditioning power saving management system based on the Internet of Things technology, which collects the reservation information of each self-study classroom and the information on the number of students who have actually arrived through the set indoor number monitoring unit, thereby providing data support for the subsequent adjustment of the operating status and control right of the air conditioner, and monitors the operating status of the air conditioner through the set air conditioner status monitoring unit.

Description

Technical Field

[0001] The present invention relates to the technical field of Internet of Things, and in particular to a classroom air-conditioning power saving management system based on the Internet of Things technology. Background Art

[0002] Air conditioning, or air conditioner, refers to equipment that uses artificial means to adjust and control parameters such as temperature, humidity, and flow rate of ambient air in buildings or structures. It generally includes cold source / heat source equipment, cold and hot medium distribution systems, terminal devices, and other parts and other auxiliary equipment. The Chinese patent application number 202210571190.7 discloses a "personnel behavior management air conditioning energy-saving system, including a presence sensor, a temperature sensor, a Xiaohu gateway, a cloud, a water system air conditioner, a refrigerant system air conditioner, and a central air conditioner. The output end of the presence sensor and the input end of the Xiaohu gateway are connected via a Z-WAVE wireless communication protocol. The output end of the temperature sensor is connected to the input end of the Xiaohu gateway through the Z-WAVE wireless communication protocol. The personnel behavior management air conditioning energy-saving system is mainly used in household and office variable refrigerant air conditioners, split air conditioners, and large commercial water system air conditioners. It is particularly effective in the use of variable refrigerant air conditioners, and can save 20-30% of electricity. The total amount of greenhouse gas emissions generated directly or indirectly can be offset by energy conservation and emission reduction to achieve "zero emission" of carbon dioxide. The system runs stably and can effectively resist interference from various wireless signals such as 5G, WiFi, and Bluetooth. ";

[0003] This prior art only solves the problem that, in actual use, when no one is in the room, the air conditioner is still turned on, so that when no one is in the room, the energy-saving air conditioner remains in normal working state, resulting in energy consumption, making the energy-saving effect of the existing energy-saving air conditioner poor. It does not take into account that when the air conditioner in the study room is managed to save electricity, it is necessary to adjust the control right of the air conditioner and the operating state of the air conditioner based on the actual number of students in the study room to improve the energy utilization rate of the air conditioner, and monitor the energy consumption of the air conditioner in the operating state to facilitate the handling of abnormal energy consumption. Summary of the invention

[0004] The purpose of the present invention is to provide a classroom air conditioning power saving management system based on Internet of Things technology to solve the problems raised in the above background technology.

[0005] To achieve the above-mentioned purpose, the present invention provides the following technical solutions: a classroom air conditioning power saving management system based on the Internet of Things technology, including an indoor number monitoring unit, taking the air conditioning power saving management system for a self-study classroom as an example, the indoor number monitoring unit is used to deploy an image monitoring device in the self-study classroom to realize the information collection of the number of students in the self-study classroom based on the collected image data, and collect the reservation information of the self-study classroom, and obtain the actual attendance rate information of the number of reserved students based on the identified student number information;

[0006] An air conditioner status monitoring unit, wherein the air conditioner status monitoring unit is used to install a monitoring device for monitoring air conditioner vibration information, and train the monitoring device to achieve learning of the stationary and running states of the air conditioner, and obtain the running state of the air conditioner through the monitoring device that has completed the learning;

[0007] An air conditioning state adjustment unit, the air conditioning state adjustment unit is used to identify the information of students entering the building where the self-study classroom is located based on the reservation information of the self-study classroom, perform air conditioning pre-cooling operation based on the identification result, and adjust the air conditioning operation state based on the actual number of students in the self-study classroom;

[0008] An air conditioning energy consumption monitoring unit is used to construct an air conditioning energy consumption monitoring model, and to construct an air conditioning energy consumption data set based on historical air conditioning energy consumption data, and to train the air conditioning energy consumption monitoring model through the air conditioning energy consumption data set. The trained air conditioning energy consumption monitoring model performs abnormal air conditioning energy consumption detection operations based on real-time air conditioning energy consumption data.

[0009] Preferably, the indoor number monitoring unit includes a monitoring equipment deployment module and a reservation information collection module. The monitoring equipment deployment module is used to evenly distribute cameras and Raspberry Pis around the self-study classroom to achieve full coverage monitoring of the image in the self-study classroom, thereby ensuring accurate detection of the actual number of people in the self-study classroom. The reservation information collection module is used to collect relevant reservation information of each self-study classroom, including reservation number information for the three time periods of morning, afternoon and evening, the location of the reserved self-study classroom, personal information of the reserved students and reservation time period information, so as to obtain the reservation number information for each self-study classroom in different time periods.

[0010] Preferably, the indoor number monitoring unit also includes an image data collection module and an indoor number recognition module. The image data collection module is used to collect video images of students in the self-study classroom through a camera arranged in the self-study classroom, and perform facial image capture operations on the video, and process the captured facial images, including performing image grayscale operations on the captured facial images, and performing image multi-scale transformation and repeated image merging operations on the facial images after the image grayscale operation, and finally performing histogram equalization operations on the facial images to improve the detection of facial features in the facial images and improve the accuracy of identifying student identities. The indoor number recognition module is used to identify and verify the identities of each student in the self-study classroom based on the facial images processed in the image data collection module and the facial image information in the personal information of the students who have made reservations in the corresponding self-study classroom, and then obtain the actual attendance rate information of the number of reservations based on the identified student information.

[0011] Preferably, the air conditioning status monitoring unit includes a monitoring device installation module, which is used to install ESP32 and a three-axis sensor on the air conditioner in the study room. Through the high sensitivity of the three-axis sensor, it quickly responds to changes in the air conditioning status, thereby obtaining accurate air conditioning vibration messages, and through a combination of WIFI connection and MQTT connection, communication between the four modules of the host Raspberry Pi, the three-axis sensor module, the infrared ray module and the language broadcast module is achieved, so that the system can operate normally in various network environments.

[0012] Preferably, the air conditioning status monitoring unit also includes a monitoring device training module and an air conditioning status acquisition module. The monitoring device training module is used to perform infrared signal learning operations of various air conditioning models on the installed ESP32 and three-axis sensor, and perform multiple air conditioning static state learning operations on the three-axis sensor, so as to be used for subsequent identification of air conditioning on-off. The air conditioning status acquisition module is used to acquire the current operating status of the air conditioner in the self-study classroom through the learned ESP32 and three-axis sensor, and add an information encryption security mechanism during the information transmission process, so as to ensure the security of communication through the encryption protocol and prevent potential network attacks and information leakage risks.

[0013] Preferably, the air-conditioning state adjustment unit includes an air-conditioning precooling module, which is used to collect facial images and verify student identities of students entering the building where each self-study classroom is located based on the student facial information in the student personal information in the relevant reservation information of the self-study classroom obtained in the reservation information collection module, and when it is recognized that the student in the reservation information enters the building where the self-study classroom is located, the air-conditioning in the corresponding reserved self-study classroom is precooled, and the cooling load value and precooling time of the air-conditioning are calculated by the air-conditioning precooling algorithm, and the specific calculation formula is as follows:

[0014]

[0015] In the formula, represents the cooling load value of the air conditioner, j represents the reservation day, i represents the time when the student in the reservation information enters the building where the self-study classroom is located, represents the learning coefficient, Z ij represents the building load value, m represents the start time of the reservation period, M represents the end time of the reservation period, T represents the precooling time, K represents the precooling load constant, K * represents the time constant, P(S j -1) represents the activation function, which means estimating and correcting the precooling time of the day by comparing the deviation between the actual value of the precooling time of the previous day and the calculated value, and turning on the air conditioner for cooling operation when the students in the reservation information enter the corresponding self-study classroom.

[0016] Preferably, the air-conditioning state adjustment unit also includes an air-conditioning operation state change module, which is used to obtain the information of the number of students actually arriving in the self-study classroom within the reservation period through the indoor number recognition module, and compare it with the lower threshold of the number of self-study students in each self-study classroom preset by the management personnel, and the lower threshold of the number of self-study students in the self-study classroom is set according to the number of self-study students that each self-study classroom can accommodate. When the number of students actually arriving in the self-study classroom within the reservation period is not greater than the lower threshold of the number of self-study students in the corresponding self-study classroom preset by the management personnel, the number of students actually arriving in the reservation period is obtained. The location information of the study classrooms whose number is greater than the lower threshold of the number of self-study students preset by the administrator and there are remaining unreserved seats is announced through the loudspeaker based on the speech synthesis technology to remind the students to go to the study classrooms with the obtained location for self-study and turn off the air conditioner after ten minutes. When it is recognized that there are no students in the study classroom, the air conditioner can be turned off in advance, and the air conditioning cooling operation is maintained only when there are no remaining unreserved seats in other study classrooms. When the number of students actually arriving in the study classroom during the reservation time period is greater than the lower threshold of the number of self-study students in the corresponding study classroom preset by the administrator, the air conditioner in the study classroom is normally controlled and adjusted by the students.

[0017] Preferably, the air conditioning energy consumption monitoring unit includes an air conditioning energy consumption monitoring model construction module and a model training module. The air conditioning energy consumption monitoring model construction module is used to construct an air conditioning energy consumption monitoring model based on a convolutional neural network, including an input layer, a convolution layer, a pooling layer, a fully connected layer and an output layer. The model training module is used to obtain the historical energy consumption data of the air conditioner in the self-study classroom, and to construct an air conditioning energy consumption data set based on the acquired historical air conditioning energy consumption data. The air conditioning energy consumption monitoring model is trained by the air conditioning energy consumption data set, and the trained air conditioning energy consumption monitoring model is verified by the model accuracy algorithm. The specific calculation formula is as follows:

[0018]

[0019] Where PR represents the accuracy value of the air conditioning energy consumption monitoring model, TP represents the number of sample data detected correctly, and FP represents the number of sample data detected incorrectly. When the calculated result is greater than 0.95, it indicates that the accuracy of the air conditioning energy consumption monitoring model meets the requirements. When the calculated result is not greater than 0.95, it indicates that the accuracy of the customer's air conditioning energy consumption monitoring model does not meet the requirements and the air conditioning energy consumption monitoring model needs to be optimized and adjusted.

[0020] Preferably, the air conditioning energy consumption monitoring unit also includes an air conditioning energy consumption data acquisition module and an air conditioning abnormal energy consumption detection module. The air conditioning energy consumption data acquisition module is used to acquire real-time energy consumption data of the air conditioner in the self-study classroom which is in operation, and add a timestamp tag to the acquired real-time energy consumption data of the air conditioner. The air conditioning abnormal energy consumption detection module is used to perform abnormal air conditioning energy consumption detection operations based on the real-time energy consumption data of the air conditioner, and inspect and process the air conditioner with abnormal energy consumption based on the detection result and the timestamp tag of the real-time energy consumption data of the air conditioner.

[0021] Compared with the prior art, the beneficial effects of the present invention at least include: the present invention proposes a classroom air-conditioning power saving management system based on the Internet of Things technology, which collects the reservation information of each self-study classroom and the information on the actual number of students arriving through the set indoor population monitoring unit, thereby providing data support for the subsequent adjustment of the operating status and control rights of the air conditioner, and monitors the operating status of the air conditioner through the set air-conditioning status monitoring unit. After the set air-conditioning status adjustment unit recognizes that the students in the reservation information enter the building where the self-study classroom is located, the air-conditioning in the corresponding reserved self-study classroom is pre-cooled, and when the students in the reservation information enter the corresponding self-study classroom, the air-conditioning is turned on for cooling, and the operating status and control rights of the air conditioner are adjusted based on the actual number of students in the self-study classroom during the reservation period, thereby improving the energy utilization rate of the air conditioner, and an air-conditioning energy consumption monitoring model is constructed through the set air-conditioning energy consumption monitoring unit, and the air-conditioning energy consumption monitoring model is trained, and the air-conditioning abnormal energy consumption detection operation is performed through the trained air-conditioning energy consumption monitoring model. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] Figure 1 It is a schematic diagram of the overall process of an embodiment of the present invention;

[0023] Figure 2 This is a flow chart of an indoor number monitoring unit according to an embodiment of the present invention;

[0024] Figure 3 This is a schematic diagram of the process of the air conditioner status monitoring unit according to an embodiment of the present invention;

[0025] Figure 4 This is a schematic diagram of the process of the air conditioning state adjustment unit according to an embodiment of the present invention;

[0026] Figure 5 The figure is a flow chart of an air conditioning energy consumption monitoring unit according to an embodiment of the present invention.

[0027] In the figure: 100, indoor number monitoring unit; 101, monitoring equipment deployment module; 102, reservation information collection module; 103, image data collection module; 104, indoor number recognition module; 200, air-conditioning status monitoring unit; 201, monitoring equipment installation module; 202, monitoring equipment training module; 203, air-conditioning status acquisition module; 300, air-conditioning status adjustment unit; 301, air-conditioning pre-cooling module; 302, air-conditioning operation status change module; 400, air-conditioning energy consumption monitoring unit; 401, air-conditioning energy consumption monitoring model construction module; 402, model training module; 403, air-conditioning energy consumption data acquisition module; 404, air-conditioning abnormal energy consumption detection module. DETAILED DESCRIPTION

[0028] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. 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 creative work are within the scope of protection of the present invention.

[0029] See also Figure 1-5 The present invention provides a technical solution: a classroom air conditioning power saving management system based on the Internet of Things technology, including an indoor number monitoring unit 100. Taking the air conditioning power saving management system for a self-study classroom as an example, the indoor number monitoring unit 100 is used to deploy image monitoring equipment in the self-study classroom to realize the information collection of the number of students in the self-study classroom based on the collected image data, and collect the reservation information of the self-study classroom. Based on the identified student number information, the actual attendance rate information of the number of reserved students is obtained;

[0030] The air conditioner status monitoring unit 200 is used to install a monitoring device for monitoring the vibration information of the air conditioner, and train the monitoring device to learn the static and running states of the air conditioner, and obtain the running state of the air conditioner through the monitoring device after learning;

[0031] The air conditioning state adjustment unit 300 is used to identify the students who enter the building where the self-study classroom is located based on the reservation information of the self-study classroom, perform air conditioning pre-cooling operation based on the identification result, and adjust the air conditioning operation state based on the actual number of students in the self-study classroom;

[0032] The air conditioning energy consumption monitoring unit 400 is used to construct an air conditioning energy consumption monitoring model, and to construct an air conditioning energy consumption data set based on historical air conditioning energy consumption data, and to train the air conditioning energy consumption monitoring model through the air conditioning energy consumption data set. The trained air conditioning energy consumption monitoring model performs abnormal air conditioning energy consumption detection operations based on the real-time air conditioning energy consumption data.

[0033] The indoor number monitoring unit 100 includes a monitoring device deployment module 101 and a reservation information collection module 102. The monitoring device deployment module 101 is used to evenly distribute cameras and Raspberry Pis around the self-study classroom to achieve full coverage monitoring of the images in the self-study classroom, thereby ensuring accurate detection of the actual number of people in the self-study classroom. The reservation information collection module 102 is used to collect relevant reservation information of each self-study classroom, including reservation number information in the morning, afternoon and evening, reservation self-study classroom location, reservation student personal information and reservation time period information, so as to obtain reservation number information of each self-study classroom in different time periods;

[0034] The indoor number monitoring unit 100 also includes an image data collection module 103 and an indoor number recognition module 104. The image data collection module 103 is used to collect video images of students in the self-study classroom through the camera arranged in the self-study classroom, and perform a facial image interception operation on the video, and process the intercepted facial image, including performing an image grayscale operation on the intercepted facial image, and performing an image multi-scale transformation and repeated image merging operations on the facial image after the image grayscale operation, and finally performing a histogram equalization operation on the facial image to improve the detection of facial features in the facial image and improve the accuracy of identifying the identity of the student. The indoor number recognition module 104 is used to identify and verify the identity of each student in the self-study classroom based on the facial image processed in the image data collection module 103 and the facial image information in the personal information of the students who have made reservations in the corresponding self-study classroom, and then obtain the actual attendance rate information of the number of reservations based on the identified student information;

[0035] The air conditioner status monitoring unit 200 includes a monitoring device installation module 201, which is used to install ESP32 and a three-axis sensor on the air conditioner in the self-study classroom. The high sensitivity of the three-axis sensor can quickly respond to changes in the air conditioner status, thereby obtaining accurate air conditioner vibration information, and realize communication between the four modules of the host Raspberry Pi, the three-axis sensor module, the infrared ray module, and the language broadcast module through a combination of WIFI connection and MQTT connection, so that the system can operate normally in various network environments;

[0036] The air conditioner status monitoring unit 200 further includes a monitoring device training module 202 and an air conditioner status acquisition module 203. The monitoring device training module 202 is used to perform infrared signal learning operations of various air conditioner models on the installed ESP32 and the three-axis sensor, and perform multiple learning operations of the air conditioner static state on the three-axis sensor, so as to be used for subsequent identification of the air conditioner on. The air conditioner status acquisition module 203 is used to obtain the current operating state of the air conditioner in the self-study classroom through the learned ESP32 and the three-axis sensor, and add an information encryption security mechanism in the information transmission process, so as to ensure the security of communication through the encryption protocol and prevent potential network attacks and information leakage risks;

[0037] The air conditioning state adjustment unit 300 includes an air conditioning precooling module 301. The air conditioning precooling module 301 is used to collect facial images and verify student identities of students entering the building where each self-study classroom is located based on the student facial information in the student personal information in the relevant reservation information of the self-study classroom obtained in the reservation information collection module 102. When it is recognized that the student in the reservation information enters the building where the self-study classroom is located, the air conditioning in the corresponding reserved self-study classroom is precooled, and the cooling load value and precooling time of the air conditioning are calculated by the air conditioning precooling algorithm. The specific calculation formula is as follows:

[0038]

[0039] In the formula, represents the cooling load value of the air conditioner, j represents the reservation day, i represents the time when the student in the reservation information enters the building where the self-study classroom is located, represents the learning coefficient, Z ij represents the building load value, m represents the start time of the reservation period, M represents the end time of the reservation period, T represents the precooling time, K represents the precooling load constant, K * represents the time constant, P(S j -1) represents the activation function, which means that the pre-cooling time of the day is estimated and corrected by comparing the deviation between the actual value of the pre-cooling time of the previous day and the calculated value, and when the student in the reservation information enters the corresponding self-study classroom, the air conditioner is turned on for cooling operation;

[0040] The air conditioning state adjustment unit 300 also includes an air conditioning operation state change module 302, which is used to obtain the information on the number of students who actually arrived in the self-study classroom during the reservation period through the indoor population recognition module 104, and compare it with the lower threshold of the number of self-study students in each self-study classroom preset by the management personnel, and the lower threshold of the number of self-study students in the self-study classroom is set according to the number of self-study students that can be accommodated in each self-study classroom. When the number of students who actually arrived in the self-study classroom during the reservation period is not greater than the lower threshold of the number of self-study students in the corresponding self-study classroom preset by the management personnel, the number of students who actually arrived in the self-study classroom during the reservation period is obtained. The location information of the self-study classrooms where the number of students is greater than the lower threshold of the number of self-study students preset by the administrator and there are remaining unreserved positions is announced through the loudspeaker based on the speech synthesis technology to remind the students to go to the self-study classrooms where the location is obtained for self-study and the air conditioner is turned off after ten minutes. When it is recognized that there are no students in the self-study classroom, the air conditioner can be turned off in advance, and the air conditioning cooling operation is maintained only when there are no remaining unreserved positions in other self-study classrooms. When the number of students who actually arrive in the self-study classroom within the reservation time period is greater than the lower threshold of the number of self-study students in the corresponding self-study classroom preset by the administrator, the air conditioner in the self-study classroom is normally controlled and adjusted by the students;

[0041] The air conditioning energy consumption monitoring unit 400 includes an air conditioning energy consumption monitoring model construction module 401 and a model training module 402. The air conditioning energy consumption monitoring model construction module 401 is used to construct an air conditioning energy consumption monitoring model based on a convolutional neural network, including an input layer, a convolution layer, a pooling layer, a fully connected layer and an output layer. The model training module 402 is used to obtain the historical energy consumption data of the air conditioning in the self-study classroom, and to construct an air conditioning energy consumption data set based on the acquired historical air conditioning energy consumption data. The air conditioning energy consumption monitoring model is trained by the air conditioning energy consumption data set, and the trained air conditioning energy consumption monitoring model is verified by the model accuracy algorithm. The specific calculation formula is as follows:

[0042]

[0043] In the formula, PR represents the accuracy value of the air conditioning energy consumption monitoring model, TP represents the number of sample data detected correctly, and FP represents the number of sample data detected incorrectly. When the calculation result is greater than 0.95, it indicates that the accuracy of the air conditioning energy consumption monitoring model meets the requirements. When the calculation result is not greater than 0.95, it indicates that the accuracy of the customer's air conditioning energy consumption monitoring model does not meet the requirements and the air conditioning energy consumption monitoring model needs to be optimized and adjusted.

[0044] The air conditioning energy consumption monitoring unit 400 also includes an air conditioning energy consumption data acquisition module 403 and an air conditioning abnormal energy consumption detection module 404. The air conditioning energy consumption data acquisition module 403 is used to acquire real-time energy consumption data of the air conditioner in the self-study classroom in operation, and add a timestamp tag to the acquired real-time energy consumption data of the air conditioner. The air conditioning abnormal energy consumption detection module 404 is used to perform abnormal air conditioning energy consumption detection operations based on the real-time energy consumption data of the air conditioner, and inspect and process the air conditioner with abnormal energy consumption based on the detection results and the timestamp tag of the real-time energy consumption data of the air conditioner.

[0045] Working principle: Through the monitoring device deployment module 101, cameras and Raspberry Pi are evenly distributed around the self-study classroom, and the reservation information of each self-study classroom is collected through the reservation information collection module 102. The video image of the students in the self-study classroom is collected through the image data collection module 103. The identity of each student in the self-study classroom is identified and verified by the indoor number recognition module 104 based on the face image processed in the image data collection module 103 and the face image information in the personal information of the students who have made reservations in the corresponding self-study classroom. The ESP32 and the three-axis sensor are installed on the air conditioner in the self-study classroom through the monitoring device installation module 201. The infrared signal learning operation of various air-conditioning models is performed on the installed ESP32 and the three-axis sensor through the monitoring device training module 202, and the three-axis sensor is subjected to multiple air-conditioning static state learning operations. The air-conditioning state acquisition module 203 is used to obtain the number of people in the self-study classroom. The current operating status of the air conditioner in the study classroom is obtained, and facial images and student identity authentication are performed on the students entering the buildings where each self-study classroom is located through the air-conditioning pre-cooling module 301. After the students in the reservation information are recognized to enter the building where the self-study classroom is located, the air-conditioning in the corresponding reserved self-study classroom is pre-cooled. The operating status of the air conditioner in the self-study classroom is adjusted based on the actual number of students in the self-study classroom through the air-conditioning operating status changing module 302. An air-conditioning energy consumption monitoring model is constructed through the air-conditioning energy consumption monitoring model construction module 401. An air-conditioning energy consumption data set is constructed through the model training module 402. The air-conditioning energy consumption monitoring model is trained through the air-conditioning energy consumption data set. The real-time energy consumption data of the air conditioner in the self-study classroom in operation is obtained through the air-conditioning energy consumption data acquisition module 403. The air-conditioning abnormal energy consumption detection operation is performed through the air-conditioning abnormal energy consumption detection module 404.

[0046] It should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device.

[0047] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A classroom air conditioning power saving management system based on Internet of Things technology, characterized by: The invention comprises an indoor number monitoring unit (100). Taking an air conditioning power saving management system for a self-study classroom as an example, the indoor number monitoring unit (100) is used to deploy image monitoring equipment in the self-study classroom to collect information on the number of students in the self-study classroom based on collected image data, collect reservation information for the self-study classroom, and obtain actual attendance rate information on the number of reserved students based on the identified student number information; The indoor number monitoring unit (100) further comprises an image data collection module (103) and an indoor number recognition module (104). The image data collection module (103) is used to collect video images of students in the self-study classroom through a camera arranged in the self-study classroom, and to perform a facial image interception operation on the video, and to process the intercepted facial image, including performing an image grayscale operation on the intercepted facial image, and performing an image multi-scale transformation and repeated image merging operations on the facial image after the image grayscale operation, and finally performing a histogram equalization operation on the facial image to improve the detection of facial features in the facial image and improve the recognition accuracy of the student identity. The indoor number recognition module (104) is used to identify and verify the identity of each student in the self-study classroom based on the facial image processed in the image data collection module (103) and the facial image information in the personal information of the students who have made reservations in the corresponding self-study classroom, and then obtain the actual attendance rate information of the number of students who have made reservations based on the identified student information; An air conditioner state monitoring unit (200), the air conditioner state monitoring unit (200) being used to install a monitoring device for monitoring vibration information of the air conditioner, and to train the monitoring device to achieve learning of the stationary and running states of the air conditioner, and to obtain the running state of the air conditioner through the monitoring device that has completed the learning; An air conditioning state adjustment unit (300), the air conditioning state adjustment unit (300) being used to identify information of students entering the building where the self-study classroom is located based on the reservation information of the self-study classroom, perform air conditioning pre-cooling operation based on the identification result, and adjust the air conditioning operation state based on the actual number of students in the self-study classroom; The air conditioning state adjustment unit (300) further comprises an air conditioning operation state change module (302), wherein the air conditioning operation state change module (302) is used to obtain information on the number of students actually arriving in the self-study classroom during the reservation period through the indoor population recognition module (104), and compare the information with the lower threshold of the number of self-study students in each self-study classroom preset by the management personnel, and the lower threshold of the number of self-study students in the self-study classroom is set according to the number of self-study students that can be accommodated in each self-study classroom. When the number of students actually arriving in the self-study classroom during the reservation period is not greater than the lower threshold of the number of self-study students in the corresponding self-study classroom preset by the management personnel, the number of students actually arriving in the self-study classroom during the reservation period is obtained. The location information of the self-study classroom where the number of students who actually arrive is greater than the lower threshold of the number of self-study students preset by the administrator and there are remaining unreserved positions is announced through the loudspeaker based on the speech synthesis technology to remind students to go to the self-study classroom where the location is obtained for self-study and turn off the air conditioner after ten minutes. When it is recognized that there are no students in the self-study classroom, the air conditioner can be turned off in advance, and the air conditioning cooling operation is maintained only when there are no remaining unreserved positions in other self-study classrooms. When the number of students who actually arrive in the self-study classroom within the reservation time period is greater than the lower threshold of the number of self-study students in the corresponding self-study classroom preset by the administrator, the air conditioner in the self-study classroom is normally controlled and adjusted by the students; An air conditioning energy consumption monitoring unit (400) is used to construct an air conditioning energy consumption monitoring model, and to construct an air conditioning energy consumption data set based on historical air conditioning energy consumption data, and to perform model training on the air conditioning energy consumption monitoring model through the air conditioning energy consumption data set, and to perform abnormal air conditioning energy consumption detection operations based on the real-time air conditioning energy consumption data through the trained air conditioning energy consumption monitoring model.

2. According to the Internet of Things technology-based classroom air conditioning power saving management system according to claim 1, it is characterized by: The indoor number monitoring unit (100) comprises a monitoring device deployment module (101) and a reservation information collection module (102). The monitoring device deployment module (101) is used to evenly deploy cameras and Raspberry Pis around the self-study classroom to achieve full coverage monitoring of the images in the self-study classroom, thereby ensuring accurate detection of the actual number of people in the self-study classroom. The reservation information collection module (102) is used to collect relevant reservation information of each self-study classroom, including reservation number information for three time periods: morning, afternoon and evening, the location of the reserved self-study classroom, personal information of the reserved students and reservation time period information, so as to obtain the reservation number information of each self-study classroom in different time periods.

3. According to the Internet of Things technology-based classroom air conditioning power saving management system according to claim 1, it is characterized by: The air conditioner status monitoring unit (200) comprises a monitoring device installation module (201), wherein the monitoring device installation module (201) is used to install ESP32 and a three-axis sensor on the air conditioner in the self-study classroom, and rapidly respond to changes in the air conditioner status through the high sensitivity of the three-axis sensor, thereby obtaining accurate air conditioner vibration information, and realize a stable connection between the Raspberry Pi, ESP32 and the speaker through a combination of WIFI connection and MQTT connection, so that the system can operate normally in various network environments.

4. According to the Internet of Things technology-based classroom air conditioning power saving management system according to claim 1, it is characterized by: The air conditioner status monitoring unit (200) further comprises a monitoring device training module (202) and an air conditioner status acquisition module (203). The monitoring device training module (202) is used to perform infrared signal learning operations of various air conditioner models on the installed ESP32 and the three-axis sensor, and to perform multiple air conditioner static state learning operations on the three-axis sensor, so as to be used for subsequent identification of air conditioner on-state. The air conditioner status acquisition module (203) is used to acquire the current operating state of the air conditioner in the self-study classroom through the learned ESP32 and the three-axis sensor, and to add an information encryption security mechanism during the information transmission process, so as to ensure the security of communication through the encryption protocol and prevent potential network attacks and information leakage risks.

5. According to the Internet of Things technology-based classroom air conditioning power saving management system according to claim 2, it is characterized by: The air conditioning state adjustment unit (300) comprises an air conditioning pre-cooling module (301), the air conditioning pre-cooling module (301) being used for collecting facial images and performing student identity verification on students entering the building where each self-study classroom is located based on the student facial information in the student personal information in the relevant reservation information of the self-study classroom obtained in the reservation information collection module (102), and when it is recognized that the student in the reservation information has entered the building where the self-study classroom is located, pre-cooling the air conditioner in the corresponding reserved self-study classroom is performed, and the cooling load value and pre-cooling time of the air conditioner are calculated through an air conditioning pre-cooling algorithm, and when the student in the reservation information has entered the corresponding self-study classroom, the air conditioner is turned on for cooling.

6. According to the Internet of Things technology-based classroom air conditioning power saving management system of claim 1, it is characterized by: The air conditioning energy consumption monitoring unit (400) comprises an air conditioning energy consumption monitoring model construction module (401) and a model training module (402). The air conditioning energy consumption monitoring model construction module (401) is used to construct an air conditioning energy consumption monitoring model based on a convolutional neural network, comprising an input layer, a convolutional layer, a pooling layer, a fully connected layer and an output layer. The model training module (402) is used to obtain historical energy consumption data of the air conditioning in the self-study classroom, and to construct an air conditioning energy consumption data set based on the acquired historical air conditioning energy consumption data. The air conditioning energy consumption monitoring model is trained using the air conditioning energy consumption data set, and the trained air conditioning energy consumption monitoring model is verified for accuracy using a model accuracy algorithm. When the calculation result is greater than 0.95, it indicates that the accuracy of the air conditioning energy consumption monitoring model meets the requirements. When the calculation result is not greater than 0.95, it indicates that the accuracy of the customer's air conditioning energy consumption monitoring model does not meet the requirements and the air conditioning energy consumption monitoring model needs to be optimized and adjusted.

7. According to the Internet of Things technology-based classroom air conditioning power saving management system of claim 1, it is characterized by: The air conditioner energy consumption monitoring unit (400) further comprises an air conditioner energy consumption data acquisition module (403) and an air conditioner abnormal energy consumption detection module (404), wherein the air conditioner energy consumption data acquisition module (403) is used to acquire real-time energy consumption data of an air conditioner in a self-study classroom in operation, and to add a timestamp tag to the acquired real-time energy consumption data of the air conditioner, and the air conditioner abnormal energy consumption detection module (404) is used to perform an air conditioner abnormal energy consumption detection operation based on the air conditioner real-time energy consumption data, and to inspect and process an air conditioner with abnormal energy consumption based on the detection result and the timestamp tag of the air conditioner real-time energy consumption data.

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