Controller Based on Internet of Things and Control Method for Air Conditioning System

Abstract

The present invention provides an Internet of Things-based controller and a control method for an air conditioning system. The controller includes: an induction acquisition module that uses sensors to obtain induction data and gets induction acquisition data; a cloud computing module that obtains the status data information of the on-site control module, and uses sample data combined with the status data information to optimize and learn the control model to obtain an optimized control model; an on-site control module that determines a regulation strategy based on the induction acquisition data according to the optimized control model; and a monitoring and management module that performs status monitoring and management according to the status data information. The present invention integrates Internet technology and uses a cloud computing module to optimize and learn the control model, can realize the optimization of the control model without manual participation, saves labor consumption, improves the optimization efficiency of the control model, and thus provides a guarantee for control adjustment.

Description

Technical Field

[0001] The present invention relates to the field of electronic control technology, and particularly to a controller based on the Internet of Things and a control method for an air conditioning system. Background Art

[0002] Air conditioners belong to consumer electronic products, with a wide range of user groups and application scenarios. They can adjust the indoor temperature and humidity, improve the comfortable air quality, and ensure people's comfort and health. With the development of society, people are becoming more and more dependent on air conditioners, requiring them to not only provide a comfortable indoor environment, but also have higher energy efficiency performance and intelligent management capabilities. With the popularization of intelligent technologies, more and more controllers are applied in various aspects.

[0003] At present, the performance of the controller is limited. Usually, manual optimization and adjustment of the control model are required, which not only has low optimization and adjustment efficiency and low accuracy, but also requires a lot of time. Therefore, the present invention proposes a controller based on the Internet of Things and a control method for an air conditioning system, which uses a cloud computing module to integrate Internet technology for optimizing and learning the control model, and can realize the optimization of the control model without manual participation, saving labor consumption, improving the optimization efficiency of the control model, and thus providing guarantee for control adjustment. Summary of the Invention

[0004] The purpose of the present invention is to provide a controller based on the Internet of Things and a control method for an air conditioning system to solve the problems raised in the above background art.

[0005] To achieve the above purpose, the present invention provides the following technical solution: A controller based on the Internet of Things, comprising: an induction acquisition module, a field control module, a cloud computing module, and a monitoring and management module;

[0006] The induction acquisition module is used to obtain induction data by using sensors to obtain induction acquisition data;

[0007] The cloud computing module is used to obtain the status data information of the field control module, and optimize and learn the control model by using sample data combined with the status data information to obtain an optimized control model;

[0008] The field control module is used to determine a regulation strategy based on the optimized control model according to the induction acquisition data combined with the control operation information;

[0009] The monitoring and management module is used to perform status monitoring and management according to the status data information.

[0010] Further, the induction acquisition module includes a plurality of sensors. When using sensors to obtain induction data, the target area for monitoring and acquisition is determined, the positions of the sensors are deployed according to the target area, and the acquisition self-control information of the sensors is determined. Then, according to the acquisition self-control information, the sensors are used to monitor and collect environmental factors in the target area to obtain environmental factor induction acquisition data.

[0011] Further, the cloud computing module includes: a data acquisition unit, a learning and training unit, an intelligent analysis unit, and an optimization and adjustment unit;

[0012] The data acquisition unit is used to receive the status data information of the on-site control module and obtain sample data based on the status data information;

[0013] The learning and training unit is used to optimize and learn the control model by using the sample data in combination with the status data information to determine the optimized control model;

[0014] The intelligent analysis unit is used to perform intelligent analysis on the status data information to determine the control monitoring information;

[0015] The optimization and adjustment unit is used to determine the optimization and adjustment information according to the optimized control model.

[0016] Further, it is characterized in that the learning and training unit uses the sample data in combination with the status data information to optimize and learn the control model, including:

[0017] Obtain the current model parameter data of the control model according to the status data information according to a preset period;

[0018] Determine the current control model based on the current model parameter data;

[0019] Use the current control model to perform model training on the sample data to obtain sample training data;

[0020] Perform model analysis and evaluation on the control model according to the sample training data to obtain model analysis data;

[0021] Combine the model standard to analyze the model analysis data to determine whether the current control model needs to be optimized and adjusted to obtain the model analysis result;

[0022] Perform model parameter optimization analysis according to the model analysis result to obtain the model parameter optimization value; when the model analysis result is that the current control model needs to be optimized and adjusted, combine the current model to perform optimization analysis on the current model parameter data to determine the model parameter optimization value;

[0023] Determine an optimized control model based on the optimized values of the model parameters, verify the optimized control model, analyze whether the optimized control model is the optimal control model, and obtain the verification and analysis results;

[0024] Determine the final optimized control model according to the verification and analysis results; when the verification and analysis result is that the optimized control model is the optimal control model, the optimized control model is the final optimized control model; when the verification and analysis result is that the optimized control model is not the optimal control model, continue the optimization analysis based on the optimized control model until the optimized control model is the optimal control model.

[0025] Furthermore, the intelligent analysis unit performs intelligent analysis on the status data information, including:

[0026] Perform first information analysis on the status data information to determine the control status and obtain the first analysis result;

[0027] Determine the monitoring information mode according to the first analysis result. When the first analysis result is that the control status is the closed state, retrieve the first monitoring information mode, and determine the monitoring display information based on the first monitoring information mode combined with the control closed state. When the first analysis result is that the control status is the open state, retrieve the second monitoring information mode, perform second information recognition and extraction on the status data information to obtain the status data recognition information, and then generate the control display information for the second monitoring information mode according to the status data recognition information to obtain the control display information.

[0028] Furthermore, the optimization and adjustment unit determines the optimization and adjustment information according to the optimized control model, including:

[0029] Analyze the optimized control model to judge whether optimization and adjustment are required, and obtain the preliminary analysis and judgment result;

[0030] Retrieve the optimized control instruction information according to the preliminary analysis and judgment result;

[0031] Perform effective adjustment information recognition on the optimized control model to obtain the target adjustment information;

[0032] Adjust and improve the optimized control instruction information according to the target adjustment information to obtain the optimization and adjustment information.

[0033] Furthermore, the on-site control module includes: a control operation unit, a control adjustment unit, and a control display unit;

[0034] The control operation unit is used to obtain control operation information based on quick control operations;

[0035] The control and adjustment unit is configured to perform control model analysis in combination with the sensed and collected data according to the control operation information, determine the control adjustment instruction, and perform a regulation plan for the control adjustment instruction to obtain a regulation strategy;

[0036] The control and display unit is configured to determine the control display information for the control and adjustment unit and present the information for the control display information.

[0037] Further, the controller further includes: an active query module; the active query module obtains a query request instruction by making a query request for a target customer, and then the cloud computing module determines query information according to the query request instruction to obtain target query information and provides feedback for the target query information.

[0038] Further, the monitoring and management module includes: a status monitoring unit, a ledger management unit, and a user management unit;

[0039] The status monitoring unit is configured to perform status monitoring according to the status data information;

[0040] The ledger management unit is configured to perform control status analysis according to the status data information, and perform energy calculation in combination with the loss according to the control status to obtain an energy consumption analysis result;

[0041] The user management unit shown is configured to perform user management for customers, verify the target customer, and present feedback for the target query information when the target customer is verified.

[0042] A control method for an air conditioning system controls the air conditioning system based on the above controller. The controller is connected to the air conditioning system, a regulation strategy is determined based on the controller, and then the air conditioning main unit performs control adjustment according to the regulation strategy.

[0043] The present invention combines Internet technology, adopts a cloud computing module to optimize the control model of the on-site control module, improves the computing power of the on-site control module, can realize the optimization and adjustment of the control model without manual participation, saves labor consumption, improves the control model optimization efficiency, and further provides guarantee for the control adjustment of the on-site control module.

[0044] Other features and advantages of the present invention will be described in the following specification, and, in part, will be obvious from the specification, or will be understood by implementing the present invention. The objectives and other advantages of the present invention can be achieved and obtained by the structure specifically pointed out in the written specification and the drawings.

[0045] The technical solution of the present invention will be further described in detail below through the drawings and embodiments. Description of the Drawings

[0046] The accompanying drawings are used to provide a further understanding of the present invention and constitute a part of the specification. Together with the embodiments of the present invention, they are used to explain the present invention and do not constitute a limitation to the present invention. In the accompanying drawings:

[0047] Figure 1 It is a schematic diagram of a controller according to the present invention;

[0048] Figure 2 It is a schematic diagram of the cloud computing module in the controller according to the present invention;

[0049] Figure 3 It is a schematic diagram of the steps of the learning and training unit of the cloud computing module in the controller according to the present invention;

[0050] Figure 4 It is a schematic diagram of the steps of the intelligent analysis unit of the cloud computing module in the controller according to the present invention;

[0051] Figure 5 It is a schematic diagram of the steps of the optimization and adjustment unit of the cloud computing module in the controller according to the present invention;

[0052] Figure 6 It is a schematic diagram of the on-site control module in the controller according to the present invention;

[0053] Figure 7 It is another schematic diagram of the controller according to the present invention;

[0054] Figure 8 It is a schematic diagram of the monitoring and management module in the controller according to the present invention;

[0055] Figure 9 It is a connection schematic diagram of the control method for an air conditioning system according to the present invention. Detailed implementation manners

[0056] The following describes the preferred embodiments of the present invention with reference to the accompanying drawings. It should be understood that the preferred embodiments described herein are only used to illustrate and explain the present invention and are not used to limit the present invention.

[0057] As Figure 1 shown, the embodiments of the present invention provide a controller based on the Internet of Things, including: an induction and acquisition module, an on-site control module, a cloud computing module, and a monitoring and management module;

[0058] The induction and acquisition module is used to obtain induction data by using sensors to obtain induction acquisition data;

[0059] The cloud computing module is used to obtain the status data information of the on-site control module, and optimize and learn the control model by using sample data in combination with the status data information to obtain an optimized control model;

[0060] The on-site control module is used to determine a regulation strategy based on the optimized control model by combining the sensed acquisition data with the control operation information;

[0061] The monitoring and management module is used to perform status monitoring and management based on the status data information.

[0062] In the above technical solution, the sensed acquisition module is connected to the on-site control module, the on-site control module is also connected to the cloud computing module, and the monitoring and management module is connected to the cloud computing module.

[0063] In the above technical solution, during the control process of the controller, the sensed acquisition module uses sensors to obtain sensed data to get the sensed acquisition data. The on-site control module determines the regulation strategy based on the sensed acquisition data by combining the control operation information based on the optimized control model. At the same time, the on-site control module sends the control status data information to the cloud computing module. The cloud computing module uses the sample data and the status data information to perform optimized learning for the control model to obtain the optimized control model, and performs optimized adjustment feedback for the on-site control module according to the optimized control module, so that the on-site control module performs control adjustment according to the optimized control model. And the cloud computing module also performs intelligent analysis based on the status data information, and then the monitoring and management module performs status monitoring and management for the intelligent analysis result.

[0064] In the above technical solution, the status data information refers to the control status data information.

[0065] In the above technical solution, the sensed data refers to the associated factors for control, such as temperature, humidity, etc. in environmental factors.

[0066] The above technical solution combines Internet technology and uses a cloud computing module to enable the on-site control module to perform optimized learning of the control model while performing control adjustment, improving the performance of the controller. It can perform optimized control of the control model through optimized learning without manual participation, saving manpower consumption, reducing the time consumed for optimized learning of the control model, and improving the efficiency of control model optimization, providing guarantee for the control adjustment of the on-site control module. The sensed acquisition module is used to sense and acquire environmental data, enabling control adjustment to be combined with the sensed acquisition data when adjusting the controller, making the control adjustment result adapt to the actual factors and ensuring people's comfort and health. The cloud computing module is used to optimize the control model of the on-site control module, integrating the Internet of Things technology into the on-site control module, improving the computing power of the on-site control module, enabling no manual adjustment of the control model, saving manpower consumption, improving the control model adjustment efficiency, and providing guarantee for the control adjustment of the on-site control module. The monitoring and management module can monitor the control status, making the control status data information transparent and enabling people to understand the status of the controller.

[0067] In an embodiment provided by the present invention, the induction acquisition module includes multiple sensors. When using sensors to obtain induction data, the target area to be monitored and collected is determined, the positions of the sensors are deployed according to the target area, and the acquisition self-control information of the sensors is determined. Then, according to the acquisition self-control information, the sensors are used to monitor and collect environmental factors in the target area, and environmental factor induction acquisition data is obtained.

[0068] In the above technical solution, there are various types of sensors. For example, temperature sensors, humidity sensors, etc., and multiple sensors of each type are provided.

[0069] In the above technical solution, the acquisition self-control information is the control information for the sensors. For example, induction time, induction frequency, induction angle, etc.

[0070] In the above technical solution, the automatic monitoring of the target area can be realized through the sensors, so that when determining the regulation strategy, the control adjustment can be combined with the environmental factor induction acquisition data, and then the control adjustment result can be adapted to the environment, thereby improving the comfort of people in the target area and providing guarantee for people's health.

[0071] As Figure 2 shown, in an embodiment provided by the present invention, the cloud computing module includes: a data acquisition unit, a learning and training unit, an intelligent analysis unit, and an optimization and adjustment unit;

[0072] The data acquisition unit is used to receive the status data information of the on-site control module and obtain sample data based on the status data information;

[0073] The learning and training unit is used to optimize and learn the control model by using the sample data in combination with the status data information to determine the optimized control model;

[0074] The intelligent analysis unit is used to perform intelligent analysis on the status data information to determine the control monitoring information;

[0075] The optimization and adjustment unit is used to determine the optimization and adjustment information according to the optimized control model.

[0076] In the above technical solution, the learning and training unit is respectively connected to the data acquisition unit and the optimization and adjustment unit, and the data acquisition unit is also connected to the intelligent analysis unit.

[0077] In the above technical solution, there are multiple sample data. The status data information of the received on-site control module can be used as part of the sample data, or sample data can be directly imported or obtained.

[0078] In the above technical solution, when performing intelligent analysis on the status data information, AI technology is used to automatically analyze the status data information to obtain an intelligent analysis result and obtain control monitoring information.

[0079] In the above technical solution, when the data acquisition unit obtains sample data based on the status data information, the status data information of the received on-site control module is used as sample data, and the sample type analysis is performed on the status data information of the received on-site control module to determine the current number of sample types, and then the total number of sample data is obtained. The total data volume of the sample data is divided to obtain a first sample number and a second sample number. Among them, the average value of the first sample number is greater than the second sample number. Then, the current data of the sample type is combined with the first sample number to obtain target data information according to the sample type, and the obtained data information is combined with the status data information of the received on-site control module to obtain a first sample data set. At the same time, target data information is randomly obtained according to the second sample number to obtain a second sample data set, so as to obtain sample data based on the first sample data set and the second sample data set.

[0080] The above technical solution realizes a large amount of calculation and analysis through the cloud computing module, which can not only realize the determination of monitoring information, but also realize the optimization learning of the control model, improve the accuracy of the control model, and further enable the on-site control module to better adjust based on the control model.

[0081] As Figure 3 shown, in an embodiment provided by the present invention, the learning and training unit uses sample data combined with status data information to perform optimization learning on the control model, including:

[0082] S1. Obtain the current model parameter data of the control model according to the status data information at a preset cycle;

[0083] S2. Determine the current control model based on the current model parameter data;

[0084] S3. Use the current control model to perform model training on the sample data to obtain sample training data;

[0085] S4. Perform model analysis and evaluation on the control model according to the sample training data to obtain model analysis data;

[0086] S5. Combine the model standard to analyze the model analysis data to determine whether the current control model needs to be optimized and adjusted, and obtain a model analysis result;

[0087] S6. Optimize and analyze the model parameters based on the model analysis results to obtain the optimized values of the model parameters; when the model analysis result indicates that the current control model needs to be optimized and adjusted, perform optimization analysis on the current model parameters data in combination with the current model to determine the optimized values of the model parameters.

[0088] S7. Determine the optimized control model based on the optimized values of the model parameters, and verify the optimized control model to analyze whether the optimized control model is the optimal control model, and obtain the verification analysis result.

[0089] S8. Determine the final optimized control model according to the verification analysis result; when the verification analysis result indicates that the optimized control model is the optimal control model, the optimized control model is the final optimized control model; when the verification analysis result indicates that the optimized control model is not the optimal control model, continue the optimization analysis based on the optimized control model until the optimized control model is the optimal control model.

[0090] In the above technical solution, the preset period can be adjusted according to requirements.

[0091] In the above technical solution, when the model analysis result indicates that the current control model does not need to be optimized and adjusted, there is no need to continue any response.

[0092] In the above technical solution, the model analysis data includes: model analysis information and model evaluation information. Analyze the model analysis data in combination with the model standard, including: perform the first information recognition on the model analysis data to obtain the model evaluation information, and at the same time disassemble the model standard into the first standard information and the second standard information, where the first standard information is the analysis and judgment standard for the model evaluation information, and the second standard information is the analysis and judgment standard for the model analysis information; analyze and judge according to the model evaluation information in combination with the first standard information to determine whether the current control model needs to be optimized and adjusted. When the current control model needs to be optimized and adjusted, obtain the model analysis result, and the model analysis result is that the current control model needs to be optimized and adjusted. When the current control model does not need to be optimized and adjusted, match the model analysis information in the second standard information, and analyze the model analysis information in combination with the corresponding second standard information according to the matching result to judge whether the model analysis information meets the corresponding second standard information. When there is model analysis information that does not meet the corresponding second standard information, obtain the model analysis result, and the model analysis result is that the current control model needs to be optimized and adjusted. When all the model analysis information meets the corresponding second standard information, obtain the model analysis result, and the model analysis result is that the current control model does not need to be optimized and adjusted.

[0093] The above technical solution realizes the periodic optimization learning of the control model through a preset period, enabling timely improvement of the control model, ensuring the adjustment based on the control model, and through model analysis and evaluation, clarifying the current situation of the control model, enabling asynchronous optimization analysis when optimization adjustment is required, ensuring the effectiveness of the optimization analysis, and reducing unnecessary time waste.

[0094] As Figure 4 shown, in an embodiment provided by the present invention, the intelligent analysis unit performs intelligent analysis on the status data information, including:

[0095] A1. Perform the first information analysis on the status data information to determine the control status and obtain the first analysis result;

[0096] A2. Determine the monitoring information mode according to the first analysis result. When the first analysis result is that the control status is the closed state, retrieve the first monitoring information mode, and determine the monitoring display information based on the first monitoring information mode in combination with the control closed state. When the first analysis result is that the control status is the open state, retrieve the second monitoring information mode, and perform the second information recognition and extraction on the status data information to obtain the status data recognition information, and then generate the control display information for the second monitoring information mode according to the status data recognition information to obtain the control display information.

[0097] In the above technical solution, the first information analysis includes: the control status is the closed state and the control status is the open state.

[0098] In the above technical solution, the second information refers to the control information.

[0099] In the above technical solution, the first monitoring information mode and the second monitoring information mode are two modes with different display contents.

[0100] The above technical solution realizes the intelligent analysis of the status data information through the intelligent analysis unit, enabling the determination of the control display information from the status data information, thereby making the control status information transparent, and through the first monitoring information mode and the second monitoring information mode, it can ensure the comprehensiveness of the status data information while reducing the redundancy of irrelevant information, enabling relevant personnel to better understand the control status from the control display information.

[0101] As Figure 5 shown, in an embodiment provided by the present invention, the optimization adjustment unit determines the optimization adjustment information according to the optimized control model, including:

[0102] B1. Analyze the optimized control model, judge whether optimization adjustment is required, and obtain the preliminary analysis and judgment result;

[0103] B2. Retrieve the optimized control instruction information according to the preliminary analysis and judgment result;

[0104] B3. Identify the effective adjustment information for the optimized control model to obtain the target adjustment information;

[0105] B4. Adjust and improve the optimized control instruction information according to the target adjustment information to obtain the optimized adjustment information.

[0106] In the above technical solution, when adjusting and improving the optimized control instruction information according to the target adjustment information, the target adjustment information is matched with the optimized control instruction information to determine the position of the target adjustment information, lock the target position, and use the target adjustment information to fill or replace the data information according to the target position.

[0107] In the above technical solution, when analyzing the optimized control model to determine whether optimization adjustment is required, the optimized control model is compared with the control model before optimization, including: performing an overall comparative analysis on the optimized control model and the control model before optimization to determine whether the model framework has changed, obtaining the first judgment result. When the first judgment result is that the model framework has changed, the preliminary analysis and judgment result is that optimization adjustment is required. When the first judgment result is that the model framework has not changed, the parameter comparative analysis is performed on the optimized control model and the control model before optimization according to the steps to determine whether the step parameters have changed, obtaining the second judgment result. Then, statistical analysis is performed on the second judgment result. When the second judgment results of all steps are that the step parameters have not changed, the preliminary analysis and judgment result is that optimization adjustment is not required. When there is a second judgment result of a step that the step parameters have changed, the preliminary analysis and judgment result is that optimization adjustment is required.

[0108] In the above technical solution, the effective adjustment information refers to the change information existing in the current optimized control model compared with the optimized control model obtained by the previous optimization learning.

[0109] In the above technical solution, when retrieving the optimized control instruction information according to the preliminary analysis and judgment result, the optimized control instruction information is retrieved only when the preliminary analysis and judgment result is that optimization adjustment is required, and no response is required when optimization adjustment is not required.

[0110] The above technical solution determines whether optimization and adjustment are required, so that subsequent steps are only carried out when optimization and adjustment are needed, avoiding resource waste caused by ineffective analysis. By retrieving optimization control instruction information, adjustment and improvement are carried out based on the existing retrieved optimization control instruction information, improving the determination efficiency of optimization adjustment information. And by effectively identifying adjustment information for the optimization control model, adjustment and improvement can be carried out according to the target adjustment information, reducing the redundancy of irrelevant information. This can not only ensure the result feedback of optimization learning, but also improve the data transmission efficiency between the cloud computing module and the on-site control module.

[0111] As Figure 6 shown, in an embodiment provided by the present invention, the on-site control module includes: a control operation unit, a control adjustment unit, and a control display unit;

[0112] The control operation unit is used to obtain control operation information based on quick control operations;

[0113] The control adjustment unit is used to analyze the control model according to the control operation information combined with the sensed and collected data, determine the control adjustment instruction, and plan the regulation according to the control adjustment instruction to obtain the regulation strategy;

[0114] The control display unit is used to determine control display information for the control adjustment unit and present the information for the control display information.

[0115] In the above technical solution, the control operation unit includes a plurality of quick operation buttons, such as: start, stop, upward setting, downward setting, confirmation, etc.

[0116] In the above technical solution, the control display information is obtained based on the control adjustment result, including: operation mode, supply air temperature, return air temperature, set temperature, etc.

[0117] In the above technical solution, when the control adjustment unit analyzes the control model according to the control operation information combined with the sensed and collected data, it identifies the control operation information, determines the type of the control operation, judges whether the control operation is a control adjustment operation. When the control operation is a control adjustment operation, key information is extracted from the control operation information to obtain control adjustment target information, and the control adjustment target information is combined with the sensed and collected data to determine the control adjustment instruction based on the control model.

[0118] In the above technical solution, when formulating a regulation plan for a control adjustment instruction, the adjustment quantity is determined for the control adjustment instruction. When the adjustment quantity is 2, the regulation order of the control adjustment instruction is determined according to the priority to obtain a regulation strategy. When the adjustment quantity is greater than 2, the control adjustment instruction is disassembled in pairs to obtain multiple regulation sub-combinations. The internal order is determined according to the priority in the adjustment sub-combination to obtain a regulation sub-queue. Then, sequence analysis is performed on the regulation sub-queue to obtain multiple regulation plan sequences. Next, rationality analysis and screening are performed on the multiple regulation plan sequences, and the regulation strategy is determined according to the analysis and screening results.

[0119] In the above technical solution, through the on-site control module, not only can the regulation strategy determination based on on-site operations be realized, but also the control adjustment results of the regulation strategy can be visually displayed. Through the control operation unit, it is possible to directly perform quick control operations, providing convenience for users. Through the control adjustment unit, the determination of the regulation strategy is realized, enabling timely control response according to the control operation information, improving the efficiency of performance regulation, and enabling the target object to better meet people's needs. Through the control display unit, the control adjustment results are visualized, enabling relevant personnel to more intuitively clarify the change phenomena caused by the current control adjustment.

[0120] As Figure 7 shown, in an embodiment provided by the present invention, the controller further includes: an active query module; the active query module obtains a query request for a target customer to obtain a query request instruction, and then the cloud computing module determines query information according to the query request instruction to obtain target query information, and feeds back the target query information.

[0121] In the above technical solution, when the active query module obtains a query request for a target customer, it obtains the identity information of the target customer.

[0122] In the above technical solution, the query request includes a query requirement and the identity information of the target customer.

[0123] In the above technical solution, through the active query module, the target customer can query the relevant information of the control at any time and place, realizing the interaction with the target customer and providing convenience for the target customer.

[0124] As Figure 8 shown, in an embodiment provided by the present invention, the monitoring and management module includes: a status monitoring unit, an account management unit, and a user management unit;

[0125] The status monitoring unit is used to perform status monitoring according to the status data information;

[0126] The ledger management unit is used to analyze the control status based on the status data information, and calculate the energy consumption by combining the control status with the loss to obtain the energy consumption analysis result;

[0127] The user management unit shown is used to manage users for customers, verify the target customer, and present feedback for the target query information when the target customer is verified.

[0128] In the above technical solution, when the target customer verification fails, the user management unit issues a notice and reminder for the target customer.

[0129] In the above technical solution, the energy calculation includes: start time, power consumption, etc.

[0130] In the above technical solution, the monitoring and management module can not only monitor the control status and visually display the control status, but also achieve integrated management. While performing ledger management, it can also achieve user management. The status monitoring unit displays the status monitoring in real time, enabling relevant personnel to better monitor the control and status. Through the ledger management unit, not only can the start time management of the control be clarified, and it can be known how long the current control has been started, but also the current power consumption of the controller can be clarified, so as to generally understand the energy consumption of the controller. The user management unit ensures the security of data information, so that only the target customers who pass the verification can obtain the target query information based on the query request, ensuring the right of active query and avoiding the leakage of data resources.

[0131] Such as Figure 9 As shown, the embodiment of the present invention provides a control method for an air-conditioning system. Based on any one of the above-mentioned controllers, the air-conditioning system is controlled. The controller is connected to the air-conditioning system, and a regulation strategy is determined based on the controller. Then, the air-conditioning host performs control adjustment according to the regulation strategy.

[0132] The above technical solution integrates the Internet of Things-based controller into the air-conditioning control system, enabling the control of the air-conditioning system through the Internet of Things-based controller, and enabling the air-conditioning host to perform control adjustment according to the regulation strategy determined by the Internet of Things-based controller, improving the control performance of the air-conditioning system, enabling the air-conditioning system to perform control according to a more accurate regulation strategy while controlling, and improving the accuracy of air-conditioning system control.

[0133] Those skilled in the art should understand that the first and second in the present invention only refer to different application stages.

[0134] Other embodiments of the present disclosure will be readily apparent to those skilled in the art upon consideration of the specification and practice of the disclosure herein. This application is intended to cover any variations, uses, or adaptations of the present disclosure that follow the general principles of the present disclosure and include known common general knowledge or conventional technical means in the technical field not disclosed herein. The specification and examples are only to be considered as exemplary, and the true scope and spirit of the present disclosure are pointed out by the following claims.

[0135] It should be understood that the present disclosure is not limited to the exact structures described above and shown in the drawings, and various modifications and changes can be made without departing from its scope. The scope of the present disclosure is only limited by the appended claims.

Claims

1. A controller based on the Internet of Things, characterized in that: include: Sensing acquisition module, field control module, cloud computing module and monitoring management module; The sensing acquisition module is used to acquire sensing data using a sensor to obtain sensing acquisition data; The cloud computing module is used to obtain the status data information of the field control module, and optimize the control model by using the sample data combined with the status data information to obtain the optimized control model; The field control module is used to determine the control strategy based on the optimized control model according to the sensing collected data combined with the control operation information, and includes: a control operation unit, a control adjustment unit and a control display unit; the control operation unit is used to obtain the control operation information based on the quick control operation; the control adjustment unit is used to perform control model analysis according to the control operation information combined with the sensing collected data, determine the control adjustment instructions, and perform control planning according to the control adjustment instructions to obtain the control strategy; the control display unit is used to determine the control display information for the control adjustment unit, and present the control display information; wherein, when the control adjustment unit performs control model analysis according to the control operation information combined with the sensing collected data, it identifies the control operation information, determines the type of control operation, and judges whether the control operation is Control adjustment operation, when the control operation is a control adjustment operation, key information is extracted from the control operation information to obtain control adjustment target information, the control adjustment target information is combined with the sensing acquisition data to determine the control adjustment instruction based on the control model, and when the control planning is performed according to the control adjustment instruction, the adjustment quantity is determined for the control adjustment instruction, when the adjustment quantity is 2, the control order of the control adjustment instruction is determined according to the priority to obtain the control strategy, when the adjustment quantity is greater than 2, the control adjustment instruction is disassembled in pairs to obtain multiple control sub-combinations, the order in the adjustment sub-combinations is determined according to the priority to obtain the control sub-queue, and then the control sub-queue is sequenced and multiple control planning sequences are obtained, and then the rationality analysis and screening are performed on the multiple control planning sequences, and the control strategy is determined according to the analysis and screening results; The monitoring and management module is used to perform status monitoring and management according to status data information.

2. The controller according to claim 1, characterized in that: The sensing acquisition module includes multiple sensors. When using sensors to acquire sensing data, the target area for monitoring and acquisition is determined, the position of the sensor is deployed according to the target area, and the sensor's acquisition automatic control information is determined. Then, according to the acquisition automatic control information, environmental factors are monitored and collected for the target area through the sensor to obtain environmental factor sensing acquisition data.

3. The controller according to claim 1, characterized in that: The cloud computing module includes: a data acquisition unit, a learning and training unit, an intelligent analysis unit and an optimization and adjustment unit; The data acquisition unit is used to receive status data information of the field control module and acquire sample data based on the status data information; The learning and training unit is used to optimize the control model by using the sample data combined with the state data information to determine the optimized control model; The intelligent analysis unit is used to perform intelligent analysis on the status data information to determine the control monitoring information; The optimization adjustment unit is used to determine the optimization adjustment information according to the optimization control model.

4. The controller according to claim 3, characterized in that: The learning and training unit uses sample data combined with state data information to perform optimization learning on the control model, including: Acquiring current model parameter data of the control model according to the state data information at a preset period; determining a current control model based on current model parameter data; Using the current control model to perform model training on the sample data to obtain sample training data; Perform model analysis and evaluation on the control model according to the sample training data to obtain model analysis data; Analyze the model analysis data in combination with the model standard to determine whether the current control model needs to be optimized and adjusted, and obtain the model analysis results; Perform model parameter optimization analysis based on the model analysis results to obtain the model parameter optimization values; when the model analysis results indicate that the current control model needs to be optimized and adjusted, perform optimization analysis on the current model parameter data in combination with the current model to determine the model parameter optimization values; Determine the optimized control model based on the optimized values ​​of the model parameters, verify the optimized control model, analyze whether the optimized control model is the optimal control model, and obtain the verification analysis results; The final optimized control model is determined according to the verification analysis results; when the verification analysis result shows that the optimized control model is the optimal control model, the optimized control model is the final optimized control model; when the verification analysis result shows that the optimized control model is not the optimal control model, the optimization analysis is continued based on the optimized control model until the optimized control model is the optimal control model.

5. The controller according to claim 3, characterized in that: The intelligent analysis unit performs intelligent analysis on the status data information, including: Performing a first information analysis on the state data information, determining a control state, and obtaining a first analysis result; The monitoring information mode is determined according to the first analysis result. When the first analysis result shows that the control state is in a closed state, the first monitoring information mode is called, and the monitoring display information is determined based on the first monitoring information mode combined with the control closed state. When the first analysis result shows that the control state is in an open state, the second monitoring information mode is called, and the second information is identified and extracted for the state data information to obtain the state data identification information. Then, the control display information is generated for the second monitoring information mode according to the state data identification information to obtain the control display information.

6. The controller according to claim 3, characterized in that: The optimization adjustment unit determines the optimization adjustment information according to the optimization control model, including: Analyze and optimize the control model, determine whether optimization adjustment is needed, and obtain preliminary analysis and judgment results; Retrieve optimized control instruction information based on preliminary analysis and judgment results; Identify effective adjustment information for the optimization control model and obtain target adjustment information; The optimized control instruction information is adjusted and improved according to the target adjustment information to obtain the optimized adjustment information.

7. The controller according to claim 1, characterized in that: The controller also includes: an active query module; the active query module obtains query requests for target customers and obtains query request instructions, and then the cloud computing module determines query information according to the query request instructions, obtains target query information, and provides feedback on the target query information.

8. The controller according to claim 7, characterized in that: The monitoring management module includes: a status monitoring unit, a ledger management unit and a user management unit; The state monitoring unit is used to perform state monitoring according to the state data information; The ledger management unit is used to perform control status analysis according to the status data information, and calculate energy according to the control status combined with the loss to obtain energy consumption analysis results; The user management unit shown is used to perform user management on customers, verify target customers, and present feedback on target query information when the target customers are verified.

9. A control method for an air conditioning system, based on the controller according to any one of claims 1 to 8, wherein: The controller is connected to the air conditioning system, a control strategy is determined based on the controller, and then the air conditioning host performs control adjustments according to the control strategy.

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