Controller based on Internet of Things and control method for air conditioning system

Abstract

The invention provides a controller based on the Internet of Things and a control method for an air conditioning system, and the controller comprises an induction collection module which obtains induction data through a sensor to obtain induction collection data; the cloud computing module obtains the state data information of the field control module, and performs optimization learning on the control model by combining the sample data with the state data information to obtain an optimization control model; the field control module determines a regulation and control strategy based on an optimization control model according to the induction collection data; and the monitoring management module carries out state monitoring and management according to the state data information. According to the invention, the cloud computing module is adopted to carry out control model optimization learning by fusing the Internet technology, control model optimization can be realized without manual participation, manpower consumption is saved, the control model optimization efficiency is improved, and a guarantee is provided for control adjustment.

Description

Technical Field

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

[0002] Air conditioners are consumer electronic products that are used by a wide range of users and applications. They adjust indoor temperature and humidity, improve comfortable air quality, and ensure people's comfort and health. With the development of society, people are increasingly dependent on air conditioners, requiring them to not only provide a comfortable indoor environment, but also have higher energy efficiency and intelligent management capabilities. With the popularization of intelligent technology, more and more controllers are applied to various aspects.

[0003] At present, the performance of the controller is limited, and manual optimization and adjustment of the control model is usually required. Not only is the optimization and adjustment efficiency low, the accuracy is also low, and it also takes 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 to optimize and learn the control model. The control model can be optimized without manual participation, which saves manpower consumption, improves the optimization efficiency of the control model, and provides a guarantee for the control adjustment. Summary of the invention

[0004] The object 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 technology.

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

[0006] The sensing acquisition module is used to acquire sensing data using a sensor to obtain sensing acquisition data;

[0007] 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;

[0008] The field control module is used to determine the control strategy based on the optimization control model according to the sensor collection data combined with the control operation information;

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

[0010] Furthermore, 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.

[0011] Furthermore, 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 status data information of the field control module and acquire sample data based on the status data information;

[0013] 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;

[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 adjustment unit is used to determine the optimization adjustment information according to the optimization control model.

[0016] Furthermore, it is 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:

[0017] Acquiring current model parameter data of the control model according to the state data information at a preset period;

[0018] determining a current control model based on current model parameter data;

[0019] Using 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] 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;

[0022] 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;

[0023] 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;

[0024] 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.

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

[0026] Performing a first information analysis on the state data information, determining a control state, and obtaining a first analysis result;

[0027] 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.

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

[0029] Analyze and optimize the control model, determine whether optimization adjustment is needed, and obtain preliminary analysis and judgment results;

[0030] Retrieve optimized control instruction information based on preliminary analysis and judgment results;

[0031] Identify effective adjustment information for the optimization control model and obtain target adjustment information;

[0032] The optimized control instruction information is adjusted and improved according to the target adjustment information to obtain the optimized adjustment information.

[0033] Further, the field 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 the shortcut control operation;

[0035] The control adjustment unit is used to perform control model analysis according to the control operation information combined with the sensor collection data, determine the control adjustment instruction, and perform control planning according to the control adjustment instruction to obtain the control strategy;

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

[0037] Furthermore, 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.

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

[0039] The state monitoring unit is used to perform state monitoring according to the state data information;

[0040] 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;

[0041] 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.

[0042] A control method for an air conditioning system controls the air conditioning system based on the above-mentioned controller, connects the controller to the air conditioning system, determines a control strategy based on the controller, and then the air conditioning host performs control adjustment according to the control strategy.

[0043] The present invention combines Internet technology and adopts a cloud computing module to optimize the control model of the field control module, thereby improving the computing power of the field control module. The control model can be optimized and adjusted without human intervention, saving manpower consumption and improving the optimization efficiency of the control model, thereby providing a guarantee for the control adjustment of the field control module.

[0044] Other features and advantages of the present invention will be described in the following description, and partly become apparent from the description, or understood by practicing the present invention. The purpose and other advantages of the present invention can be realized and obtained by the structures particularly pointed out in the written description and the accompanying drawings.

[0045] The technical solution of the present invention is further described in detail below through the accompanying drawings and embodiments. BRIEF 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 of the present invention. In the accompanying drawings:

[0047] Figure 1 A schematic diagram of the controller of the present invention;

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

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

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

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

[0052] Figure 6 A schematic diagram of a field control module in a controller according to the present invention;

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

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

[0055] Fig. 9 It is a connection diagram of the control method for an air conditioning system according to the present invention. DETAILED DESCRIPTION

[0056] The preferred embodiments of the present invention are described below in conjunction with 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] like Figure 1 As shown, an embodiment of the present invention provides a controller based on the Internet of Things, including: a sensing acquisition module, a field control module, a cloud computing module and a monitoring management module;

[0058] The sensing acquisition module is used to acquire sensing data using a sensor to obtain sensing acquisition data;

[0059] 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;

[0060] The field control module is used to determine the control strategy based on the optimization control model according to the sensor collection data combined with the control operation information;

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

[0062] In the above technical solution, the sensing acquisition module is connected to the field control module, the field control module is also connected to the cloud computing module, and the monitoring management module is connected to the cloud computing module.

[0063] In the above technical solution, during the control process, the controller uses the sensor to acquire sensing data through the sensing acquisition module to obtain sensing acquisition data. The field control module determines the control strategy based on the optimization control model according to the sensing acquisition data combined with the control operation information. At the same time, the field control module sends the control status data information to the cloud computing module, and the cloud computing module uses the sample data combined with the status data information to optimize the control model and obtain the optimized control model. The optimization control module optimizes and adjusts the field control module according to the feedback, so that the field control module performs control adjustment according to the optimized control model. 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 based on the intelligent analysis results.

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

[0065] In the above technical solution, the sensing 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 adopts a cloud computing module so that the field control module can also optimize the control model while making control adjustments, improve the performance of the controller, and optimize the control model through optimization learning without human participation, saving manpower consumption, reducing the time consumed by the optimization learning of the control model, improving the efficiency of the control model optimization, and providing a guarantee for the control adjustment of the field control module. The sensing acquisition module realizes the sensing acquisition of environmental data, so that when the controller is controlled and adjusted, the control adjustment can be combined with the sensing acquisition data, so that the control adjustment result is adapted to the actual factors, ensuring people's comfort and health. The cloud computing module realizes the optimization of the control model of the field control module, integrates the Internet of Things technology into the field control module, improves the computing power of the field control module, and does not require manual adjustment of the control model, saving manpower consumption, improving the efficiency of the control model adjustment, and providing a guarantee for the control adjustment of the field control module. The monitoring management module can realize the monitoring of the control state, make the control state data information transparent, and enable people to understand the state of the controller.

[0067] In one embodiment provided by the present invention, the sensing acquisition module includes multiple sensors. When using the 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 acquisition automatic control information of the sensor 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.

[0068] In the above technical solution, there are many types of sensors, such as temperature sensors, humidity sensors, etc., and multiple sensors of each type are provided.

[0069] In the above technical solution, the collected self-control information is the control information of the sensor, for example, sensing time, sensing frequency, sensing angle, etc.

[0070] The above technical solution can realize automatic monitoring of the target area through sensors, so that when determining the control strategy, it can combine the environmental factors to sense and collect data for control and adjustment, so that the control and adjustment results can be adapted to the environment, thereby improving the comfort of people in the target area and improving the protection of people's health.

[0071] like Figure 2 As shown, in one 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 status data information of the field control module and acquire sample data based on the status data information;

[0073] 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;

[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 adjustment unit is used to determine the optimization adjustment information according to the optimization control model.

[0076] In the above technical solution, the learning and training unit is connected to the data acquisition unit and the optimization and adjustment unit respectively, 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 received status data information of the field control module can be used as part of the sample data, or the 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 perform automatic analysis on the status data information, obtain intelligent analysis results, and obtain control monitoring information.

[0079] In the above technical solution, when the data acquisition unit acquires sample data based on the status data information, the status data information of the received field control module is used as the sample data, and the sample type analysis is performed on the status data information of the received field control module to determine the current number of the sample type, and then the total number of sample data is acquired, and the total data volume of the sample data is divided to obtain a first sample number and a second sample number, wherein the mean of the first sample number is greater than the second sample number, and then the target data information is acquired according to the sample type in combination with the current data of the sample type and the first sample number, and the acquired data information is combined with the status data information of the received field control module to obtain a first sample data set, and at the same time, the target data information is randomly acquired according to the second sample number to obtain a second sample data set, thereby obtaining 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 computational analysis through the cloud computing module, which can not only determine the monitoring information, but also optimize the learning of the control model and improve the accuracy of the control model, so that the on-site control module can be better adjusted based on the control model.

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

[0082] S1. Obtaining current model parameter data of the control model according to the state data information at a preset period;

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

[0084] S3, using 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. 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;

[0087] S6. Performing model parameter optimization analysis based on the model analysis results to obtain model parameter optimization values; when the model analysis results indicate that the current control model needs to be optimized and adjusted, performing optimization analysis on the current model parameter data in combination with the current model to determine the model parameter optimization values;

[0088] S7. 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;

[0089] S8. Determine the final optimized control model 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, continue to perform 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 demand.

[0091] In the above technical solution, when the model analysis result shows 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. The model analysis data is analyzed in combination with the model standard, including: performing first information identification on the model analysis data, obtaining model evaluation information, and disassembling the model standard to divide it into first standard information and second standard information, wherein 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; analyzing and judging 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, a model analysis result is obtained, 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, matching is performed in the second standard information according to the model analysis information, and the model analysis information is analyzed in combination with the corresponding second standard information according to the matching result to determine 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, a model analysis result is obtained, and the model analysis result is that the current control model needs to be optimized and adjusted, and when all model analysis information meets the corresponding second standard information, a model analysis result is obtained, 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 regular optimization learning of the control model through a preset cycle, so that the control model can be improved in time to ensure adjustments based on the control model. Moreover, through model analysis and evaluation, the current status of the control model is clarified, so that asynchronous optimization analysis can be performed when optimization adjustment is needed, thereby ensuring the effectiveness of the optimization analysis and reducing unnecessary waste of time.

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

[0095] A1. Perform a first information analysis on the state data information, determine the control state, and obtain a first analysis result;

[0096] A2. Determine the monitoring information mode according to the first analysis result. When the first analysis result shows that the control state is in the closed state, call the first monitoring information mode, and determine the monitoring display information based on the first monitoring information mode and the control closed state. When the first analysis result shows that the control state is in the open state, call the second monitoring information mode, and perform second information identification and extraction on the state data information to obtain the state data identification information. Then, generate the control display information for the second monitoring information mode according to the state data identification information to obtain the control display information.

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

[0098] In the above technical solution, the second information refers to 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 intelligent analysis of status data information through an intelligent analysis unit, so that control display information can be determined 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, the status data information can ensure the comprehensiveness of information while reducing the redundancy of irrelevant information, so that relevant personnel can better understand the control status from the control display information.

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

[0102] B1. Analyze and optimize the control model, determine whether optimization adjustment is needed, and obtain preliminary analysis and judgment results;

[0103] B2. Retrieve optimized control instruction information based on preliminary analysis and judgment results;

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

[0105] B4. Adjust and improve the optimized control instruction information according to the target adjustment information to obtain 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, the position of the target adjustment information is determined, the target position is locked, and the target adjustment information is used to fill or replace the data information according to the target position.

[0107] In the above technical solution, when analyzing the optimized control model and judging whether optimization adjustment is needed, 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, and obtaining a first judgment result. When the first judgment result is that the model framework has changed, the preliminary analysis judgment result is that optimization adjustment is needed. When the first judgment result is that the model framework has not changed, the parameters of the optimized control model and the control model before optimization are compared and analyzed according to the steps to judge whether the step parameters have changed, and obtain a second judgment result. Then, a statistical analysis is performed on the second judgment result. When the second judgment result of all steps is that the step parameters have not changed, the preliminary analysis judgment result is that optimization adjustment is not needed. When the second judgment result of a step is that the step parameters have changed, the preliminary analysis judgment result is that optimization adjustment is needed.

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

[0109] In the above technical solution, when the optimization control instruction information is retrieved according to the preliminary analysis and judgment result, the optimization control instruction information is retrieved only when the preliminary analysis and judgment result indicates 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 needed so that subsequent steps are carried out only when optimization and adjustment are needed, thereby avoiding waste of resources caused by invalid analysis. By retrieving the optimization control instruction information, adjustments and improvements are made based on the existing retrieved optimization control instruction information, thereby improving the efficiency of determining the optimization adjustment information. By effectively identifying the adjustment information for the optimization control model, adjustments and improvements can be made according to the target adjustment information, reducing the redundancy of irrelevant information. It can not only ensure the feedback of the optimization learning results, but also improve the data transmission efficiency between the cloud computing module and the field control module.

[0111] like Figure 6 As shown, in one embodiment provided by the present invention, the field 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 the shortcut control operation;

[0113] The control adjustment unit is used to perform control model analysis according to the control operation information combined with the sensor collection data, determine the control adjustment instruction, and perform control planning according to the control adjustment instruction to obtain the control strategy;

[0114] The control display unit is used to determine the control display information for the control adjustment unit and present 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, set up, set down, confirm, 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 performs control model analysis according to the control operation information combined with the sensing acquisition data, the control operation information is identified to determine the type of control operation and 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 sensing acquisition data to determine the control adjustment instruction based on the control model.

[0118] In the above technical scheme, when the control planning is carried out for 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 decomposed in pairs to obtain multiple control sub-combinations. The order within the team is determined according to the priority in the adjustment sub-combinations to obtain the control sub-queues. Then, sequence analysis is performed on the control sub-queues to obtain multiple control planning sequences. Then, 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.

[0119] The above technical solution can not only determine the control strategy based on the on-site operation through the on-site control module, but also visualize the control adjustment results of the control strategy. The control operation unit enables direct quick control operations to provide convenience for users. The control adjustment unit determines the control strategy, so that control responses can be made in time according to the control operation information, improving the efficiency of performance control, so that the target object can better meet people's needs. The control display unit visualizes the control adjustment results, so that relevant personnel can more intuitively understand the changes caused by the current control adjustment.

[0120] like Figure 7 As shown, in one embodiment provided by the present invention, the controller also includes: an active query module; the active query module obtains a query request for a target customer and obtains a query request instruction, and then the cloud computing module determines the query information according to the query request instruction, obtains the target query information, and provides feedback on the target query information.

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

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

[0123] The above technical solution enables the target customers to query the control-related information anytime and anywhere through the active query module, realizes the interaction with the target customers, and provides convenience for the target customers.

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

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

[0126] 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;

[0127] 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.

[0128] In the above technical solution, the user management unit notifies and reminds the target customer when the target customer verification fails.

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

[0130] The monitoring and management module of the above technical solution can not only monitor the control status and visualize the control status, but also realize integrated management. It can also realize user management while performing ledger management. The status monitoring is displayed in real time through the status monitoring unit, so that relevant personnel can better monitor the control and status. The ledger management unit can not only clarify the control startup time management and clarify how long the current control has been started, but also clarify the current power consumption of the controller, so as to roughly understand the energy consumption of the controller. The user management unit ensures the security of data information, so that only the target customers who have passed the verification can obtain the target query information based on the query request, which guarantees the authority of active query and avoids the leakage of data resources.

[0131] like Fig. 9 As shown, an embodiment of the present invention provides a control method for an air-conditioning system, which controls the air-conditioning system based on any of the controllers described above, connects the controller to the air-conditioning system, determines a control strategy based on the controller, and then the air-conditioning host performs control adjustments according to the control strategy.

[0132] The above technical solution integrates the controller based on the Internet of Things into the air-conditioning control system, so that the air-conditioning system can be controlled through the controller based on the Internet of Things, and the air-conditioning host is controlled and adjusted according to the control strategy determined by the controller based on the Internet of Things, thereby improving the control performance of the air-conditioning system, and enabling the air-conditioning system to be controlled according to a more precise control strategy while being controlled, thereby improving the accuracy of the air-conditioning system control.

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

[0134] Other embodiments of the present disclosure will be readily apparent to those skilled in the art after considering the specification and practicing the disclosure disclosed 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 common knowledge or customary techniques in the art that are not disclosed in the present disclosure. The specification and examples are to be considered as exemplary only, and the true scope and spirit of the present disclosure are indicated by the following claims.

[0135] It should be understood that the present disclosure is not limited to the exact structures that have been described above and shown in the drawings, and that various modifications and changes may be made without departing from the scope thereof. The scope of the present disclosure is limited only 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 optimization control model according to the sensor collection data combined with the control operation information; 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 field control module includes: a control operation unit, a control adjustment unit and a control display unit; The control operation unit is used to obtain control operation information based on the shortcut control operation; The control adjustment unit is used to perform control model analysis according to the control operation information combined with the sensor collection data, determine the control adjustment instruction, and perform control planning according to the control adjustment instruction 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.

8. 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.

9. The controller according to claim 8, 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.

10. A control method for an air conditioning system, based on the controller according to any one of claims 1 to 9, 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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