Intelligent temperature control system

Abstract

The invention discloses an intelligent temperature control system. The system comprises a solar heat collection plate, an energy storage device and an intelligent temperature control integrated circuit. The solar heat collection plate is connected with the energy storage device, and solar energy is converted into heat energy to be stored in the energy storage device. On the basis, renewable solar energy can be used as an energy source, and dependence on traditional fossil energy is eliminated. The processor in the intelligent temperature control integrated circuit can predict the indoor temperature change condition based on the historical temperature sequence, the weather sequence, the air humidity sequence and the indoor biological condition, and determine the heat energy release measure based on the indoor temperature change condition and the target temperature; heat energy release operation is conducted on the energy storage device based on the heat energy release measures so as to adjust the indoor temperature; on the basis, adjustment is not carried out only according to the current temperature, and pre-judgment and active intervention are carried out in advance. It can be seen that environment protection and energy saving can be guaranteed, meanwhile, the indoor temperature adjusting process is accelerated, and the use experience feeling and the living comfort degree are improved.

Description

Technical Field

[0001] The present application relates to the technical field of room temperature regulation, and more specifically, to an intelligent temperature control system. Background Art

[0002] In today's living scene, indoor temperature has become one of the important factors affecting living comfort. In daily life, people always expect to be in an indoor environment with a suitable temperature to obtain a comfortable living experience. In order to achieve this goal, indoor temperature is often adjusted with the help of equipment such as air conditioners and floor heating.

[0003] However, traditional air conditioning equipment or floor heating systems often consume a lot of electricity or burn a considerable amount of fossil energy to meet users' needs for room temperature adjustment. It is worth noting that even the generation of electricity is achieved by burning a large amount of fossil energy. In the process of burning fossil energy, many harmful gases will inevitably be released, such as carbon dioxide, sulfur dioxide, etc. These gases are discharged into the atmosphere in large quantities, which will undoubtedly cause extremely serious pollution to the atmosphere and pose a considerable threat to the ecological balance and people's health.

[0004] In recent years, as people pay more and more attention to environmental protection and sustainable development, solar energy, as a clean and pollution-free renewable energy with extremely abundant reserves, has gradually entered the public's field of vision and has attracted much attention from all walks of life. With its unique advantages of being inexhaustible and green, it provides a new direction with great potential for solving the energy consumption and environmental problems brought about by traditional room temperature control methods. Many scientific research teams and companies have begun to explore how to use solar energy more efficiently to adjust indoor temperature, hoping to create a new indoor temperature control system that can not only meet people's comfortable living needs, but also minimize dependence on traditional energy and reduce environmental pollution. Summary of the invention

[0005] In view of this, the present application provides an intelligent temperature control system, which is a new intelligent temperature system using solar energy to solve the shortcomings of the prior art.

[0006] In order to achieve the above objectives, the proposed solution is as follows:

[0007] An intelligent temperature control system, comprising a solar collector, an energy storage device and an intelligent temperature control integrated circuit;

[0008] The solar thermal collector is connected to the energy storage device to convert solar energy into thermal energy and store it in the energy storage device;

[0009] The intelligent temperature control integrated circuit is integrated with a processor;

[0010] The processor predicts indoor temperature changes based on historical temperature sequences, weather sequences, air humidity sequences and indoor biological conditions, and determines heat energy release measures based on the indoor temperature changes and target temperature; and performs heat energy release operations on the energy storage device based on the heat energy release measures to adjust the indoor temperature.

[0011] Optionally, the energy storage device includes a battery;

[0012] The solar thermal collector also converts solar energy into electrical energy and stores it in the battery;

[0013] The processor includes an operation execution module;

[0014] The operation execution module converts the electrical energy of the battery into thermal energy to perform a thermal energy release operation when the thermal energy stored in the energy storage device cannot meet the thermal energy required by the thermal energy release measure.

[0015] Optionally, the intelligent temperature control integrated circuit is also integrated with a temperature sensor;

[0016] The processor includes a temperature aggregation unit;

[0017] The temperature sensor collects indoor temperature and / or biological temperature in real time and uploads it to the processor;

[0018] The temperature aggregation unit combines the received indoor temperatures and / or biological temperatures to form a historical temperature sequence.

[0019] Optionally, the intelligent temperature control integrated circuit is also integrated with an intelligent camera;

[0020] The smart camera collects indoor image data in real time, identifies each collected indoor image data, determines the indoor biological situation, and uploads the indoor biological situation to the processor.

[0021] Optionally, the smart camera includes an indoor situation determination unit;

[0022] The indoor situation determination unit identifies the region of interest for each indoor image data, extracts feature information of the region of interest, and determines the number of people active indoors and their movement conditions.

[0023] Optionally, the processor includes a measure generation module;

[0024] The measure generation module predicts indoor temperature changes according to historical temperature sequences, weather sequences, air humidity sequences, the number of people active indoors and exercise conditions, and determines heat energy release measures based on the indoor temperature changes and the target temperature.

[0025] Optionally, the measure generation module includes a prediction unit;

[0026] The prediction unit, in combination with the fuzzy reasoning mechanism and the trained temperature prediction network, predicts indoor temperature changes based on historical temperature sequences, weather sequences, air humidity sequences, the number of people active indoors and exercise conditions.

[0027] Optionally, the prediction unit includes a temperature prediction component;

[0028] The temperature prediction component, combined with the fuzzy reasoning mechanism, predicts the fuzzy change trend of indoor temperature based on historical temperature sequences, weather sequences, air humidity sequences, the number of people active indoors and exercise conditions; combined with the trained temperature prediction network, predicts the indoor temperature multivariate data based on historical temperature sequences, weather sequences, air humidity sequences, the number of people active indoors and exercise conditions; and generates indoor temperature change conditions by referring to the indoor temperature fuzzy change trend and the indoor temperature multivariate data.

[0029] Optionally, the prediction unit includes a model training component;

[0030] The model training component constructs an initial prediction network and multiple training samples, each training sample includes a temperature training sequence of two consecutive historical periods and a weather training sequence, an air humidity training sequence, indoor activity number change information and indoor movement information in the previous historical period; the initial prediction network is trained using each training sample to obtain a temperature prediction sequence output by the initial prediction network; based on each temperature prediction sequence and its corresponding training sample, a corresponding prediction loss value is calculated, and based on each prediction loss value, the parameters of the initial prediction network are adjusted until the prediction loss value is less than a preset prediction threshold, and the final initial prediction network is the trained temperature prediction network.

[0031] Optionally, the processor includes a target temperature determination unit;

[0032] The target temperature determination unit obtains a control behavior prediction model, which is trained using multiple historical temperature control records containing behavior data, ambient temperature, weather conditions and / or ambient humidity as training samples; and predicts the target temperature based on the historical temperature sequence, the weather sequence, the air humidity sequence and the indoor biological conditions in combination with the control behavior prediction model.

[0033] It can be seen from the above technical solutions that the intelligent temperature control system provided by the present application can include a solar collector panel, an energy storage device and an intelligent temperature control integrated circuit; based on this, the present application can use renewable solar energy as an energy source, get rid of the dependence on traditional fossil energy, and fundamentally reduce the possibility of harmful gases produced by burning fossil energy and then polluting the atmospheric environment, which has significant environmental benefits, and the solar energy resources are abundant and almost inexhaustible, which reduces energy costs. However, considering the intermittent and unstable characteristics of solar energy, the solar collector panel of the present application can be connected to the energy storage device to convert solar energy into heat energy and store it in the energy storage device; thereby, it is ensured that the indoor temperature adjustment of the present application is not affected by the changes in solar energy, and that the present application has sufficient heat energy reserves to adjust the indoor temperature at any time, any time, and any weather, which improves the system operation stability and sustainability of the present application and ensures the reliable realization of the indoor temperature adjustment function. In addition, the intelligent temperature control integrated circuit of the present application may be integrated with a processor; the processor may predict indoor temperature changes based on historical temperature sequences, weather sequences, air humidity sequences and indoor biological conditions, and determine heat release measures based on the indoor temperature changes and target temperature; based on the heat release measures, the energy storage device is subjected to heat release operations to adjust the indoor temperature; based on this, the heat release measures of the present application are generated based on the predicted future indoor temperature, rather than only adjusting according to the current temperature, but pre-judgment and active intervention in advance, so that the generated heat release measures are more in line with actual needs, accelerating the adjustment of the indoor temperature to the target temperature, and further improving the user's living comfort and user experience. In addition, the present application can comprehensively consider historical temperature changes, weather conditions, air humidity changes, and the organisms and biological conditions contained in the room, predict the changing trend of the indoor temperature, and analyze and predict the comprehensive multi-dimensional data, so as to more accurately predict the future changing trend of the indoor temperature, and further improve the reliability and accuracy of the produced heat release measures. It can be seen that the present application can utilize clean energy to achieve uninterrupted indoor temperature regulation. While ensuring environmental protection and energy saving, it can accelerate the process of indoor temperature regulation and improve the user experience and living comfort. BRIEF DESCRIPTION OF THE DRAWINGS

[0034] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on the provided drawings without paying any creative work.

[0035] Figure 1 A system architecture diagram of an intelligent temperature control system disclosed in an embodiment of the present application;

[0036] Figure 2 A content architecture diagram of a processor disclosed in an embodiment of the present application;

[0037] Figure 3 This is a circuit architecture diagram of an intelligent temperature control integrated circuit disclosed in an embodiment of the present application. DETAILED DESCRIPTION

[0038] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0039] Next, the intelligent temperature control system of the present application is described in detail with reference to the accompanying drawings. It should be noted that the directions of the structures shown in the accompanying drawings of the present application are set in consideration of the ease of understanding of the description, and do not impose any restrictions on the directions of the embodiments of the present disclosure during actual implementation. Furthermore, the shape and size of the entire or a part of the structure shown in the accompanying drawings do not limit the actual shape and size.

[0040] See also Figure 1 It can be found that the intelligent temperature control system of the present application may include a solar collector panel 1 , an energy storage device 2 and an intelligent temperature control integrated circuit 3 .

[0041] The solar thermal collector panel 1 can be installed on a roof or balcony or other location that is easily exposed to sunlight.

[0042] The energy storage device 2 may contain a large amount of heat storage medium and pyrolytic medium, and the heat storage medium of the energy storage device 2 may flow through the solar thermal collector panel 1 .

[0043] The surface of the solar collector 1 may be covered with a heat absorber, which can absorb the visible light, near-infrared light and other energies in the solar radiation to the maximum extent. When sunlight irradiates the solar collector 1, the solar collector 1 absorbs the solar radiation energy, increases its own temperature, and then transfers the heat to the heat storage medium in the energy storage device 2 which is in close contact with the solar collector 1.

[0044] The heat storage medium may be water or heat transfer oil.

[0045] In addition, the energy storage device 2 may also be provided with a heat-insulating layer to reduce heat energy loss.

[0046] In addition, the heat absorber may be a vacuum tube or a flat plate coated with a heat absorbing coating.

[0047] The intelligent temperature control integrated circuit 3 can be used to monitor the indoor state in real time, generate a heat energy release operation based on the indoor state, and perform a heat energy release operation on the energy storage device based on the heat energy release operation to adjust the indoor temperature.

[0048] Specifically, the intelligent temperature control integrated circuit 3 may be integrated with a processor 30 .

[0049] The processor 30 may be a central processing unit (CPU), or an application-specific integrated circuit (ASIC); or one or more integrated circuits configured to implement the embodiment of the present invention; or a microprocessor.

[0050] The processor 30 can predict indoor temperature changes based on historical temperature sequences, weather sequences, air humidity sequences and indoor biological conditions, and determine heat energy release measures based on the indoor temperature changes and the target temperature; based on the heat energy release measures, the energy storage device is subjected to heat energy release operations to adjust the indoor temperature.

[0051] Among them, the heat energy releasing operation may correspond to a room temperature lowering operation or a room temperature raising operation.

[0052] Specifically, the processor 30 may adjust the temperature of the pyrolytic medium based on the thermal energy release measure to achieve a decrease in room temperature or an increase in room temperature.

[0053] For example, the processor 30 controls the heat energy stored in the energy storage device to heat the heat-releasing medium through command control. When the temperature of the heat-releasing medium is increased, the room can be heated.

[0054] For another example, the processor 30 controls the pyrolytic medium stored in the energy storage device to contact the surface of the low-temperature heat medium pipeline through command control, and the heat of the pyrolytic medium is transferred to the heat medium, so that the temperature of the hot air is reduced. At the same time, in conjunction with the ventilation system, the cooled air is reasonably circulated indoors, the hot air in the room is discharged, and the relatively cool outdoor air is introduced, so that the indoor temperature can be reduced.

[0055] It can be seen from the above technical solutions that the intelligent temperature control system provided by the present application may include a solar collector panel 1, an energy storage device 2 and an intelligent temperature control integrated circuit 3; based on this, the present application may use renewable solar energy as an energy source, get rid of the dependence on traditional fossil energy, and fundamentally reduce the possibility of polluting the atmospheric environment by producing harmful gases due to the burning of fossil energy, which has significant environmental benefits, and the solar energy resources are abundant and almost inexhaustible, which reduces the energy cost. However, considering that solar energy is intermittent and energy is unstable, the solar collector panel of the present application may be connected to the energy storage device 2 through a thermal energy medium to convert solar energy into thermal energy and store it in the energy storage device 2; thereby, it is ensured that the indoor temperature adjustment of the present application is not affected by the change of solar energy, and that the present application has sufficient thermal energy reserves to adjust the indoor temperature at any time, any time, and any weather, which improves the system operation stability and sustainability of the present application and ensures the reliable realization of the indoor temperature adjustment function. In addition, the intelligent temperature control integrated circuit 3 of the present application may be integrated with a processor 30; the processor 30 may predict indoor temperature changes based on historical temperature sequences, weather sequences, air humidity sequences and indoor biological conditions, and determine heat release measures based on the indoor temperature changes and target temperature; based on the heat release measures, the energy storage device 2 is subjected to heat release operation to adjust the indoor temperature; based on this, the heat release measures of the present application are generated based on the predicted future indoor temperature, rather than being adjusted only according to the current temperature, but are predicted in advance and actively intervened, so that the generated heat release measures are more in line with actual needs, accelerating the adjustment of the indoor temperature to the target temperature, and further improving the user's living comfort and user experience. In addition, the present application can comprehensively consider historical temperature changes, weather conditions, air humidity changes, and the organisms and biological conditions contained in the room, predict the trend of indoor temperature changes, and analyze and predict based on multi-dimensional data, so as to more accurately predict the future trend of indoor temperature changes, and further improve the reliability and accuracy of the produced heat release measures. It can be seen that the present application can utilize clean energy to achieve uninterrupted indoor temperature regulation. While ensuring environmental protection and energy saving, it can accelerate the process of indoor temperature regulation and improve the user experience and living comfort.

[0056] In some embodiments of the present application, the energy storage device 2 also includes a battery and a hot water tank.

[0057] The large amount of heat storage medium of the energy storage device 2 can be water, and a large amount of water can be built into the hot water tank for heat storage.

[0058] In addition to converting solar energy into thermal energy, the solar thermal collector panel 1 can also convert solar energy into electrical energy through built-in thermoelectric conversion equipment such as thermopiles, pyroelectric materials, etc.

[0059] The energy storage device 2 may also include a battery for storing electrical energy.

[0060] On this basis, the processor 30 may include an operation execution module 300, such as Figure 2 shown.

[0061] The operation execution module 300 can convert the electric energy of the battery into thermal energy to perform a thermal energy release operation when the thermal energy stored in the energy storage device cannot meet the thermal energy required by the thermal energy release measure.

[0062] Specifically, when the heat energy stored in the energy storage device cannot meet the heat energy required by the heat energy release measure, the operation execution module 300 can use the electric energy of the battery to adjust the temperature of the pyrolytic medium, so as to adjust the indoor temperature using the pyrolytic medium after the temperature adjustment.

[0063] It can be seen from the above technical solution that this embodiment provides an optional composition method of the energy storage device 2 and the processor 3. Through the above method, the battery in the energy storage device 2 and the operation execution module 300 in the processor can be used to apply the electric energy converted from solar energy to adjust the indoor temperature, thereby ensuring that the indoor temperature adjustment is not affected by the light intensity, thereby improving the wide application of the present application.

[0064] In some embodiments of the present application, the intelligent temperature control integrated circuit 3 may also be integrated with a temperature sensor 31, such as Figure 3 shown.

[0065] The temperature sensor may include an infrared temperature collection element and an indoor temperature collection element.

[0066] The indoor temperature collection element can monitor and collect the indoor temperature in real time, and upload the collected indoor temperature to the processor 30.

[0067] The infrared temperature collection element can monitor and collect the biological temperature in the room in real time through infrared sensing, and upload the collected biological temperature to the processor 30.

[0068] On this basis, the processor 30 can summarize the received indoor temperature and biological temperature, so the processor 30 can include a temperature summarizing unit 301, such as Figure 2 shown.

[0069] The temperature aggregation unit 301 may combine the received indoor temperatures and / or biological temperatures to form a historical temperature sequence.

[0070] Specifically, the indoor temperature collection element can collect the indoor temperature at various locations indoors, transmit it to the processor 30 via wired or wireless means, and apply the temperature aggregation unit 301 to filter, sample, encode, combine, and other processes on the indoor temperature.

[0071] In addition, the processor 30 can also determine in real time whether the indoor temperature exceeds the target temperature. If so, it re-enters the step of predicting indoor temperature changes based on historical temperature sequences, weather sequences, air humidity sequences and indoor biological conditions, and determining heat energy release measures based on the indoor temperature changes and the target temperature; based on the heat energy release measures, the energy storage device is subjected to heat energy release operations to adjust the indoor temperature.

[0072] It can be seen from the above technical solution that this embodiment provides an optional composition method of an intelligent temperature control integrated circuit 3. Through the above composition method, the intelligent temperature control integrated circuit 3 can monitor and collect the actual room temperature and actual human body temperature in real time through the temperature sensor, further improving the reliability of the historical temperature sequence of this application.

[0073] In some embodiments of the present application, the intelligent temperature control integrated circuit 3 may also be integrated with an intelligent camera 32, such as Figure 3 shown.

[0074] The smart camera 32 can collect indoor image data in real time, identify each collected indoor image data, determine the indoor biological situation, and upload the indoor biological situation to the processor 30.

[0075] Specifically, the smart camera 32 may be configured with a high-resolution image sensor to collect high-precision indoor image data in real time.

[0076] It can be seen from the above technical solution that this embodiment provides an optional composition method of an intelligent temperature integrated circuit 3. Through the above method, the intelligent camera 3 can be used to determine the indoor biological situation in real time, further improving the reliability of the present application.

[0077] In some embodiments of the present application, the smart camera 32 may include an indoor situation determination unit.

[0078] The indoor situation determination unit can identify the region of interest for each indoor image data, extract feature information of the region of interest, and determine the number of people active indoors and their movement conditions.

[0079] Specifically, the indoor situation determination unit can identify the region of interest for each indoor image data, extract the biometric information of the region of interest, and determine the number of people active indoors and their movement conditions.

[0080] Among them, the movement status may include information such as biological activity trajectory, biological behavior movements, etc.

[0081] It can be seen from the above technical solution that this embodiment provides an optional composition method of the smart camera 32, and the reliability of the present application can be further improved through the above method.

[0082] In some embodiments of the present application, the processor 30 may include a measure generation module 302, such as Figure 2 shown.

[0083] The measure generation module 302 can predict indoor temperature changes according to historical temperature sequences, weather sequences, air humidity sequences, the number of people active indoors and exercise conditions, and determine heat release measures based on the indoor temperature changes and the target temperature.

[0084] Specifically, when the indoor temperature change indicates that the indoor temperature will rise significantly, the heat energy release operation can further reduce the temperature of the heat release medium and slow down the temperature rise trend to maintain the stability of the indoor temperature.

[0085] When the indoor temperature changes indicate that the indoor temperature will drop significantly, the heat energy release operation can further increase the temperature of the heat release medium and slow down the temperature drop trend to maintain the stability of the indoor temperature.

[0086] Specifically, the intelligent temperature control integrated circuit 3 may also be integrated with a humidity sensor;

[0087] The humidity sensor is used to collect the humidity at various locations in the room and transmit the collected humidity to the processor 30 so that the processor 30 combines the various humidities to form an air humidity sequence.

[0088] The processor 30 may also compare the received humidity with a preset humidity threshold, and issue a health reminder when the humidity threshold is exceeded.

[0089] Similarly, the processor 30 may also issue a health reminder when the indoor temperature exceeds a preset temperature threshold.

[0090] A variety of safety protection measures can also be built into the intelligent temperature control system, such as protection against overheating and water leakage, to ensure the safe operation of the intelligent temperature control system.

[0091] The intelligent temperature control system can also be equipped with fault self-detection and alarm functions. When a fault occurs in the intelligent temperature control system, an alarm can be issued in time and corresponding protective measures can be taken.

[0092] Combined with the usage records of the intelligent temperature control system, questionnaire surveys and other data, the user's living environment and living habits are analyzed.

[0093] Assess the user's health status based on the user's exercise data, eating habits and other information.

[0094] Based on the analysis results, provide users with suggestions on improving living environment and quality of life.

[0095] Through advanced intelligent control algorithms, users can basically achieve a fully automatic, imperceptible experience of the most comfortable indoor temperature. At the same time, users can also remotely monitor and control the system through a mobile phone APP or control panel, achieving an intelligent and convenient user experience.

[0096] It can be seen from the above technical solution that this embodiment further provides an optional composition method of a processor 30, through which multi-dimensional data information can be combined to generate heat energy release measures.

[0097] In some embodiments of the present application, the measure generation module 302 may include a prediction unit.

[0098] The prediction unit can combine the fuzzy reasoning mechanism and the trained temperature prediction network to predict the indoor temperature changes based on the historical temperature series, weather series, air humidity series, number of indoor active people and exercise conditions.

[0099] Specifically, user portraits can be constructed and user groups can be identified based on users' historical behavior patterns such as behavioral habits and life situations.

[0100] The prediction unit can combine the fuzzy reasoning mechanism and the trained temperature prediction network to perform data processing such as cleaning, denoising and standardization on user groups, user portraits, historical temperature series, weather series, air humidity series, number of people active indoors and exercise conditions, and predict indoor temperature changes based on the processed data.

[0101] It can be seen from the above technical solutions that this embodiment provides an optional composition method of the measure generation module 302, through which the indoor temperature change situation can be better predicted, and the reliability of this application can be further improved.

[0102] In some embodiments of the present application, the measure generation module 302 may include a temperature prediction component.

[0103] The temperature prediction component can combine the fuzzy reasoning mechanism to predict the fuzzy change trend of indoor temperature based on historical temperature sequences, weather sequences, air humidity sequences, the number of people active indoors and exercise conditions; combine the trained temperature prediction network to predict indoor temperature multivariate data based on historical temperature sequences, weather sequences, air humidity sequences, the number of people active indoors and exercise conditions; and generate indoor temperature changes by referring to the indoor temperature fuzzy change trend and the indoor temperature multivariate data.

[0104] Specifically, the prediction unit can calculate the temperature deviation and the deviation change rate based on the historical temperature sequence and the target temperature, and determine the fuzzy change trend of the indoor temperature based on the historical temperature sequence, weather sequence, air humidity sequence, number of people active indoors, exercise conditions, temperature deviation and deviation change rate, combined with the fuzzy reasoning mechanism.

[0105] The temperature prediction network can record the mapping relationship between the corresponding indoor temperature sequence, ambient weather sequence, indoor air humidity sequence, indoor number of people and indoor movement and temperature changes, as well as the changing trends of the indoor temperature sequence, ambient weather sequence, indoor air humidity sequence, indoor number of people and indoor movement over time.

[0106] It can be seen from the above technical solution that this embodiment provides an optional composition method of a prediction unit, through which the fuzzy change trend of indoor temperature and the multivariate data of indoor temperature can be combined to form the indoor temperature change situation, further ensuring the accuracy of the indoor temperature change situation.

[0107] In some embodiments of the present application, the prediction unit may include a model training component.

[0108] A model training component can construct an initial prediction network and multiple training samples, each training sample contains a temperature training sequence of two consecutive historical periods and a weather training sequence, an air humidity training sequence, indoor activity number change information and indoor movement information in the previous historical period; the initial prediction network is trained using each training sample to obtain a temperature prediction sequence output by the initial prediction network; based on each temperature prediction sequence and its corresponding training sample, the corresponding prediction loss value is calculated, and the parameters of the initial prediction network are adjusted based on each prediction loss value until the prediction loss value is less than a preset prediction threshold, and the final initial prediction network is the temperature prediction network.

[0109] Specifically, the model training component can be used to enable the initial prediction network to learn the mapping relationships between the indoor temperature sequence, the ambient weather sequence, the indoor air humidity sequence, the number of people indoors and the indoor movement and the temperature changes, as well as the changing trends of the indoor temperature sequence, the ambient weather sequence, the indoor air humidity sequence, the number of people indoors and the indoor movement over time.

[0110] The Euclidean distance between each temperature prediction sequence and the temperature training sequence in the subsequent historical period in the corresponding training sample can be calculated as the loss value.

[0111] The specific value of the prediction threshold can be adjusted based on user feedback.

[0112] It can be seen from the above technical solution that this embodiment provides an optional composition method of a prediction unit, and the temperature prediction network can be trained through the above method to further improve the reliability of the temperature prediction network.

[0113] In some embodiments of the present application, the processor 30 may include a target temperature determination unit 303 .

[0114] The target temperature determination unit 303 can obtain a control behavior prediction model, which is trained using multiple historical temperature control records corresponding to behavior data, ambient temperature, weather conditions and / or ambient humidity as training samples; combined with the control behavior prediction model, the target temperature is predicted based on the historical temperature sequence, the weather sequence, the air humidity sequence and the indoor biological conditions.

[0115] Specifically, the control behavior prediction model may record the mapping relationship between behavior data, ambient temperature, weather conditions, ambient humidity and user temperature control behavior.

[0116] Different user portraits can correspond to different regulatory behavior prediction models.

[0117] Different user behavior patterns can correspond to different regulatory behavior prediction models.

[0118] It can be seen from the above technical solution that this embodiment also provides an optional composition method of a processor 30, through which the intelligence of temperature control can be further accelerated and the user experience can be further improved.

[0119] Finally, it should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, the elements defined by the sentence "comprise a ..." do not exclude the presence of other identical elements in the process, method, article or device including the elements.

[0120] The various embodiments in this specification are described in a progressive manner, and each embodiment focuses on the differences from other embodiments. The same or similar parts between the various embodiments can be referenced to each other.

[0121] The above description of the disclosed embodiments enables professionals and technicians in the field to implement or use the present application. Various modifications to these embodiments will be apparent to professionals and technicians in the field, and the general principles defined herein can be implemented in other embodiments without departing from the spirit or scope of the present application. The various embodiments of the present application can be combined with each other. Therefore, the present application will not be limited to the embodiments shown herein, but will conform to the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. An intelligent temperature control system, characterized in that: Including solar thermal collectors, energy storage devices and intelligent temperature control integrated circuits; The solar thermal collector is connected to the energy storage device to convert solar energy into thermal energy and store it in the energy storage device; The intelligent temperature control integrated circuit is integrated with a processor; The processor predicts indoor temperature changes based on historical temperature sequences, weather sequences, air humidity sequences and indoor biological conditions, and determines heat energy release measures based on the indoor temperature changes and target temperature; and performs heat energy release operations on the energy storage device based on the heat energy release measures to adjust the indoor temperature.

2. The intelligent temperature control system according to claim 1, characterized in that: The energy storage device includes a battery; The solar thermal collector also converts solar energy into electrical energy and stores it in the battery; The processor includes an operation execution module; The operation execution module converts the electrical energy of the battery into thermal energy to perform a thermal energy release operation when the thermal energy stored in the energy storage device cannot meet the thermal energy required by the thermal energy release measure.

3. The intelligent temperature control system according to claim 1, characterized in that: The intelligent temperature control integrated circuit is also integrated with a temperature sensor; The processor includes a temperature aggregation unit; The temperature sensor collects indoor temperature and / or biological temperature in real time and uploads it to the processor; The temperature aggregation unit combines the received indoor temperatures and / or biological temperatures to form a historical temperature sequence.

4. The intelligent temperature control system according to claim 1, characterized in that: The intelligent temperature control integrated circuit is also integrated with an intelligent camera; The smart camera collects indoor image data in real time, identifies each collected indoor image data, determines the indoor biological situation, and uploads the indoor biological situation to the processor.

5. The intelligent temperature control system according to claim 4, characterized in that: The smart camera includes an indoor situation determination unit; The indoor situation determination unit identifies the region of interest for each indoor image data, extracts feature information of the region of interest, and determines the number of people active indoors and their movement conditions.

6. The intelligent temperature control system according to claim 5, characterized in that: The processor includes a measure generation module; The measure generation module predicts indoor temperature changes according to historical temperature sequences, weather sequences, air humidity sequences, the number of people active indoors and exercise conditions, and determines heat energy release measures based on the indoor temperature changes and the target temperature.

7. The intelligent temperature control system according to claim 6, characterized in that: The measure generation module includes a prediction unit; The prediction unit, in combination with the fuzzy reasoning mechanism and the trained temperature prediction network, predicts indoor temperature changes based on historical temperature sequences, weather sequences, air humidity sequences, the number of people active indoors and exercise conditions.

8. The intelligent temperature control system according to claim 7, characterized in that: The prediction unit includes a temperature prediction component; The temperature prediction component, combined with the fuzzy reasoning mechanism, predicts the fuzzy change trend of indoor temperature based on historical temperature sequences, weather sequences, air humidity sequences, the number of people active indoors and exercise conditions; combined with the trained temperature prediction network, predicts the indoor temperature multivariate data based on historical temperature sequences, weather sequences, air humidity sequences, the number of people active indoors and exercise conditions; and generates indoor temperature change conditions by referring to the indoor temperature fuzzy change trend and the indoor temperature multivariate data.

9. The intelligent temperature control system according to claim 7, characterized in that: The prediction unit includes a model training component; The model training component constructs an initial prediction network and multiple training samples, each training sample includes a temperature training sequence of two consecutive historical periods and a weather training sequence, an air humidity training sequence, indoor activity number change information and indoor movement information in the previous historical period; the initial prediction network is trained using each training sample to obtain a temperature prediction sequence output by the initial prediction network; based on each temperature prediction sequence and its corresponding training sample, a corresponding prediction loss value is calculated, and based on each prediction loss value, the parameters of the initial prediction network are adjusted until the prediction loss value is less than a preset prediction threshold, and the final initial prediction network is the trained temperature prediction network.

10. The intelligent temperature control system according to claim 1, characterized in that: The processor includes a target temperature determination unit; The target temperature determination unit obtains a control behavior prediction model, which is trained using multiple historical temperature control records containing behavior data, ambient temperature, weather conditions and / or ambient humidity as training samples; and predicts the target temperature based on the historical temperature sequence, the weather sequence, the air humidity sequence and the indoor biological conditions in combination with the control behavior prediction model.

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