A method and system for monitoring indoor intelligent heating

Abstract

This invention provides an indoor intelligent heating monitoring method and system, belonging to the field of heating management technology. Specifically, it includes: acquiring the historical heating volume of indoor heating pipes, determining the historical predicted temperature within the most recent first time threshold based on other indoor temperature influencing factors, and determining, based on the deviation between the historical predicted temperature and the historical indoor temperature, that there are no problems with the heating pipes; determining the recommended valve opening of the indoor heating pipes based on user comfort thresholds and other indoor temperature influencing factors; constructing a valve correction amount based on the maximum value of the deviation between the historical predicted temperature and the historical temperature, the duration of the deviation exceeding the first deviation threshold, and the average absolute value of the deviation; obtaining the predicted valve opening based on the recommended valve opening and the valve correction amount; and allowing heating users to adjust the valves via a mobile terminal according to the predicted valve opening, thereby ensuring efficient tracking and tracing.

Description

Technical Field

[0001] This invention belongs to the field of heating management technology, and in particular relates to an indoor intelligent heating monitoring method and system. Background Technology

[0002] To achieve online monitoring of indoor heating status, the authorized invention patent CN102721108B, "A Household Heat Metering System for Single-Pipe Flow-Type Heating," calculates each user's heating consumption based on the total received start-up time and total heat, thus achieving accurate monitoring of users' heating usage. However, the following technical problems exist:

[0003] 1. The heating load for users was not adjusted based on indoor temperature fluctuations. In actual heating processes, valve jamming or other malfunctions may occur. Therefore, if indoor temperature fluctuations are not taken into account, it may be impossible to accurately monitor the heating load.

[0004] 2. Users cannot remotely and adaptively adjust their indoor heating status. In the existing technical solution, users can only manually adjust the heating amount according to the current indoor temperature. Not only can it not achieve fine adjustment, but it also cannot be linked with the future indoor temperature, resulting in a poor user experience.

[0005] To address the aforementioned technical problems, this invention provides an indoor intelligent heating monitoring method and system. Summary of the Invention

[0006] According to one aspect of the present invention, an indoor intelligent heating monitoring method is provided.

[0007] A method for monitoring indoor intelligent heating, characterized in that it specifically includes:

[0008] S11 Obtain the valve opening, supply water temperature, and return water temperature of the indoor heating pipes to determine the historical heating volume, and combine other indoor temperature influencing factors to determine the historical predicted temperature within the most recent first time threshold. If the deviation between the historical predicted temperature and the indoor historical temperature determines that there is no problem with the heating pipes, proceed to step S12.

[0009] S12 acquires the real-time indoor temperature of heating users and determines the predicted indoor temperature within a first time threshold in the future based on the real-time temperature, heating capacity, and other factors affecting indoor temperature.

[0010] S13 constructs user comfort based on the average value of the indoor predicted temperature, the duration of the indoor predicted temperature exceeding the first temperature threshold, and the duration of the indoor predicted temperature being lower than the second temperature threshold, and determines whether the heating amount meets the requirements based on the user comfort. If yes, no adjustment is needed; otherwise, proceed to step S14.

[0011] S14 determines the recommended valve opening of the indoor heating pipes based on the user comfort threshold and other indoor temperature influencing factors, and constructs a valve correction amount based on the maximum value of the deviation between the historical predicted temperature and the historical temperature, the duration of the deviation being greater than the first deviation threshold, and the average value of the absolute value of the deviation. Based on the recommended valve opening and the valve correction amount, a predicted valve opening is obtained, and the heating user adjusts the valve through a mobile terminal according to the predicted valve opening.

[0012] By using the deviation between historical predicted temperature and historical indoor temperature to determine the operating status of heating pipes, the system combines indoor temperature with the determination of the pipes' operating condition. This reduces technical problems such as inaccurate judgments and imprecise valve adjustments caused by issues with the pipes' operating status, while also improving the efficiency and reliability of valve adjustment.

[0013] User comfort is constructed based on the average value of the indoor predicted temperature, the duration of the indoor predicted temperature exceeding the first temperature threshold, and the duration of the indoor predicted temperature falling below the second temperature threshold. This not only considers the actual situation of the indoor predicted temperature but also takes into account the duration of excessively high and low indoor temperatures, thus achieving an evaluation of user comfort from multiple perspectives and ensuring an accurate assessment of the heating comfort of heating users.

[0014] By constructing the valve correction amount based on the maximum value of the deviation between the historical predicted temperature and the historical temperature, the duration of the deviation being greater than the first deviation threshold, and the average value of the absolute value of the deviation, the valve opening degree is accurately adjusted by combining historical data, ensuring the accuracy of valve opening degree adjustment and further improving the user's heating comfort.

[0015] A further technical solution is that the other factors affecting indoor temperature include, but are not limited to, indoor building area, outdoor temperature, and heating method, wherein the heating method includes radiators and underfloor heating.

[0016] A further technical solution involves determining that the heating pipes are free of problems using the following specific steps:

[0017] S21 determines the historical temperature deviation within the most recent first time threshold based on the historical predicted temperature and the indoor historical temperature, and determines whether there is a problem with the heating pipe based on the duration of the historical temperature deviation being greater than the second deviation threshold. If so, it is determined that there is a problem with the heating pipe; otherwise, proceed to step S22.

[0018] S22 determines the average absolute value of the historical temperature deviation within the most recent first time threshold based on the historical predicted temperature and the indoor historical temperature, and determines whether there is a problem with the heating pipe based on the average absolute value of the historical temperature deviation. If so, it is determined that there is a problem with the heating pipe; otherwise, proceed to step S23.

[0019] S23 determines the fault assessment value of the heating pipe based on the average value of the absolute value of the historical temperature deviation, the duration of the historical temperature deviation being greater than the second deviation threshold, and the ratio of the duration of the historical temperature deviation being greater than the second deviation threshold to the first time threshold. Based on the fault assessment value, it is determined whether there is a problem with the heating pipe. If so, it is determined that there is a problem with the heating pipe. If not, proceed to step S23.

[0020] S24 constructs a historical temperature deviation curve based on the historical predicted temperature and the historical indoor temperature, converts the historical temperature deviation curve into a grayscale image, and uses an image recognition model based on the grayscale image to obtain the image fault assessment value of the heating pipe, and determines whether the heating pipe has a fault based on the image fault assessment value and the fault assessment value.

[0021] A further technical solution is to obtain a comprehensive fault assessment value for the heating pipe based on the image fault assessment value and the fault assessment value, and to determine that the heating pipe does not have a fault when the comprehensive fault assessment value is less than a set fault assessment value.

[0022] A further technical solution is that the first time threshold is a duration of less than 2 hours, and the heating user can adjust it according to the mobile terminal.

[0023] A further technical solution involves determining whether the heating capacity meets the requirements using the following method:

[0024] S31 determines whether the heating capacity meets the requirements based on the average value of the indoor predicted temperature. If yes, the heating capacity meets the requirements; otherwise, proceed to step S32.

[0025] S32 determines whether the heating capacity meets the requirements based on the duration for which the indoor predicted temperature exceeds the first temperature threshold. If yes, proceed to step S33; otherwise, determine that the heating capacity cannot meet the requirements.

[0026] S33 determines whether the heating capacity meets the requirements based on the duration of the indoor predicted temperature exceeding the first temperature threshold. If yes, proceed to step S34; otherwise, determine that the heating capacity cannot meet the requirements.

[0027] S34 constructs user comfort based on the average value of the indoor predicted temperature, the duration of the indoor predicted temperature exceeding the first temperature threshold, and the duration of the indoor predicted temperature being lower than the second temperature threshold, and determines whether the heating capacity meets the requirements based on the user comfort.

[0028] A further technical solution is that the indoor predicted temperature needs to be further corrected by the historical temperature deviation, and the heating capacity needs to be determined based on the corrected indoor predicted temperature.

[0029] A further technical solution involves determining the recommended valve opening for the indoor heating pipes based on user comfort thresholds and other factors affecting indoor temperature, specifically including:

[0030] The comfort difference of the heating user is determined based on the user comfort level and the user comfort threshold.

[0031] Based on the aforementioned comfort difference and other factors affecting indoor temperature, the recommended heating capacity of the indoor heating pipes is determined.

[0032] The heating temperature of the heating pipe is corrected based on the lowest outdoor temperature within the first time threshold in the future to obtain the corrected heating temperature.

[0033] The recommended valve opening for the indoor heating pipes is determined based on the recommended heating capacity and the corrected heating temperature.

[0034] A further technical solution involves the following specific steps for constructing the valve correction amount:

[0035] S41 determines whether valve correction amount needs to be constructed based on the duration for which the deviation between the historical predicted temperature and the historical temperature is greater than the first deviation threshold. If yes, proceed to step S42; otherwise, valve correction amount does not need to be constructed.

[0036] S42 determines whether valve correction amount needs to be constructed based on the average value of the absolute value of the deviation amount. If yes, proceed to step S44; otherwise, proceed to step S43.

[0037] S43 determines whether valve correction amount needs to be constructed based on the maximum value of the deviation amount. If yes, proceed to step S44; otherwise, valve correction amount does not need to be constructed.

[0038] S44 constructs the valve correction amount based on the maximum value of the deviation between the historical predicted temperature and the historical temperature, the duration of the deviation being greater than the first deviation threshold, and the average value of the absolute value of the deviation.

[0039] On the other hand, this application provides a computer system comprising: a memory and a processor connected in communication, and a computer program stored in the memory and capable of running on the processor, characterized in that: when the processor runs the computer program, it executes the above-described indoor intelligent heating monitoring method.

[0040] On the other hand, the present invention provides a computer storage medium storing a computer program, which, when executed in a computer, causes the computer to execute the above-described indoor intelligent heating monitoring method.

[0041] Other features and advantages will be set forth in the description which follows, and will be apparent in part from the description, or may be learned by practicing the invention. The objects and other advantages of the invention are realized and obtained through the structures particularly pointed out in the description and the drawings.

[0042] To make the above-mentioned objects, features and advantages of the present invention more apparent and understandable, preferred embodiments are described below in detail with reference to the accompanying drawings. Attached Figure Description

[0043] The above and other features and advantages of the present invention will become more apparent from a detailed description of exemplary embodiments thereof with reference to the accompanying drawings.

[0044] Figure 1 This is a flowchart of an indoor intelligent heating monitoring method according to Embodiment 1. Detailed Implementation

[0045] Exemplary embodiments will now be described more fully with reference to the accompanying drawings. However, these exemplary embodiments can be implemented in many forms and should not be construed as limited to the embodiments set forth herein; rather, they are provided so that the invention will be thorough and complete, and the concept of the exemplary embodiments will be fully conveyed to those skilled in the art. The same reference numerals in the drawings denote the same or similar structures, and therefore their detailed description will be omitted.

[0046] The terms “a,” “one,” “the,” and “the” are used to indicate the existence of one or more elements / components / etc.; the terms “including” and “having” are used to indicate an open-ended meaning of inclusion and that other elements / components / etc. may exist in addition to the listed elements / components / etc.

[0047] Example 1

[0048] To solve the above problems, according to one aspect of the present invention, such as Figure 1 As shown, an indoor intelligent heating monitoring method is provided, characterized by specifically including:

[0049] S11 Obtain the valve opening, supply water temperature, and return water temperature of the indoor heating pipes to determine the historical heating volume, and combine other indoor temperature influencing factors to determine the historical predicted temperature within the most recent first time threshold. If the deviation between the historical predicted temperature and the indoor historical temperature determines that there is no problem with the heating pipes, proceed to step S12.

[0050] It should be noted that when determining the historical predicted temperature within the most recent first time threshold, it is also necessary to further combine the baseline temperature before the most recent first time threshold to determine the historical predicted temperature. For example, it is necessary to combine the historical indoor temperature 2 hours ago to determine the historical predicted temperature for the most recent 2 hours.

[0051] It should be noted that the other factors affecting indoor temperature include, but are not limited to, indoor building area, outdoor temperature, and heating method, wherein the heating method includes radiators and underfloor heating.

[0052] It should be noted that the specific steps to determine that there are no problems with the heating pipes are as follows:

[0053] S21 determines the historical temperature deviation within the most recent first time threshold based on the historical predicted temperature and the indoor historical temperature, and determines whether there is a problem with the heating pipe based on the duration of the historical temperature deviation being greater than the second deviation threshold. If so, it is determined that there is a problem with the heating pipe; otherwise, proceed to step S22.

[0054] S22 determines the average absolute value of the historical temperature deviation within the most recent first time threshold based on the historical predicted temperature and the indoor historical temperature, and determines whether there is a problem with the heating pipe based on the average absolute value of the historical temperature deviation. If so, it is determined that there is a problem with the heating pipe; otherwise, proceed to step S23.

[0055] S23 determines the fault assessment value of the heating pipe based on the average value of the absolute value of the historical temperature deviation, the duration of the historical temperature deviation being greater than the second deviation threshold, and the ratio of the duration of the historical temperature deviation being greater than the second deviation threshold to the first time threshold. Based on the fault assessment value, it is determined whether there is a problem with the heating pipe. If so, it is determined that there is a problem with the heating pipe. If not, proceed to step S23.

[0056] S24 constructs a historical temperature deviation curve based on the historical predicted temperature and the historical indoor temperature, converts the historical temperature deviation curve into a grayscale image, and uses an image recognition model based on the grayscale image to obtain the image fault assessment value of the heating pipe, and determines whether the heating pipe has a fault based on the image fault assessment value and the fault assessment value.

[0057] It is understood that a comprehensive fault assessment value for the heating pipe is obtained based on the image fault assessment value and the fault assessment value, and when the comprehensive fault assessment value is less than the set fault assessment value, it is determined that the heating pipe does not have a fault.

[0058] By using the deviation between historical predicted temperature and historical indoor temperature to determine the operating status of heating pipes, the system combines indoor temperature with the determination of the pipes' operating condition. This reduces technical problems such as inaccurate judgments and imprecise valve adjustments caused by issues with the pipes' operating status, while also improving the efficiency and reliability of valve adjustment.

[0059] S12 acquires the real-time indoor temperature of heating users and determines the predicted indoor temperature within a first time threshold in the future based on the real-time temperature, heating capacity, and other factors affecting indoor temperature.

[0060] It should be noted that the first time threshold is a duration of less than 2 hours, and the heating user can adjust it according to the mobile terminal.

[0061] S13 constructs user comfort based on the average value of the indoor predicted temperature, the duration of the indoor predicted temperature exceeding the first temperature threshold, and the duration of the indoor predicted temperature being lower than the second temperature threshold, and determines whether the heating amount meets the requirements based on the user comfort. If yes, no adjustment is needed; otherwise, proceed to step S14.

[0062] It should be noted that the method for determining whether the heating capacity meets the requirements is as follows:

[0063] S31 determines whether the heating capacity meets the requirements based on the average value of the indoor predicted temperature. If yes, the heating capacity meets the requirements; otherwise, proceed to step S32.

[0064] S32 determines whether the heating capacity meets the requirements based on the duration for which the indoor predicted temperature exceeds the first temperature threshold. If yes, proceed to step S33; otherwise, determine that the heating capacity cannot meet the requirements.

[0065] S33 determines whether the heating capacity meets the requirements based on the duration of the indoor predicted temperature exceeding the first temperature threshold. If yes, proceed to step S34; otherwise, determine that the heating capacity cannot meet the requirements.

[0066] S34 constructs user comfort based on the average value of the indoor predicted temperature, the duration of the indoor predicted temperature exceeding the first temperature threshold, and the duration of the indoor predicted temperature being lower than the second temperature threshold, and determines whether the heating capacity meets the requirements based on the user comfort.

[0067] For example, the user comfort level is determined using a model based on the PSO-BiGRU algorithm. Specifically, this invention introduces the concepts of sigmoid functions and random functions to optimize the inertia weight. The improved inertia weight formula is as follows:

[0068]

[0069] In the formula ω min ω max These are the minimum and maximum values ​​of the inertia weight, respectively; p, p max These are the current iteration number and the maximum iteration number, respectively; a and b are velocity coefficients, and the value of a ranges from 0 to 0.1. rand(8+p / p) max The value of 10) ranges from 8+p / p max A random number between 10 and 10.

[0070] It should be noted that the indoor predicted temperature needs to be further corrected by the historical temperature deviation, and the heating capacity needs to be determined based on the corrected indoor predicted temperature.

[0071] User comfort is constructed based on the average value of the indoor predicted temperature, the duration of the indoor predicted temperature exceeding the first temperature threshold, and the duration of the indoor predicted temperature falling below the second temperature threshold. This not only considers the actual situation of the indoor predicted temperature but also takes into account the duration of excessively high and low indoor temperatures, thus achieving an evaluation of user comfort from multiple perspectives and ensuring an accurate assessment of the heating comfort of heating users.

[0072] S14 determines the recommended valve opening of the indoor heating pipes based on the user comfort threshold and other indoor temperature influencing factors, and constructs a valve correction amount based on the maximum value of the deviation between the historical predicted temperature and the historical temperature, the duration of the deviation being greater than the first deviation threshold, and the average value of the absolute value of the deviation. Based on the recommended valve opening and the valve correction amount, a predicted valve opening is obtained, and the heating user adjusts the valve through a mobile terminal according to the predicted valve opening.

[0073] It is understandable that the recommended valve opening for the indoor heating pipes is determined based on user comfort thresholds and other factors affecting indoor temperature, specifically including:

[0074] The comfort difference of the heating user is determined based on the user comfort level and the user comfort threshold.

[0075] Based on the aforementioned comfort difference and other factors affecting indoor temperature, the recommended heating capacity of the indoor heating pipes is determined.

[0076] The heating temperature of the heating pipe is corrected based on the lowest outdoor temperature within the first time threshold in the future to obtain the corrected heating temperature.

[0077] The recommended valve opening for the indoor heating pipes is determined based on the recommended heating capacity and the corrected heating temperature.

[0078] For example, the specific steps for constructing the valve correction amount are as follows:

[0079] S41 determines whether valve correction amount needs to be constructed based on the duration for which the deviation between the historical predicted temperature and the historical temperature is greater than the first deviation threshold. If yes, proceed to step S42; otherwise, valve correction amount does not need to be constructed.

[0080] S42 determines whether valve correction amount needs to be constructed based on the average value of the absolute value of the deviation amount. If yes, proceed to step S44; otherwise, proceed to step S43.

[0081] S43 determines whether valve correction amount needs to be constructed based on the maximum value of the deviation amount. If yes, proceed to step S44; otherwise, valve correction amount does not need to be constructed.

[0082] S44 constructs the valve correction amount based on the maximum value of the deviation between the historical predicted temperature and the historical temperature, the duration of the deviation being greater than the first deviation threshold, and the average value of the absolute value of the deviation.

[0083] By constructing the valve correction amount based on the maximum value of the deviation between the historical predicted temperature and the historical temperature, the duration of the deviation being greater than the first deviation threshold, and the average value of the absolute value of the deviation, the valve opening degree is accurately adjusted by combining historical data, ensuring the accuracy of valve opening degree adjustment and further improving the user's heating comfort.

[0084] Example 2

[0085] This application provides a computer system comprising: a memory and a processor connected in communication, and a computer program stored in the memory and capable of running on the processor, characterized in that: when the processor runs the computer program, it executes the above-described indoor intelligent heating monitoring method.

[0086] Example 3

[0087] The present invention provides a computer storage medium storing a computer program, which, when executed in a computer, causes the computer to perform the aforementioned indoor intelligent heating monitoring method.

[0088] In the several embodiments provided in this application, it should be understood that the disclosed systems and methods can also be implemented in other ways. The system embodiments described above are merely illustrative; for example, the flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of the present invention. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code, which contains one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions marked in the blocks may occur in a different order than those marked in the drawings. For example, two consecutive blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in a block diagram and / or flowchart, and combinations of blocks in block diagrams and / or flowcharts, can be implemented using a dedicated hardware-based system that performs the specified function or action, or using a combination of dedicated hardware and computer instructions.

[0089] In addition, the functional modules in the various embodiments of the present invention can be integrated together to form an independent part, or each module can exist independently, or two or more modules can be integrated to form an independent part.

[0090] If the functionality is implemented as a software module and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this invention, or the part that contributes to the prior art, or a part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods of the various embodiments of this invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0091] Based on the above-described preferred embodiments of the present invention, and through the foregoing description, those skilled in the art can make various changes and modifications without departing from the inventive concept. The technical scope of this invention is not limited to the contents of the specification, but must be determined according to the scope of the claims.

Claims

1. A method for monitoring indoor intelligent heating, characterized in that, Specifically comprising: S11 acquires the valve opening degree of the heating pipeline in the indoor, the water supply temperature, and the return water temperature to determine the historical heating amount, and determines the historical predicted temperature within the first time threshold in the recent period in combination with other indoor temperature influencing factors, and determines that the heating pipeline has no problem when the deviation between the historical predicted temperature and the historical temperature in the indoor is determined, and enters step S12; S12 acquires the real-time temperature of the indoor of the heating user in real time, and determines the indoor predicted temperature within the future first time threshold based on the real-time temperature, the heating amount, and other indoor temperature influencing factors; S13 constructs the user comfort degree based on the average value of the indoor predicted temperature, the time length during which the indoor predicted temperature exceeds the first temperature threshold, and the time length during which the indoor predicted temperature is lower than the second temperature threshold, and determines whether the heating amount meets the requirement based on the user comfort degree, if yes, no adjustment is needed, and if no, enters step S14; S14 determines the recommended valve opening degree of the heating pipeline in the indoor based on the user comfort degree threshold and other indoor temperature influencing factors, constructs the valve correction amount based on the maximum value of the deviation between the historical predicted temperature and the historical temperature, the time length during which the deviation is greater than the first deviation threshold, and the average value of the absolute value of the deviation, obtains the predicted valve opening degree based on the recommended valve opening degree and the valve correction amount, and adjusts the valve based on the predicted valve opening degree through the mobile terminal by the heating user; The specific steps for determining that the heating pipeline has no problem are as follows: S21 determines the historical temperature deviation within the first time threshold in the recent period based on the historical predicted temperature and the historical temperature in the indoor, and determines whether the heating pipeline has a problem based on the time length during which the historical temperature deviation is greater than the second deviation threshold, if yes, it is determined that the heating pipeline has a problem, and if no, enters step S22; S22 determines the average value of the absolute value of the historical temperature deviation within the first time threshold in the recent period based on the historical predicted temperature and the historical temperature in the indoor, and determines whether the heating pipeline has a problem based on the average value of the absolute value of the historical temperature deviation, if yes, it is determined that the heating pipeline has a problem, and if no, enters step S23; S23 determines the fault evaluation value of the heating pipeline based on the average value of the absolute value of the historical temperature deviation, the time length during which the historical temperature deviation is greater than the second deviation threshold, and the ratio of the time length during which the historical temperature deviation is greater than the second deviation threshold to the first time threshold, and determines whether the heating pipeline has a problem based on the fault evaluation value, if yes, it is determined that the heating pipeline has a problem, and if no, enters step S23; S24 constructs the historical temperature deviation curve based on the historical predicted temperature and the historical temperature in the indoor, converts the historical temperature deviation curve into a grayscale image based on the historical temperature deviation curve, and obtains the image fault evaluation value of the heating pipeline by using an image recognition model based on the grayscale image, and determines whether the heating pipeline has a fault based on the image fault evaluation value and the fault evaluation value; The first time threshold is a time length within 2 hours.

2. The indoor intelligent heating monitoring method of claim 1, wherein, The other indoor temperature influencing factors include, but are not limited to, indoor building area, outdoor temperature, and heating mode, wherein the heating mode includes radiator and floor heating.

3. The indoor intelligent heating monitoring method of claim 1, wherein, The comprehensive fault evaluation value of the heating pipeline is obtained based on the image fault evaluation value and the fault evaluation value, and when the comprehensive fault evaluation value is less than a set fault evaluation value, it is determined that the heating pipeline does not have a fault.

4. The indoor intelligent heating monitoring method of claim 1, wherein, The method for determining whether the heating amount meets the requirement is: S31, whether the heating amount meets the requirement is determined based on the average value of the indoor predicted temperature, if yes, it is determined that the heating amount meets the requirement, and if no, step S32 is entered; S32, whether the heating amount meets the requirement is determined based on the time length during which the indoor predicted temperature exceeds a first temperature threshold, if yes, step S33 is entered, and if no, it is determined that the heating amount cannot meet the requirement; S33, whether the heating amount meets the requirement is determined based on the time length during which the indoor predicted temperature exceeds a first temperature threshold, if yes, step S34 is entered, and if no, it is determined that the heating amount cannot meet the requirement; S34, user comfort is constructed based on the average value of the indoor predicted temperature, the time length during which the indoor predicted temperature exceeds a first temperature threshold, and the time length during which the indoor predicted temperature is lower than a second temperature threshold, and whether the heating amount meets the requirement is determined based on the user comfort.

5. The indoor intelligent heating monitoring method of claim 1, wherein, The indoor predicted temperature also needs to be further corrected by the historical temperature deviation amount, and whether the heating amount meets the requirement is determined according to the corrected indoor predicted temperature.

6. A computer system comprising: The memory and the processor connected in communication, and the computer program stored on the memory and capable of running on the processor, characterized in that: when the processor runs the computer program, the indoor intelligent heating monitoring method of any one of claims 1-5 is executed.

7. A computer storage medium having a computer program stored thereon, when the computer program is executed in a computer, the computer program causes the computer to execute the indoor intelligent heating monitoring method of any one of claims 1-5.

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