Intelligent equipment joint control method, system and storage medium suitable for heat metering statistics

Abstract

The present invention provides a smart device joint control method, system and storage medium suitable for heat metering statistics, wherein the method comprises: performing equipment monitoring on smart devices located in a monitored residence for a preset number of monitoring days, and obtaining the operating status of the smart devices on each natural day corresponding to the preset monitoring days; calculating the difference between each adjacent outdoor temperature based on each natural day, and determining each natural day whose corresponding temperature difference is in a preset temperature range as a data comparison group; comparing the operating status of smart devices corresponding to each natural day in the same data comparison group, and obtaining the heat metering difference based on the heat metering output value corresponding to each natural day when the comparison result corresponds to a differential behavior; determining the behavior attribute corresponding to the differential behavior when the heat metering difference is negatively decreasing; and determining the behavior energy-saving index based on the behavior attribute corresponding to the differential behavior and the corresponding heat metering difference.

Description

Technical Field

[0001] The present invention relates to the field of energy-saving technology, and in particular to an intelligent device joint control method, system and storage medium suitable for heat metering statistics. Background Art

[0002] In cold seasons, residential heating is an important means to ensure a comfortable living environment and protect the health of residents. Heating equipment provides stable heat to maintain the indoor temperature within a suitable range. While radiators, floor heating and other heating equipment provide sufficient heat, they also cause a lot of energy consumption. With the development of technology, smart home devices are being used more and more widely in homes, such as smart windows and smart curtains. These smart devices can not only improve people's living experience, but also achieve energy saving by adjusting indoor light intensity and other behaviors.

[0003] The existing technology lacks quantitative evaluation of the energy-saving behavior of smart devices, so it is impossible to determine which specific behaviors of smart devices can achieve the best energy-saving effect, resulting in the inability of smart devices to fully exert their energy-saving advantages during actual use. Summary of the invention

[0004] Based on the above problems, the present invention is proposed to provide a smart device joint control method, system and storage medium suitable for heat metering statistics that overcome the above problems or at least partially solve the above problems.

[0005] According to one aspect of the present invention, there is provided a smart device joint control method suitable for heat metering statistics, comprising the following steps: performing device monitoring on smart devices located in a monitored residence for a preset number of monitoring days under the condition of corresponding to the same indoor temperature, and obtaining the operating status of the smart devices on each natural day corresponding to the preset monitoring days, determining each outdoor temperature corresponding to each natural day, and calculating the difference between adjacent outdoor temperatures based on each natural day, determining each natural day whose corresponding temperature difference is in a preset temperature range as a data comparison group, comparing the operating status of the smart devices corresponding to each natural day in the same data comparison group, and when the comparison result corresponds to a differential behavior, performing a differential calculation on the heat metering output values ​​corresponding to each natural day to obtain a heat metering difference, and when the heat metering difference is negatively decreasing, determining a behavior attribute corresponding to the differential behavior, wherein the behavior attribute includes a positive behavior attribute and a negative behavior attribute, and determining a behavior energy-saving index based on the behavior attribute corresponding to the differential behavior and the corresponding heat metering difference.

[0006] Optionally, in the method according to the present invention, the smart devices located in the monitored residence are continuously monitored for a preset number of monitoring days, and the operating status of the smart devices on each natural day corresponding to the preset monitoring days is obtained, including: establishing data communication with the smart devices based on the Internet of Things technology, and continuously monitoring the smart devices for a preset number of monitoring days, acquiring the operating status of the smart devices in real time on each natural day corresponding to the preset monitoring days, and obtaining the operating status at different moments corresponding to the same natural day, dividing the time periods based on each natural day to obtain the morning time period, the noon time period and the evening time period, and performing state fusion based on the operating status at each moment in the same time period to obtain the operating status of each time period corresponding to each time period.

[0007] Optionally, in the method according to the present invention, the smart device includes electric windows and / or electric curtains, and state fusion is performed based on the operating states at each moment in the same time period to obtain the operating states of each time period corresponding to each time period, including: when the smart device is an electric window, the moment opening and closing angle of the electric window is obtained based on each moment, and the moment opening and closing angle is determined as the moment operating state corresponding to the electric window, based on grouping the moment opening and closing angles corresponding to different moments, to obtain time period angle groups corresponding to different time periods, the opening and closing angles at each moment in the same time period angle group are averaged, and the obtained opening and closing angles at each time period are determined as the time period operating states corresponding to each time period, and / or, when the smart device is an electric curtain, the moment sliding distance of the electric curtain is obtained based on each moment, and the moment sliding distance is determined as the moment operating state corresponding to the electric curtain, based on grouping the moment sliding distances corresponding to different moments, to obtain time period sliding groups corresponding to different time periods, the sliding distances at each moment in the same time period sliding group are averaged, and the obtained sliding distances at each time period are determined as the time period operating states corresponding to each time period.

[0008] Optionally, in the method according to the present invention, the smart devices located in the monitored residence are continuously monitored for a preset number of monitoring days, and the operating status of the smart devices on each natural day corresponding to the preset monitoring days is obtained, including: dividing the time period based on each natural day to obtain a morning period, a noon period and an evening period, and establishing a device monitoring interface corresponding to the smart device, wherein the device monitoring interface includes a morning monitoring area corresponding to the morning period, a noon monitoring area corresponding to the noon period, and an evening monitoring area corresponding to the evening period; in response to the interaction of the residential user terminal with any monitoring area, the current time is determined; when the current time is in the time period corresponding to the monitoring area, the shooting unit pre-set in the residential user terminal is triggered and turned on, and a state schematic diagram obtained by the residential user terminal based on the shooting unit performing image acquisition on the smart device is obtained, and the state schematic diagram is filled in the corresponding monitoring area, and the operating status of each time period corresponding to each time period is obtained based on the state schematic diagrams corresponding to different monitoring areas.

[0009] Optionally, in the method according to the present invention, the smart device includes electric windows and / or electric curtains, and the operating status of each time period corresponding to each time period is obtained based on the status schematic diagrams corresponding to different monitoring areas, including: in response to the status schematic diagram being filled into the corresponding monitoring area, a status determination request is sent to the residential user end, and a scheduled task is established based on the sending time of the status determination request; if it is determined that the residential user end has no response to the status determination request within a preset time corresponding to the scheduled task, image recognition is performed on the status schematic diagram based on the scheduled task; when the smart device is an electric window, image recognition is performed on the status schematic diagram based on the image recognition. The method comprises the following steps: separately determining a window frame and an opening and closing window corresponding to the electric window in the state schematic diagram, determining a time period opening and closing angle formed between the window frame and the opening and closing window, and determining the time period opening and closing angles corresponding to different monitoring areas as the time period operation states respectively corresponding to each time period, and / or, when the smart device is an electric curtain, determining a sliding track and a curtain body corresponding to the electric curtain in the state schematic diagram based on the image recognition, determining a time period sliding distance of the curtain body on the sliding track, and determining the time period sliding distances corresponding to different monitoring areas as the time period operation states respectively corresponding to each time period.

[0010] Optionally, in the method according to the present invention, each outdoor temperature corresponding to each natural day is determined, and the difference between adjacent outdoor temperatures is calculated based on each natural day, and each natural day whose corresponding temperature difference is in a preset temperature range is determined as a data comparison group, including: dividing the preset monitoring days to obtain a preset number of divided intervals corresponding to different date intervals, wherein the number of natural days included in each divided interval is greater than or equal to two, determining the temperature of all natural days in the same divided interval to obtain each outdoor temperature corresponding to each natural day, and calculating the difference between adjacent outdoor temperatures based on the order of dates to obtain each temperature difference, when the temperature difference between two adjacent natural days is in the preset temperature range, the two natural days are determined as a data comparison group.

[0011] Optionally, in the method according to the present invention, the operating states of the smart devices corresponding to the natural days in the same data comparison group are compared, and when the comparison result is that the corresponding behavior has a difference, the difference calculation is performed on the heat metering output values ​​corresponding to the natural days to obtain the heat metering difference, including: when the smart device is an electric window, the opening and closing angles of the electric windows corresponding to the natural days in the same data comparison group in different time periods are calculated based on the same time period to obtain the angle differences corresponding to the different time periods, and each angle difference is compared with a preset angle interval. When any angle difference is not within the preset angle interval, the time period corresponding to the angle difference is determined as corresponding to the behavior with a difference, and / or, When the smart device is an electric curtain, the sliding distances of the electric curtains corresponding to each natural day in the same data comparison group in different time periods are calculated based on the difference of the same time period to obtain the distance differences corresponding to different time periods, and each distance difference is compared with a preset distance interval. When any distance difference is not within the preset distance interval, the time period corresponding to the distance difference is determined as corresponding to a different behavior, and the heat metering output value is obtained based on the different time periods corresponding to each natural day to obtain the output values ​​of each time period corresponding to the different time periods of the same natural day. The output values ​​of each time period in different time periods of each natural day are calculated based on the difference of the same time period in the order of dates to obtain the heat metering difference of each time period corresponding to different time periods.

[0012] Optionally, in the method according to the present invention, determining a behavior energy saving index based on a behavior attribute corresponding to the difference behavior and a corresponding heat metering difference value includes:

[0013] When the smart device is an electric window, the behavior energy saving index is determined by the following formula:

[0014]

[0015] Wherein, E1 is the behavior energy saving coefficient of the electric window corresponding to the positive behavior attribute, X is the angle difference corresponding to the difference behavior, k1 is the angle normalization value, k2 is the heat metering normalization value, H is the time period heat metering difference corresponding to the difference behavior, and a is the angle weight value;

[0016] or,

[0017] When the smart device is an electric curtain, the behavior energy saving index is determined by the following formula:

[0018]

[0019] Wherein, E1 is the energy-saving coefficient of the electric curtain under the positive behavior attribute, L is the distance difference corresponding to the difference behavior, k3 is the distance normalization value, k2 is the heat metering normalization value, H is the heat metering difference of the time period corresponding to the difference behavior, and b is the angle weight value;

[0020] or,

[0021] When the smart devices are electric windows and electric curtains, and the electric windows and electric curtains corresponding to the same time period have different behaviors, the behavior energy-saving index is determined based on the behavior attributes of the different behaviors corresponding to the electric windows and the behavior attributes of the different behaviors corresponding to the electric curtains.

[0022] Optionally, in the method according to the present invention, determining the behavior energy saving index based on the behavior attribute of the difference behavior corresponding to the electric window and the behavior attribute of the difference behavior corresponding to the electric curtain includes:

[0023] When the behavior attributes of the difference behavior corresponding to the electric window and the difference behavior corresponding to the electric curtain are both positive behavior attributes, a statistical calculation is performed based on E1 and E2 to obtain the behavior energy saving index;

[0024] or,

[0025] When the behavior attribute of the difference behavior corresponding to the electric window is a positive behavior attribute, and the behavior attribute of the difference behavior corresponding to the electric curtain is a negative behavior attribute, the behavior energy saving index is determined by the following formula:

[0026]

[0027] Wherein, E3 is the energy saving index of the behavior;

[0028] or,

[0029] When the behavior attribute of the difference behavior corresponding to the electric window is a negative behavior attribute, and the behavior attribute of the difference behavior corresponding to the electric curtain is a positive behavior attribute, the behavior energy saving index is determined by the following formula:

[0030]

[0031] Wherein, E3 is the energy saving index of the behavior.

[0032] According to another aspect of the present invention, there is provided an intelligent device joint control system suitable for heat metering statistics, comprising: an equipment monitoring module, configured to continuously monitor the equipment of the intelligent devices located in the monitored residence for a preset monitoring number of days under the condition of corresponding to the same indoor temperature, and obtain the operating status of the intelligent devices on each natural day corresponding to the preset monitoring days, a temperature comparison module, configured to determine each outdoor temperature corresponding to each natural day, and calculate the difference between each adjacent outdoor temperature based on each natural day, determine each natural day whose corresponding temperature difference is in the preset temperature range as a data comparison group, and determine the difference. The module is configured to compare the operating states of the smart devices corresponding to each natural day in the same data comparison group, and when the comparison result corresponds to a differential behavior, perform a difference calculation on the heat metering output values ​​corresponding to each natural day to obtain a heat metering difference. The attribute determination module is configured to determine the behavior attribute corresponding to the differential behavior when the heat metering difference decreases in a negative direction, wherein the behavior attribute includes a positive behavior attribute and a negative behavior attribute. The index determination module is configured to determine the behavior energy-saving index based on the behavior attribute corresponding to the differential behavior and the corresponding heat metering difference.

[0033] According to another aspect of the present invention, there is provided a computing device, comprising:

[0034] at least one processor; and

[0035] A memory storing program instructions, wherein the program instructions are configured to be executed by the at least one processor, and the program instructions include instructions for executing the above method.

[0036] According to another aspect of the present invention, a readable storage medium storing program instructions is provided. When the program instructions are read and executed by a computing device, the computing device executes the above method.

[0037] The present invention proposes a smart device joint control method suitable for heat metering statistics. By continuously monitoring the operating status of smart devices under the same indoor temperature conditions, comparing and analyzing the heat metering output values ​​under different operating states, behaviors with energy-saving effects are identified, and the corresponding energy-saving index is calculated based on these energy-saving behaviors, thereby providing users with optimized smart device control solutions and helping users achieve more efficient energy management. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] Figure 1 It is a flow chart of a smart device joint control method applicable to heat metering statistics provided by an embodiment of the present invention;

[0039] Figure 2 is a schematic diagram of a device monitoring interface provided by an embodiment of the present invention;

[0040] Figure 3 is a schematic diagram of an electric window provided by an embodiment of the present invention;

[0041] Figure 4 is a schematic diagram of an electric curtain provided by an embodiment of the present invention;

[0042] Figure 5 It is a structural schematic diagram of an intelligent device joint control system suitable for heat metering statistics provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0043] In order to make the purpose, technical solution and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0044] It should be noted that, if there is no conflict, the various features in the embodiments of the present invention can be combined with each other, and all are within the protection scope of the present invention. In addition, although the functional modules are divided in the device schematic diagram and the logical order is shown in the flow chart, in some cases, the steps shown or described can be performed in a different order from the module division in the device schematic diagram or the order in the flow chart.

[0045] The terms "first", "second", "third", and "fourth", etc. (if any) in the specification and claims of the present invention and the above drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the numbers used in this way can be interchanged where appropriate, so that the embodiments of the present invention described herein can be implemented in sequences other than those illustrated or described herein.

[0046] It should be understood that in the present invention, "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions. For example, a process, method, system, product or apparatus comprising a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to these processes, methods, products or apparatuses.

[0047] Unless otherwise defined, all technical and scientific terms used in this specification have the same meaning as those commonly understood by those skilled in the art of the present invention. The terms used in the specification of the present invention are only for the purpose of describing specific embodiments and are not intended to limit the present invention.

[0048] See also Figure 1 , Figure 1 This is a flow chart of a smart device joint control method suitable for heat metering statistics provided by an embodiment of the present application, including steps S1 to S5, which are as follows:

[0049] S1. Under the condition of the same indoor temperature, the smart devices in the monitored residence are continuously monitored for a preset number of monitoring days, and the operating status of the smart devices on each natural day corresponding to the preset number of monitoring days is obtained.

[0050] Among them, the indoor temperature represents the internal environment temperature of the monitored residence; the monitored residence represents the monitored residence, usually a specific residential unit where smart devices are installed and used for data collection; the smart device represents a household appliance that can be remotely monitored and controlled through a network connection; the preset monitoring days represent the monitoring time pre-set before starting the monitoring, such as 3 days, 7 days, 15 days, 30 days, etc.; the natural day represents a 24-hour period from midnight to midnight of the next day, divided according to the date on the calendar; the operating status represents the working status of the smart device at a certain moment or time period, such as on, off, etc.

[0051] Specifically, while keeping the indoor temperature of each monitored residence the same, the smart devices in the monitored residence are monitored for multiple consecutive days, and the operating status of the smart devices is recorded in real time every day (i.e., every natural day). The number of smart devices in each monitored residence can be one or more. Obtaining the operating status of the smart devices on each natural day can provide data basis for the evaluation of subsequent energy-saving behaviors.

[0052] For example: The preset monitoring days are 7 days, and the same indoor temperature is 20℃. During these 7 days, the internal ambient temperature of each monitored residence is maintained at 20℃, and the specific working conditions of the smart devices in each monitored residence are recorded every day.

[0053] It should be noted that the indoor temperature of the monitored residence has a certain impact on the power consumption of smart devices, that is, the power consumption output by the same smart device in each monitored residence at different indoor temperatures may be different. In order to eliminate or minimize the impact of indoor temperature differences on the power consumption monitoring results of smart devices, it is necessary to ensure that all monitoring is carried out under the same indoor temperature conditions during the evaluation of energy-saving behavior.

[0054] In some embodiments, step S1 (continuously monitoring the smart devices in the monitored residence for a preset number of monitoring days, and obtaining the operating status of the smart devices on each natural day corresponding to the preset number of monitoring days) specifically includes steps S11 to S13:

[0055] S11. Establish data communication with the smart device based on the Internet of Things technology, and perform device monitoring on the smart device for a preset number of monitoring days.

[0056] Among them, Internet of Things technology refers to a technology that connects any object to the network through information sensing devices to exchange and communicate information. It is extended and expanded based on Internet technology to realize the interconnection of all things; data communication refers to the process of data exchange and sharing between smart devices and smart device joint control systems suitable for heat metering statistics.

[0057] It should be noted that establishing data communication with smart devices and conducting continuous (uninterrupted) monitoring can provide a data source for subsequent real-time acquisition of the working conditions of smart devices at different times on different natural days.

[0058] S12. Acquire the operating status of the smart device in real time on each natural day corresponding to the preset monitoring days, and obtain the operating status at different times corresponding to the same natural day.

[0059] Among them, different moments represent various recorded time points in a natural day, such as 6:00 am; the moment operation status represents the specific working status of the smart device at the recorded time point.

[0060] For example: The preset monitoring days are 3 days, and monitoring starts on July 3, 2024. The natural days corresponding to the preset monitoring days are July 3, 2024, July 4, 2024, and July 5, 2024. On July 3, 2024 (00:00 to 23:59 on the first day), the operating status of the smart device is obtained in real time, and the operating status of the smart device is recorded once every hour (such as 8:00 am, 12:00 noon, 22:00 pm, etc.) to obtain the operating status at different times on July 3, 2024; on July 4, 2024 (00:00 to 23:59 on the second day), the operating status of the smart device is obtained in real time, and the operating status of the smart device is recorded once every hour to obtain the operating status at different times on July 4, 2024; on July 5, 2024 (00:00 to 23:59 on the third day), the operating status of the smart device is obtained in real time, and the operating status of the smart device is recorded once every hour to obtain the operating status at different times on July 5, 2024.

[0061] It should be noted that obtaining detailed working conditions of smart devices at different times on different natural days can provide a data basis for subsequent time period division and status fusion.

[0062] S13, dividing the time periods based on each natural day to obtain the morning time period, the noon time period and the evening time period, and performing state fusion based on the operation status at each moment in the same time period to obtain the operation status of each time period corresponding to each time period.

[0063] Among them, time period division means dividing a day into different time periods; the morning period can be specifically 03:00-10:59; the noon period can be specifically 11:00-18:59; the evening period can be specifically 19:00-2:59; state fusion means comprehensively processing the corresponding operating states of multiple recorded time points in a specific time period (morning period, noon period, evening period) to obtain an overall operating state representing the time period. The overall operating state is the time period operating state, which reflects the overall working status of the smart device in a specific time period.

[0064] Specifically, a day has 24 hours in total, which are divided into 3 time periods, and each time period includes 8 hours. The moments corresponding to the morning period include 03:00, 04:00, 05:00, 06:00, 07:00, 08:00, 09:00, and 10:00. The operating states corresponding to these 8 recorded time points are comprehensively processed to obtain the period operating state corresponding to the morning period; the moments corresponding to the noon period include 11:00, 12:00, 13:00, 14:00, 15:00, 16:00, 17:00, and 18:00. The operating states corresponding to these 8 recorded time points are comprehensively processed to obtain the period operating state corresponding to the noon period; the moments corresponding to the evening period include 19:00, 20:00, 21:00, 22:00, 23:00, 00:00, 01:00, and 02:00. The operating states corresponding to these 8 recorded time points are comprehensively processed to obtain the period operating state corresponding to the evening period.

[0065] For example, the time periods corresponding to the morning period include 03:00, 04:00, 05:00, 06:00, 07:00, 08:00, 09:00, and 10:00. At the recording time points 03:00, 04:00, 05:00, 09:00, and 10:00, the operation status of the smart device is off, that is, the operation status corresponding to the five recording time points is off; at the recording time points 06:00, 07:00, and 08:00, the operation status of the smart device is on, that is, the operation status corresponding to the three recording time points is on. After comprehensive processing of the operation status corresponding to these eight recording time points, it is found that the operation status corresponding to the morning period is off.

[0066] It should be noted that dividing each natural day into different time periods can simplify complex operating status data into overall operating status within different time periods, effectively reducing the amount of data processing and facilitating subsequent analysis and comparison; and dividing each natural day into time periods according to the corresponding morning period, noon period and evening period can also ensure that the difference between the outdoor temperatures at different times is small, thereby improving the corresponding reference.

[0067] In some embodiments, the smart device includes electric windows and / or electric curtains, and step S13 (based on the state fusion of the operating states at each time in the same time period, to obtain the operating states of each time period corresponding to each time period) specifically includes steps S131 to S136:

[0068] S131. When the smart device is an electric window, the momentary opening and closing angle of the electric window is obtained at each moment, and the momentary opening and closing angle is determined as the momentary operating state corresponding to the electric window.

[0069] Among them, the electric window represents a window that can be opened and closed by a motor, and its opening and closing angle can be obtained and adjusted in real time; the momentary opening and closing angle represents the opening and closing degree of the electric window at a certain moment, expressed in angles, such as at 8:00 am on July 5, 2024, the opening and closing angle of the electric window is 60 degrees; the momentary operating status represents the specific working status of the electric window at a certain moment.

[0070] It should be noted that the larger the opening and closing angle of the electric window, the worse the heat preservation effect will be.

[0071] S132, grouping based on the opening and closing angles at different moments to obtain time period angle groups corresponding to different time periods.

[0072] The time period angle grouping means that after a natural day is divided into several time periods, the opening and closing angles at different times are grouped according to the time periods.

[0073] Specifically, the opening and closing angles of each recorded time point in the morning period are grouped into one group, the opening and closing angles of each recorded time point in the noon period are grouped into one group, and the opening and closing angles of each recorded time point in the evening period are grouped into one group.

[0074] Example: Divide July 5, 2024 into different time periods to obtain the morning period (03:00-10:59), the afternoon period (11:00-18:59) and the evening period (19:00-2:59).

[0075] For the morning period, the recording time points are 03:00, 04:00, 05:00, 06:00, 07:00, 08:00, 09:00, and 10:00, respectively. The opening and closing angles of the electric windows at 03:00 are 10°, the opening and closing angles at 04:00 are 20°, the opening and closing angles at 05:00 are 30°, the opening and closing angles at 06:00 are 40°, the opening and closing angles at 7:00 are 50°, the opening and closing angles at 8:00 are 60°, the opening and closing angles at 09:00 are 70°, and the opening and closing angles at 10:00 are 80°. The opening and closing angles of the electric windows at these times are divided into a group, and the time period angle groups of 10°, 20°, 30°, 40°, 50°, 60°, 70°, and 80° are obtained for the morning period.

[0076] For the noon period, the recording time points are 11:00, 12:00, 13:00, 14:00, 15:00, 16:00, 17:00, and 18:00, respectively. The opening and closing angles of the electric windows at 11:00 are 30°, the opening and closing angles at 12:00 are 35°, the opening and closing angles at 13:00 are 40°, the opening and closing angles at 14:00 are 45°, the opening and closing angles at 15:00 are 50°, the opening and closing angles at 16:00 are 55°, the opening and closing angles at 17:00 are 60°, and the opening and closing angles at 18:00 are 65°. The opening and closing angles of the electric windows at these times are divided into a group, and the time period angle groups for the noon period are obtained as 30°, 35°, 40°, 45°, 50°, 55°, 60°, and 65°.

[0077] For the evening period, the recording time points are 19:00, 20:00, 21:00, 22:00, 23:00, 00:00, 01:00, and 02:00, respectively. The opening and closing angle of the electric window at 19:00 is 70°, the opening and closing angle of the electric window at 20:00 is 75°, the opening and closing angle of the electric window at 21:00 is 80°, the opening and closing angle of the electric window at 22:00 is 85°, the opening and closing angle of the electric window at 23:00 is 90°, the opening and closing angle of the electric window at 00:00 is 95°, the opening and closing angle of the electric window at 01:00 is 100°, and the opening and closing angle of the electric window at 02:00 is 105°. The opening and closing angles of the electric windows at these times are divided into a group, and the time period angle groups for the evening period are obtained as 70°, 75°, 80°, 85°, 90, 95°, 100°, and 105°.

[0078] It should be noted that grouping the opening and closing angles at different times according to time periods can facilitate analysis of the changes in the opening and closing angles within the same time period.

[0079] S133, calculating the mean of the opening and closing angles at each moment in the same time period angle group, and determining the obtained opening and closing angles of each time period as the operation states of each time period corresponding to each time period.

[0080] Among them, the average value of all opening and closing angle data within a time period is calculated to obtain the average opening and closing angle of the electric window within the time period, and the average opening and closing angle is the time period opening and closing angle; the time period operating status represents the specific working status of the electric window within a certain time period.

[0081] For example, the time period opening and closing angle corresponding to the morning period is (10°+20°+30°+40°+50°+60°+70°+80°)÷8, that is, 45°; the time period opening and closing angle corresponding to the noon period is (30°+35°+40°+45°+50°+55°+60°+65°)÷8, that is, 47.5°; the time period opening and closing angle corresponding to the evening period is (70°, 75°, 80°, 85°, 90, 95°, 100°, 105°)÷8, that is, 87.5°. The time period opening and closing angle of 45° is determined as the time period operation state corresponding to the morning period, the time period opening and closing angle of 47.5° is determined as the time period operation state corresponding to the noon period, and the time period opening and closing angle of 87.5° is determined as the time period operation state corresponding to the evening period.

[0082] and / or,

[0083] S134: When the smart device is an electric curtain, the momentary sliding distance of the electric curtain is acquired at each moment, and the momentary sliding distance is determined as the momentary operating state corresponding to the electric curtain.

[0084] Among them, the electric curtain refers to a curtain that can be controlled to slide by a motor, and its sliding distance can be obtained and adjusted in real time; the sliding distance at a moment represents the straight-line distance moved by the electric curtain relative to its initial position at a specific time point, which is used to indicate the degree of opening or closing of the electric curtain at that moment, such as at 12:00 noon on July 4, 2024, the sliding distance of the electric curtain is 100 cm; the operating status at a moment represents the specific working status of the electric curtain at a certain moment.

[0085] It should be noted that the greater the sliding distance of the electric curtains, the worse the insulation effect will be.

[0086] S135 , grouping based on the sliding distances at different moments to obtain time period sliding groups corresponding to different time periods.

[0087] The time period sliding grouping means that after a natural day is divided into several time periods, the sliding distances at different times are grouped according to the time periods.

[0088] Specifically, the sliding distances of each recorded time point in the morning period are grouped into one group, the sliding distances of each recorded time point in the noon period are grouped into one group, and the sliding distances of each recorded time point in the evening period are grouped into one group.

[0089] Example: Divide July 4, 2024 into different time periods to obtain the morning period (03:00-10:59), the afternoon period (11:00-18:59) and the evening period (19:00-2:59).

[0090] For the morning period, the recording time points are 03:00, 04:00, 05:00, 06:00, 07:00, 08:00, 09:00, and 10:00, respectively. The sliding distance of the electric curtain at 03:00 is 10 cm, the sliding distance at 04:00 is 20 cm, the sliding distance at 05:00 is 30 cm, the sliding distance at 06:00 is 40 cm, the sliding distance at 7:00 is 50 cm, the sliding distance at 8:00 is 60 cm, the sliding distance at 09:00 is 70 cm, and the sliding distance at 10:00 is 80 cm. The sliding distances of the electric curtain at these moments are divided into a group, and the sliding groups of the morning period are obtained as 10 cm, 20 cm, 30 cm, 40 cm, 50 cm, 60 cm, 70 cm, and 80 cm.

[0091] For the noon period, the recording time points are 11:00, 12:00, 13:00, 14:00, 15:00, 16:00, 17:00, and 18:00, respectively. The sliding distance of the electric curtain at 11:00 is 90 cm, the sliding distance at 12:00 is 100 cm, the sliding distance at 13:00 is 110 cm, the sliding distance at 14:00 is 120 cm, the sliding distance at 15:00 is 130 cm, the sliding distance at 16:00 is 140 cm, the sliding distance at 17:00 is 150 cm, and the sliding distance at 18:00 is 160 cm. The sliding distances of the electric curtain at these times are divided into a group, and the sliding groups of the noon period are obtained as 90 cm, 100 cm, 110 cm, 120 cm, 130 cm, 140 cm, 150 cm, and 160 cm.

[0092] For the evening period, the recording time points are 19:00, 20:00, 21:00, 22:00, 23:00, 00:00, 01:00, and 02:00 respectively. The sliding distance of the electric curtain at 19:00 is 170 cm, the sliding distance at 20:00 is 180 cm, the sliding distance at 21:00 is 190 cm, the sliding distance at 22:00 is 200 cm, the sliding distance at 23:00 is 210 cm, the sliding distance at 00:00 is 220 cm, the sliding distance at 01:00 is 230 cm, and the sliding distance at 02:00 is 240 cm. The sliding distances of the electric curtain at these moments are divided into a group, and the sliding groups of the evening period are obtained as 170 cm, 180 cm, 190 cm, 200 cm, 210 cm, 220 cm, 230 cm, and 240 cm.

[0093] It should be noted that grouping the sliding distances at different times according to time periods can facilitate analysis of the sliding distance changes within the same time period.

[0094] S136: Calculate the average of the sliding distances at each moment in the same time period sliding group, and determine the obtained sliding distances of each time period as the operation states of each time period corresponding to each time period.

[0095] Among them, the average value of all sliding distance data in a time period is calculated to obtain the average sliding distance of the electric curtain in the time period, and the average sliding distance is the time period sliding distance; the time period operation status represents the specific working status of the electric curtain in a certain time period.

[0096] For example, the time period sliding distance corresponding to the morning period is (10cm+20cm+30cm+40cm+50cm+60cm+70cm+80cm)÷8, that is, 45cm; the time period sliding distance corresponding to the noon period is (90cm+100cm+110cm+120cm+130cm+140cm+150cm+160cm)÷8, that is, 125cm; the time period sliding distance corresponding to the evening period is (170cm+180cm+190cm, 200cm+210cm+220cm+230cm+240cm)÷8, that is, 205cm. The time period sliding distance of 45cm is determined as the time period operation state corresponding to the morning period, the time period sliding distance of 125cm is determined as the time period operation state corresponding to the noon period, and the time period sliding distance of 205cm is determined as the time period operation state corresponding to the evening period.

[0097] This embodiment obtains the operating status of smart devices based on the Internet of Things technology. The system divides each day into three periods: morning, noon, and evening, and monitors the smart devices in each period. For electric windows, the opening and closing angles at each moment are recorded in real time, the opening and closing angles at all moments are grouped according to the time period, and the average opening and closing angles of each time period are calculated to determine the operating status of each time period; for electric curtains, the sliding distance at each moment is recorded in real time, the sliding distances at all moments are grouped according to the time period, and the average sliding distance of each time period is calculated to determine the operating status of each time period. This embodiment does not require manual intervention, and data collection and processing are highly automated, ensuring the real-time and accuracy of the data.

[0098] The method further includes: performing device monitoring on the smart devices in the monitoring residence for a preset number of monitoring days, and obtaining the operating status of the smart devices on each natural day corresponding to the preset number of monitoring days.

[0099] A1. Divide the time periods based on each natural day to obtain morning time period, noon time period and evening time period, and establish a device monitoring interface corresponding to the smart device, wherein the device monitoring interface includes a morning monitoring area corresponding to the morning time period, a noon monitoring area corresponding to the noon time period, and an evening monitoring area corresponding to the evening time period.

[0100] See also Figure 2 , Figure 2 It is a schematic diagram of a device monitoring interface provided by an embodiment of the present invention.

[0101] Among them, the device monitoring interface represents a user interface for displaying the working image of the smart device; the morning monitoring area represents the interface part for displaying the corresponding working image of the smart device during the morning period; the noon monitoring area represents the interface part for displaying the corresponding working status image of the smart device during the noon period; the evening monitoring area represents the interface part for displaying the corresponding working image of the smart device during the evening period.

[0102] A2. In response to the interaction of the residential user terminal with any monitoring area, the current time is determined, and when the current time is in the time period corresponding to the monitoring area, the shooting unit pre-set in the residential user terminal is triggered and turned on.

[0103] Among them, the residential user end represents the terminal equipment used by users in each monitored residence, such as smart phones, tablet computers, etc., which can be used to display the device monitoring interface; the interaction represents the operations performed by the user on the device monitoring interface, such as clicks, etc.; the current time represents the actual time when the user performs the operation; the shooting unit represents a camera device used to shoot smart devices, which can be a camera or other image acquisition device, and the trigger start means activating the shooting unit to start working.

[0104] Specifically, at 9:00 a.m. on July 5, 2024, the user clicks on the morning monitoring area on the device monitoring interface. The time period corresponding to the morning monitoring area is 03:00-10:59. It is determined that the current time 9:00 a.m. is within the time period corresponding to the monitoring area, 03:00-10:59, and the shooting unit is activated to shoot the smart device.

[0105] A3. Obtain a status schematic diagram obtained by the residential user terminal based on image acquisition of the smart device by the shooting unit, and fill the status schematic diagram into the corresponding monitoring area.

[0106] Among them, image acquisition means that the camera takes pictures of the smart device, the status diagram means the image used to display the current status of the smart device; filling means placing the status diagram into the corresponding monitoring area, that is, the status diagram will be displayed in the corresponding part of the device monitoring interface.

[0107] A4. Based on the state diagrams corresponding to different monitoring areas, the operation states of each time period corresponding to each time period are obtained.

[0108] The time period operation status indicates the specific working status of the smart device in a certain time period.

[0109] It should be noted that simplifying the complex operating status data into the overall operating status in different time periods effectively reduces the amount of data processing and facilitates subsequent analysis and comparison.

[0110] In some embodiments, the smart device includes electric windows and / or electric curtains, and step A4 (obtaining the operating status of each time period corresponding to each time period based on the state diagrams corresponding to different monitoring areas) specifically includes steps A41 to A46:

[0111] A41. In response to the state diagram being filled into the corresponding monitoring area, a state determination request is sent to the residential user terminal, and a scheduled task is established based on the sending time of the state determination request.

[0112] Among them, the status confirmation request represents the request sent by the system to the residential user end, which is used to prompt the user to independently input the operating status of the smart device in the status diagram; the sending time represents the specific time point when the system sends the status confirmation request to the residential user end, such as: 10:05:20 am on July 3, 2024, which can provide a reference time for the subsequent setting of scheduled tasks; the scheduled task is used to check whether the user's response is received within the pre-set time.

[0113] A42. If it is determined that the residential user terminal does not respond to the status determination request within the preset time corresponding to the scheduled task, perform image recognition on the status schematic diagram based on the scheduled task.

[0114] The preset time refers to a specific time after the reference time (sending time), such as one minute after the reference time (sending time).

[0115] For example: The sending time is 10:05:20 am on July 3, 2024, and the preset time is within one minute after the base time (sending time). It is necessary to determine whether the user starts to manually fill in and upload the relevant operations of the corresponding operating status of the smart device before 10:06:20 am on July 3, 2024.

[0116] Specifically, if the user does not start to manually fill in and upload the relevant operations corresponding to the operating status of the smart device within the preset time, it is judged that the residential user terminal has no response to the status determination request within the preset time corresponding to the scheduled task, and the image recognition technology is directly called to perform image recognition on the status schematic diagram. The image recognition technology is well known to technicians in this field and will not be described in detail here.

[0117] It should be noted that if the user has started to manually fill in and upload relevant operations corresponding to the operating status of the smart device within the preset time, it is judged that the residential user terminal has responded to the status determination request within the preset time corresponding to the scheduled task, and the operating status of the smart device manually filled in and uploaded by the user is received and stored.

[0118] A43. When the smart device is an electric window, the window frame and the opening and closing window corresponding to the electric window in the state schematic diagram are determined based on the image recognition, and the time period opening and closing angle formed between the window frame and the opening and closing window is determined.

[0119] See also Figure 3 , Figure 3 It is a schematic diagram of an electric window provided by an embodiment of the present invention.

[0120] Among them, the window frame refers to the fixed frame part of the electric window, which can be specifically made of aluminum alloy; the opening and closing window refers to the openable and closable part of the electric window, which can be specifically made of glass; the time period opening and closing angle refers to the opening and closing angle of the electric window within a specific time period.

[0121] For example: the morning period corresponds to 03:00-10:59, and the morning monitoring area of ​​the equipment monitoring interface shows the status schematic diagrams of the electric windows at 7:00, 8:35 and 9:00, respectively. Image recognition is performed on the above status schematic diagrams to obtain that the opening and closing angle formed between the window frame and the opening and closing window of the electric window at 7:00 is 40°, the opening and closing angle formed between the window frame and the opening and closing window at 8:35 is 50°, and the opening and closing angle formed between the window frame and the opening and closing window at 9:00 is 70°. The opening and closing angle corresponding to the time period of the morning monitoring area is (30°+50°+70°)÷3, that is, 50°.

[0122] A44. The opening and closing angles of each time period corresponding to different monitoring areas are determined as the operating states of each time period corresponding to each time period.

[0123] The time period operation status indicates the specific working status of the electric window in a specific time period.

[0124] Specifically, the time period opening and closing angle of the morning monitoring area is determined as the time period operation status corresponding to the morning period; the time period opening and closing angle of the noon monitoring area is determined as the time period operation status corresponding to the noon period; the time period opening and closing angle of the evening monitoring area is determined as the time period operation status corresponding to the evening period.

[0125] and / or,

[0126] A45. When the smart device is an electric curtain, the sliding track and the curtain body corresponding to the electric curtain located in the state schematic diagram are determined based on the image recognition.

[0127] See also Figure 4 , Figure 4 It is a schematic diagram of an electric curtain provided by an embodiment of the present invention.

[0128] Among them, the sliding track refers to a physical structure used to support and guide the curtain body to move horizontally or vertically, which can be installed above a wall or window, and may specifically include a guide groove, through which the curtain body slides; the curtain body refers to the actual curtain fabric or other covering material, which is installed on the sliding track, and can be driven by a motor to slide the curtain body along the sliding track.

[0129] A46. Determine the sliding distance of the curtain body on the sliding track during each period, and determine the sliding distances of each period corresponding to different monitoring areas as the operating states of each period corresponding to each period.

[0130] The time period sliding distance indicates the distance the curtain body moves along the sliding track within a specific time period; and the time period operating state indicates the specific working state of the electric curtain within a specific time period.

[0131] Specifically, the time period sliding distance of the morning monitoring area is determined as the time period operation status corresponding to the morning time period; the time period sliding distance of the noon monitoring area is determined as the time period operation status corresponding to the noon time period; the time period sliding distance of the evening monitoring area is determined as the time period operation status corresponding to the evening time period.

[0132] For example, the noon period corresponds to 11:00-18:59. The noon monitoring area of ​​the equipment monitoring interface displays the status diagrams of the electric curtains at 12:00, 14:05, 14:55 and 15:10. Then, image recognition is performed on the above status diagrams to obtain that the sliding distance of the electric curtains at 12:00 is 40 cm, the sliding distance at 14:05 is 30 cm, the sliding distance at 14:55 is 40 cm, and the sliding distance at 15:10 is 60 cm. The time period sliding distance corresponding to the noon monitoring area is (40 cm + 30 cm + 40 cm + 60 cm) ÷ 4, that is, 42.5 cm. The time period sliding distance of 42.5 cm in the noon monitoring area is determined as the time period operation status corresponding to the noon period.

[0133] This embodiment obtains the operating status of the smart device through user interaction and the shooting unit. The system divides each natural day into three time periods: morning, noon, and evening. Each time period corresponds to a monitoring area on the device monitoring interface. When the user interacts with a monitoring area, the system determines whether the current time belongs to that time period. If so, the shooting unit is triggered to capture the image of the smart device and fill it into the corresponding monitoring area. The image recognition is automatically performed through a scheduled task to determine the operating status of the smart device or the operating status of the smart device is determined based on the user's manual input. This embodiment relies on user interaction to obtain the operating status of the smart device, does not rely on complex technology and equipment, and is suitable for scenarios with limited technical conditions.

[0134] S2. Determine the outdoor temperatures corresponding to the natural days, calculate the difference between the adjacent outdoor temperatures based on the natural days, and determine the natural days whose corresponding temperature differences are within the preset temperature range as the data comparison group.

[0135] Among them, the outdoor temperature represents the ambient temperature outside the monitored residence; the difference calculation represents the subtraction of two or more values ​​to obtain the difference between them; the temperature difference represents the difference between the outdoor temperatures of two adjacent natural days; the preset temperature interval represents a pre-set temperature range, which is used to determine whether the temperature difference between adjacent natural days meets specific conditions, and the preset temperature interval can be set according to actual conditions; the data comparison group represents a filtered data set with specific attributes, which here represents two adjacent natural days with similar outdoor temperature conditions.

[0136] Specifically, the outdoor temperature of each natural day is first recorded, and then the difference in outdoor temperature between adjacent natural days is calculated, and two adjacent natural days whose difference is within a preset temperature range are grouped together to form a data comparison group, which may be one or more data comparison groups.

[0137] Example: Assume there are 7 days of monitoring data, and the outdoor temperatures are: 10℃ on the 1st day, 12℃ on the 2nd day, 11℃ on the 3rd day, 8℃ on the 4th day, 9℃ on the 5th day, 10℃ on the 6th day, and 12℃ on the 7th day. The preset temperature range is ±1℃. Calculate the outdoor temperature difference between two consecutive days: 2nd day - 1st day = 2℃, 3rd day - 2nd day = -1℃, 4th day - 3rd day = -3℃, 5th day - 4th day = 1℃, 6th day - 5th day = 1℃, 7th day - 6th day = 2℃. According to the difference, the 2nd day and the 3rd day are used as a data comparison group, the 4th day and the 5th day are used as a data comparison group, and the 5th day and the 6th day are used as a data comparison group, for a total of 3 data comparison groups, and the outdoor temperature difference of each data comparison group is within the preset temperature range of ±1℃.

[0138] It should be noted that in order to evaluate the impact of the behavior of smart devices on energy consumption, the preset temperature range needs to be set to a relatively small range, such as ±1°C, ±2°C, etc., to ensure that the outdoor ambient temperature difference is as small as possible, create a relatively consistent external environmental condition, and keep the important factor of outdoor temperature relatively stable, eliminate the potential impact of outdoor temperature changes on energy consumption, and provide a basis for subsequent more accurate analysis of the energy-saving behavior of smart devices.

[0139] In some embodiments, step S2 (determining the outdoor temperatures corresponding to each natural day, and calculating the difference between adjacent outdoor temperatures based on each natural day, and determining each natural day whose corresponding temperature difference is in a preset temperature range as a data comparison group) specifically includes steps S21 to S23.

[0140] S21. Divide the preset monitoring days to obtain a preset number of divided intervals corresponding to different date intervals, wherein the number of natural days included in each divided interval is greater than or equal to two.

[0141] The preset number indicates the number of intervals into which the total monitoring days (preset monitoring days) are divided, and each interval is called a divided interval. A divided interval corresponds to two or more natural days, and the dates in each divided interval are continuous and uninterrupted, and one date can only correspond to one divided interval.

[0142] Example: The preset monitoring days are 20 days, specifically from July 1, 2024 to July 20, 2024, and the preset number is 4. Then July 1, 2024 to July 20, 2024 is divided into 4 intervals, each with 5 natural days. The first interval is from July 1, 2024 to July 5, 2024, the second interval is from July 6, 2024 to July 10, 2024, the third interval is from July 11, 2024 to July 15, 2024, and the fourth interval is from July 16, 2024 to July 20, 2024.

[0143] S22. Determine the temperature of all natural days in the same divided interval to obtain outdoor temperatures corresponding to each natural day, and calculate the difference between adjacent outdoor temperatures based on the date sequence to obtain temperature differences.

[0144] The date sequence means arranging the natural days in order from early to late.

[0145] Specifically, the external ambient temperature corresponding to all natural days in each divided interval may be obtained through a weather station, a temperature sensor, or the like.

[0146] It should be noted that since the temperatures corresponding to adjacent natural days are generally not very different, the difference between adjacent outdoor temperatures is calculated based on the order of the dates to ensure that the difference in outdoor ambient temperature is as small as possible.

[0147] Example: The temperature sensor is used to determine the temperature of all natural days in the first division interval, and the outdoor temperature corresponding to July 1, 2024 is 12°C, the outdoor temperature corresponding to July 2, 2024 is 13°C, the outdoor temperature corresponding to July 3, 2024 is 15°C, the outdoor temperature corresponding to July 4, 2024 is 14°C, and the outdoor temperature corresponding to July 5, 2024 is 12°C. The temperature difference between two consecutive days is calculated. The temperature difference between July 1, 2024 and July 2, 2024 is 1°C, the temperature difference between July 2, 2024 and July 3, 2024 is 2°C, the temperature difference between July 3, 2024 and July 4, 2024 is -1°C, and the temperature difference between July 4, 2024 and July 5, 2024 is -2°C.

[0148] S23: When the temperature difference between two adjacent natural days is within a preset temperature range, the two natural days are determined as a data comparison group.

[0149] Specifically, the temperature difference between each day and the next day is checked. If they are within the preset temperature range, these two days are determined as a data comparison group, until the temperature differences of all adjacent days are checked and all qualified data comparison groups are determined.

[0150] For example: the preset temperature range is set to [-1℃, 1℃]. The temperature difference between July 1, 2024 and July 2, 2024 is 1℃, which is within the preset temperature range. July 1, 2024 and July 2, 2024 are determined as one data comparison group. The temperature difference between July 3, 2024 and July 4, 2024 is -1℃, which is within the preset range. July 3, 2024 and July 4, 2024 are determined as one data comparison group, for a total of 2 data comparison groups.

[0151] S3. Compare the operating states of the smart devices corresponding to each natural day in the same data comparison group, and when the comparison result indicates that the corresponding devices have different behaviors, perform difference calculation on the heat metering output values ​​corresponding to each natural day to obtain the heat metering difference.

[0152] Among them, the comparison result indicates that in the same data comparison group, the operating states of the smart devices corresponding to different natural days are compared, and the differences or the same conclusions are drawn; the difference behavior indicates that the operating states of the smart devices corresponding to different natural days in the same data comparison group are inconsistent; the heat metering output value indicates the value of thermal energy consumed or generated in a specific natural day; the difference calculation indicates the subtraction operation of two or more numerical values, which can be used to measure the changes between the heat metering output values; the heat metering difference indicates the difference between the heat metering output values ​​of the smart devices on different natural days in the same data comparison group, which can reflect the difference in thermal output or thermal energy consumption of the smart devices on different natural days.

[0153] Specifically, after determining the data comparison group, we need to further analyze the operating status of the smart devices on each natural day in the group. If it is found that there are significant differences in the operating status of the devices on certain days (i.e., differential behaviors), it is necessary to perform differential calculations on the heat metering output values ​​corresponding to these natural days. The calculated heat metering differences are used to quantitatively evaluate the impact of these differential behaviors on the energy consumption of the heating system.

[0154] It should be noted that obtaining the heat metering difference, that is, quantitatively comparing the differences in heat metering output values ​​under different smart device behaviors, can more accurately determine which behaviors are conducive to energy saving and which behaviors may lead to increased energy consumption, providing a basis for optimizing the control strategy of smart devices.

[0155] In some embodiments, step S3 (comparing the operating states of the smart devices corresponding to the natural days in the same data comparison group, and when the comparison result indicates that the corresponding behaviors are different, performing difference calculation on the heat metering output values ​​corresponding to the natural days to obtain the heat metering difference) specifically includes steps S31 to S36:

[0156] S31. When the smart device is an electric window, the opening and closing angles of the electric windows corresponding to each natural day in the same data comparison group in different time periods are calculated based on the difference in the same time period to obtain the angle differences corresponding to different time periods.

[0157] The angle difference represents the difference in opening and closing angles of the electric windows on different natural days within the same period.

[0158] Specifically, the difference between the opening and closing angles of the electric windows in the same period on different natural days is calculated.

[0159] For example, a data comparison group includes July 3, 2024 and July 4, 2024. The opening and closing angles of the electric windows in the morning period on July 3, 2024 and July 4, 2024 are 30 degrees and 35 degrees respectively, so the angle difference in the morning period is 35°-30°, that is, 5°; the opening and closing angles of the electric windows in the noon period on July 3, 2024 and July 4, 2024 are 40° and 50° respectively, so the angle difference in the noon period is 50°-40°, that is, 10°; the opening and closing angles of the electric windows in the evening period on July 3, 2024 and July 4, 2024 are 60° and 62° respectively, so the angle difference in the evening period is 62°-60°, that is, 2°.

[0160] S32: Compare each angle difference with a preset angle interval, and when any angle difference is not within the preset angle interval, determine the time period corresponding to the angle difference as corresponding to a difference behavior.

[0161] The preset angle interval represents a preset angle range, which is used to determine whether the angle difference is within a normal range. For example, if the preset angle interval is [-3°, 3°], the angle difference within this range is considered normal, and if it exceeds this range, it is considered to have abnormal behavior.

[0162] For example, the angle difference of 5° in the morning period on July 3, 2024 and July 4, 2024 is not in [-3°, 3°], so it is confirmed that there is a difference in behavior. The angle difference of 10° in the afternoon period is not in [-3°, 3°], so it is confirmed that there is a difference in behavior. The angle difference of 2° in the evening period is in [-3°, 3°], so it is confirmed to be normal. In summary, the morning period and the afternoon period on July 3, 2024 and July 4, 2024 are confirmed to have different behaviors.

[0163] and / or

[0164] S33. When the smart device is an electric curtain, the sliding distances of the electric curtains corresponding to each natural day in the same data comparison group in different time periods are calculated based on the difference of the same time period to obtain the distance differences corresponding to different time periods.

[0165] The distance difference represents the difference in sliding distances of the electric curtains on different natural days within the same period.

[0166] Specifically, the difference between the sliding distances of the electric curtains in the same period on different natural days is calculated.

[0167] For example, a data comparison group includes July 1, 2024 and July 2, 2024. The sliding distances of the electric curtains in the morning period on July 1, 2024 and July 2, 2024 are 80cm and 90cm respectively, so the distance difference in the morning period is 90cm-80cm, that is, 10cm; the sliding angles of the electric curtains in the noon period on July 1, 2024 and July 2, 2024 are 70cm and 73cm respectively, so the distance difference in the noon period is 73cm-70cm, that is, 3cm; the sliding distances of the electric curtains in the evening period on July 1, 2024 and July 2, 2024 are 60cm and 65cm respectively, so the distance difference in the evening period is 65cm-60cm, that is, 5cm.

[0168] S34: Compare each distance difference with a preset distance interval, and when any distance difference is not within the preset distance interval, determine the time period corresponding to the distance difference as corresponding to a different behavior.

[0169] The preset distance interval represents a preset distance range, which is used to determine whether the distance difference is within a normal range. For example, if the preset distance interval is [-4cm, 4cm], the distance difference within this range is considered normal, and if it exceeds this range, it is considered to have abnormal behavior.

[0170] For example, the distance difference of 10cm in the morning period of July 1, 2024 and July 2, 2024 is not in [-4cm, 4cm], so it is confirmed that there is a difference in behavior. The distance difference of 3cm in the afternoon period is in [-4cm, 4cm], so it is confirmed to be normal. The distance difference of 5cm in the evening period is not in [-4cm, 4cm], so it is confirmed that there is a difference in behavior. In summary, the morning period and evening period of July 1, 2024 and July 2, 2024 are confirmed to have different behaviors.

[0171] S35. Acquire the heat metering output value based on the different time periods corresponding to each natural day, and obtain the output values ​​of each time period corresponding to the different time periods of the same natural day.

[0172] The time period output value represents the heat value consumed or generated in a specific time period.

[0173] Example: The morning and evening periods on July 1, 2024 and July 2, 2024 are confirmed to have different behaviors. Get the heat metering output values ​​of the morning period (03:00, 04:00, 05:00, 06:00, 07:00, 08:00, 09:00, 10:00) on July 1, 2024, calculate the average value of each heat metering output value in the morning period to obtain the period output value corresponding to the morning period of July 1, 2024; get the heat metering output values ​​of the evening period (19:00, 20:00, 21:00, 22:00, 23:00, 00:00, 01:00, 02:00) on July 1, 2024, calculate the average value of each heat metering output value in the evening period to obtain the period output value corresponding to the evening period of July 1, 2024. The calculation of the output values ​​for each time period in the morning and evening on July 2, 2024 is the same as the calculation of the output values ​​for each time period in the morning and evening on July 1, 2024, and will not be repeated here.

[0174] S36, according to the date sequence, the output values ​​of each time period of each natural day in different time periods are calculated based on the difference of the same time period to obtain the heat metering difference of each time period corresponding to the different time periods.

[0175] The time period heat metering difference represents the difference in heat metering output values ​​between different dates within the same time period.

[0176] For example: the time period output value corresponding to the morning period on July 1, 2024 is 100 units, and the time period output value corresponding to the morning period on July 2, 2024 is 80 units. The time period heat metering difference corresponding to the morning period is 80 units-100 units, that is, -20 units; the time period output value corresponding to the evening period on July 1, 2024 is 90 units, and the time period output value corresponding to the evening period on July 2, 2024 is 100 units. The time period heat metering difference corresponding to the evening period is 100 units-90 units, that is, 10 units. The unit can be kilowatt-hour (kWh), joule (J) or other energy units.

[0177] S4. When the heat metering difference value decreases in a negative direction, determining a behavior attribute corresponding to the difference behavior, wherein the behavior attribute includes a positive behavior attribute and a negative behavior attribute.

[0178] Among them, negative decrease indicates that the heat metering difference is negative, that is, the heat metering output value of the next day is lower than the heat metering output value of the previous day in the same period; the behavioral attribute represents the behavior category of the smart device that affects the change of the heat metering output value; the positive behavioral attribute represents the behavioral characteristics of the smart device that can lead to reduced energy consumption and have a positive contribution to energy saving; the negative behavioral attribute represents the behavioral characteristics of the smart device that can lead to increased energy consumption and have an adverse effect on energy saving.

[0179] It should be noted that different behavioral characteristics of smart devices may correspond to different energy-saving effects. By quantitatively evaluating the changes in energy consumption caused by different behaviors, the control strategies of smart devices can be optimized more specifically to improve energy-saving effects.

[0180] S5. Determine a behavior energy-saving index based on the behavior attributes corresponding to the differential behavior and the corresponding heat metering difference.

[0181] The behavioral energy-saving index represents a quantitative evaluation indicator used to measure the contribution of specific behavioral characteristics of smart devices to energy-saving effects.

[0182] It should be noted that the purpose of determining the behavioral energy-saving index is to quantitatively evaluate the energy-saving effects of different behaviors of smart devices and to provide data support for formulating reasonable energy-saving strategies. The behavioral energy-saving index can intuitively reflect the differences in the energy-saving advantages and disadvantages of different behaviors of smart devices, and help guide users to achieve more efficient energy utilization in daily use of smart devices.

[0183] In some embodiments, step S5 (determining the behavior energy saving index based on the behavior attribute corresponding to the difference behavior and the corresponding heat metering difference) specifically includes steps S51 to S53:

[0184] S51. When the smart device is an electric window, the behavior energy saving index is determined by the following formula:

[0185]

[0186] Among them, E1 is the behavior energy-saving coefficient of the electric window under the corresponding positive behavior attribute, X is the angle difference corresponding to the difference behavior, k1 is the angle normalization value, k2 is the heat metering normalization value, H is the time period heat metering difference corresponding to the difference behavior, and a is the angle weight value.

[0187] Specifically, in order to be able to normalize the corresponding angle difference and time period heat meter difference, it is necessary to perform corresponding normalization processing on the two respectively to facilitate subsequent calculation and analysis (the unit of the angle difference is degree, and the heat meter difference is watt. The purpose of normalization is to convert the units of the two into the same numerical coefficient for easy calculation).

[0188] It should be noted that when the smart device only has electric windows, the calculation of the behavioral energy-saving index only considers the energy-saving effect of the electric windows under specific behaviors (such as adjusting the angle). The opening and closing angles of the electric windows and the corresponding opening and closing areas grow exponentially, so the corresponding exponential function is used to express it.

[0189] or,

[0190] S52: When the smart device is an electric curtain, the behavior energy saving index is determined by the following formula:

[0191]

[0192] Among them, E1 is the behavior energy-saving coefficient of the electric curtain under the corresponding positive behavior attribute, L is the distance difference corresponding to the difference behavior, k3 is the distance normalization value, k2 is the heat metering normalization value, H is the time period heat metering difference corresponding to the difference behavior, and b is the angle weight value.

[0193] Specifically, in order to be able to normalize the corresponding distance difference and time period heat measurement difference, it is necessary to perform corresponding normalization processing on the two respectively to facilitate subsequent calculation and analysis (the unit of the distance difference is centimeter or meter, and the heat measurement difference is watt. The purpose of normalization is to convert the units of the two into the same numerical coefficient to facilitate calculation).

[0194] It should be noted that when the smart device only has electric curtains, the calculation of the behavioral energy-saving index only considers the energy-saving effect of the electric curtains under specific behaviors (such as adjusting the opening and closing distance). The sliding distance of the electric curtains is proportional to the covering area, so the corresponding proportional function is used to express it.

[0195] or,

[0196] S53. When the smart devices are electric windows and electric curtains, and the electric windows and electric curtains corresponding to the same time period have different behaviors, the behavior energy-saving index is determined based on the behavior attributes of the different behaviors corresponding to the electric windows and the behavior attributes of the different behaviors corresponding to the electric curtains.

[0197] It should be noted that when electric windows and electric curtains have different behaviors in the same period, the calculation of the behavioral energy-saving index needs to comprehensively consider the behavioral attributes of the two and their contribution to the energy-saving effect.

[0198] In some embodiments, step S53 (determining the behavior energy saving index based on the behavior attribute of the difference behavior corresponding to the electric window and the behavior attribute of the difference behavior corresponding to the electric curtain) includes steps S531 to S533:

[0199] S531. When the behavior attributes of the difference behavior corresponding to the electric window and the difference behavior corresponding to the electric curtain are both positive behavior attributes, statistical calculation is performed based on E1 and E2 to obtain the behavior energy saving index.

[0200] It should be noted that when the differential behaviors of electric windows and electric curtains are both judged as positive behavior attributes, it means that both behaviors are helpful in energy saving.

[0201] or,

[0202] S532: When the behavior attribute of the difference behavior corresponding to the electric window is a positive behavior attribute and the behavior attribute of the difference behavior corresponding to the electric curtain is a negative behavior attribute, the behavior energy saving index is determined by the following formula:

[0203]

[0204] Wherein, E3 is the energy saving index of the behavior.

[0205] It should be noted that when the differential behavior of electric windows is positive and the differential behavior of electric curtains is negative, it means that the differential behavior of electric windows helps to save energy, while the differential behavior of electric curtains may increase energy consumption.

[0206] or,

[0207] S533: When the behavior attribute of the difference behavior corresponding to the electric window is a negative behavior attribute and the behavior attribute of the difference behavior corresponding to the electric curtain is a positive behavior attribute, the behavior energy saving index is determined by the following formula:

[0208]

[0209] Wherein, E3 is the energy saving index of the behavior.

[0210] It should be noted that when the differential behavior of electric windows is negative, and the differential behavior of electric curtains is positive, it means that the differential behavior of electric curtains helps to save energy, while the differential behavior of electric windows may increase energy consumption.

[0211] In this embodiment, a smart device joint control method suitable for heat metering statistics is proposed. By continuously monitoring the operating status of smart devices under the same indoor temperature conditions, comparing and analyzing the heat metering output values ​​under different operating states, identifying behaviors with energy-saving effects, and calculating the corresponding energy-saving index based on these energy-saving behaviors, an optimized smart device control solution is provided to users, helping users to achieve more efficient energy management.

[0212] like Figure 5FIG. 1 is a schematic diagram of a system of an intelligent device joint control system applicable to heat metering statistics provided by an embodiment of the present invention. The intelligent device joint control system applicable to heat metering statistics includes:

[0213] The device monitoring module is configured to perform device monitoring on the smart devices located in the monitored residence for a preset number of monitoring days at the same indoor temperature, and obtain the operating status of the smart devices on each natural day corresponding to the preset monitoring days.

[0214] The temperature comparison module is configured to determine the outdoor temperatures corresponding to each natural day, and calculate the difference between adjacent outdoor temperatures based on each natural day, and determine each natural day whose corresponding temperature difference is within a preset temperature range as a data comparison group.

[0215] The difference determination module is configured to compare the operating states of the smart devices corresponding to each natural day in the same data comparison group, and when the comparison result indicates that the corresponding behavior has a difference, perform a difference calculation on the heat metering output values ​​corresponding to each natural day to obtain a heat metering difference.

[0216] The attribute determination module is configured to determine a behavior attribute corresponding to the difference behavior when the heat metering difference value decreases in a negative direction, wherein the behavior attribute includes a positive behavior attribute and a negative behavior attribute,

[0217] The index determination module is configured to determine a behavior energy-saving index based on a behavior attribute corresponding to the differential behavior and a corresponding heat metering difference.

[0218] It should be noted that the above-mentioned intelligent device joint control system applicable to heat metering statistics can execute the intelligent device joint control method applicable to heat metering statistics provided in the embodiment of the present invention. For technical details and beneficial effects that are not fully described in the embodiment of the intelligent device joint control system applicable to heat metering statistics, please refer to the intelligent device joint control method applicable to heat metering statistics provided in the embodiment of the present invention.

[0219] Yet another embodiment of the present invention provides a computing device, comprising: at least one processor; and a memory storing program instructions, wherein the program instructions are configured to be suitable for execution by the at least one processor, and the program instructions include instructions for executing the above method.

[0220] Yet another embodiment of the present invention provides a readable storage medium storing program instructions, and when the program instructions are read and executed by a computing device, the computing device executes the above method.

[0221] Through the description of the above implementation methods, ordinary technicians in this field can clearly understand that each implementation method can be implemented by means of software plus a general hardware platform, and of course, it can also be implemented by hardware. Ordinary technicians in this field can understand that all or part of the processes in the above-mentioned embodiment method can be completed by instructing related hardware through a computer program, and the program can be stored in a computer-readable storage medium. When the program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, the storage medium can be a disk, an optical disk, a read-only memory (ROM) or a random access memory (RAM), etc.

[0222] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit them. Under the concept of the present invention, the technical features in the above embodiments or different embodiments may also be combined, the steps may be implemented in any order, and there are many other changes in different aspects of the present invention as described above, which are not provided in detail for the sake of simplicity. Although the present invention has been described in detail with reference to the aforementioned embodiments, a person of ordinary skill in the art should understand that the technical solutions described in the aforementioned embodiments may still be modified, or some of the technical features may be replaced by equivalents. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the scope of the technical solutions of the embodiments of the present application.

Claims

1. A smart device joint control method suitable for heat metering statistics, characterized in that: The following steps are involved: Under the condition of the same indoor temperature, the smart devices in the monitored residence are continuously monitored for a preset number of monitoring days, and the operating status of the smart devices on each natural day corresponding to the preset number of monitoring days is obtained; Determine the outdoor temperatures corresponding to the natural days, calculate the difference between the adjacent outdoor temperatures based on the natural days, and determine the natural days whose corresponding temperature differences are within the preset temperature range as the data comparison group; The operating states of the smart devices corresponding to the natural days in the same data comparison group are compared, and when the comparison result indicates that the corresponding behaviors are different, the heat metering output values ​​corresponding to the natural days are calculated to obtain the heat metering difference, wherein the different behaviors indicate that the operating states of the smart devices corresponding to different natural days in the same data comparison group are different; When the heat metering difference value decreases in a negative direction, a behavior attribute corresponding to the difference behavior is determined, wherein the behavior attribute includes a positive behavior attribute and a negative behavior attribute, wherein the behavior attribute represents a behavior category of the smart device that affects the change of the heat metering output value; the positive behavior attribute represents a behavior feature of the smart device that can lead to a reduction in energy consumption and has a positive contribution to energy saving; the negative behavior attribute represents a behavior feature of the smart device that can lead to an increase in energy consumption and has an adverse effect on energy saving; Determine a behavior energy-saving index based on the behavior attributes corresponding to the difference behavior and the corresponding heat metering difference, wherein the behavior energy-saving index represents a quantitative evaluation index used to measure the contribution of specific behavior characteristics of the smart device to the energy-saving effect; The smart devices in the monitored residence are continuously monitored for a preset number of monitoring days, and the operating status of the smart devices on each natural day corresponding to the preset number of monitoring days is obtained, including: Establishing data communication with the smart device based on the Internet of Things technology, and performing device monitoring on the smart device for a preset number of monitoring days; Acquire the operating status of the smart device in real time on each natural day corresponding to the preset monitoring days, and obtain the operating status at different times corresponding to the same natural day; Based on each natural day, the time period is divided into morning period, noon period and evening period, and the state fusion is performed based on the operation state of each moment in the same time period to obtain the operation state of each time period corresponding to each time period; The smart devices include electric windows and / or electric curtains; Based on the running status at each moment in the same time period, the state fusion is performed to obtain the running status of each time period corresponding to each time period, including: When the smart device is an electric window, the moment opening and closing angle of the electric window is acquired at each moment, and the moment opening and closing angle is determined as the moment operation state corresponding to the electric window; The opening and closing angles at different times are grouped to obtain time period angle groups corresponding to different time periods; The average value of the opening and closing angles at each moment in the same time period angle group is calculated, and the obtained opening and closing angles of each time period are determined as the operation states of each time period corresponding to each time period; and / or, When the smart device is an electric curtain, the moment sliding distance of the electric curtain is acquired at each moment, and the moment sliding distance is determined as the moment operating state corresponding to the electric curtain; Grouping is performed based on the sliding distances at each moment corresponding to different moments, thereby obtaining time period sliding groups corresponding to different time periods; The sliding distances at each moment in the same time period sliding group are averaged, and the obtained sliding distances of each time period are determined as the operation states of each time period corresponding to each time period; The smart devices in the monitored residence are continuously monitored for a preset number of monitoring days, and the operating status of the smart devices on each natural day corresponding to the preset number of monitoring days is obtained, including: Based on each natural day, the time period is divided into a morning time period, a noon time period and an evening time period, and a device monitoring interface corresponding to the smart device is established, wherein the device monitoring interface includes a morning monitoring area corresponding to the morning time period, a noon monitoring area corresponding to the noon time period, and an evening monitoring area corresponding to the evening time period; In response to the interaction of the residential user terminal with any monitoring area, the current time is determined, and when the current time is in a time period corresponding to the monitoring area, a shooting unit pre-set in the residential user terminal is triggered to start; Acquire a state schematic diagram obtained by the residential user end based on image acquisition of the smart device by the shooting unit, and fill the state schematic diagram into the corresponding monitoring area; Based on the state diagrams corresponding to different monitoring areas, the operation states of each time period corresponding to each time period are obtained; The smart devices include electric windows and / or electric curtains; Based on the state diagrams corresponding to different monitoring areas, the operation states of each time period corresponding to each time period are obtained, including: In response to the state diagram being filled into the corresponding monitoring area, sending a state determination request to the residential user terminal, and establishing a scheduled task based on the sending time of the state determination request; If it is determined that the residential user terminal does not respond to the status determination request within the preset time corresponding to the scheduled task, performing image recognition on the status schematic diagram based on the scheduled task; When the smart device is an electric window, a window frame and an opening and closing window corresponding to the electric window located in the state diagram are determined based on the image recognition, and a time period opening and closing angle formed between the window frame and the opening and closing window is determined; The opening and closing angles of each time period corresponding to different monitoring areas are determined as the operation states of each time period corresponding to each time period; and / or, When the smart device is an electric curtain, the sliding track and the curtain body corresponding to the electric curtain located in the state diagram are determined based on the image recognition; Determine the sliding distance of the curtain body on the sliding track in each period, and determine the sliding distances of each period corresponding to different monitoring areas as the operating states of each period corresponding to each period; The operation states of the smart devices corresponding to the natural days in the same data comparison group are compared, and when the comparison result indicates that the corresponding behaviors are different, the heat metering output values ​​corresponding to the natural days are calculated to obtain the heat metering difference, including: When the smart device is an electric window, the opening and closing angles of the electric windows at different time periods corresponding to each natural day in the same data comparison group are calculated based on the difference of the same time period to obtain the angle differences corresponding to the different time periods; Compare each angle difference with a preset angle interval, and when any angle difference is not within the preset angle interval, determine the time period corresponding to the angle difference as corresponding to a difference behavior; and / or When the smart device is an electric curtain, the sliding distances of the electric curtains in different time periods corresponding to each natural day in the same data comparison group are calculated based on the difference of the same time period to obtain the distance differences corresponding to different time periods; Compare each distance difference with a preset distance interval, and when any distance difference is not within the preset distance interval, determine the time period corresponding to the distance difference as corresponding to a difference behavior; Based on the acquisition of heat metering output values ​​in different time periods corresponding to each natural day, output values ​​of each time period corresponding to different time periods of the same natural day are obtained; According to the date sequence, the output values ​​of each time period of each natural day in different time periods are calculated based on the difference of the same time period to obtain the heat metering difference of each time period corresponding to different time periods; Determining a behavior energy saving index based on the behavior attributes corresponding to the difference behavior and the corresponding heat metering difference value includes: When the smart device is an electric window, the behavior energy saving index is determined by the following formula: Wherein, E1 is the behavior energy saving coefficient of the electric window corresponding to the positive behavior attribute, X is the angle difference corresponding to the difference behavior, k1 is the angle normalization value, k2 is the heat metering normalization value, H is the time period heat metering difference corresponding to the difference behavior, and a is the angle weight value; or, When the smart device is an electric curtain, the behavior energy saving index is determined by the following formula: Wherein, E1 is the energy-saving coefficient of the electric curtain under the positive behavior attribute, L is the distance difference corresponding to the difference behavior, k3 is the distance normalization value, k2 is the heat metering normalization value, H is the heat metering difference of the time period corresponding to the difference behavior, and b is the angle weight value; or, When the smart devices are electric windows and electric curtains, and the electric windows and electric curtains corresponding to the same time period have different behaviors, the behavior energy-saving index is determined based on the behavior attributes of the different behaviors corresponding to the electric windows and the behavior attributes of the different behaviors corresponding to the electric curtains.

2. The intelligent device joint control method suitable for heat metering statistics according to claim 1 is characterized in that: Determine the outdoor temperatures corresponding to the natural days, calculate the difference between the adjacent outdoor temperatures based on the natural days, and determine the natural days whose corresponding temperature differences are within the preset temperature range as data comparison groups, including: Dividing the preset monitoring days to obtain a preset number of divided intervals corresponding to different date intervals, wherein the number of natural days included in each divided interval is greater than or equal to two; Determine the temperature of all natural days in the same divided interval to obtain the outdoor temperatures corresponding to the natural days, and calculate the difference between adjacent outdoor temperatures based on the date sequence to obtain the temperature differences; When the temperature difference between two adjacent natural days is within a preset temperature range, the two natural days are determined as a data comparison group.

3. The intelligent device joint control method suitable for heat metering statistics according to claim 1 is characterized in that: Determining the behavior energy saving index based on the behavior attribute of the difference behavior corresponding to the electric window and the behavior attribute of the difference behavior corresponding to the electric curtain includes: When the behavior attributes of the difference behavior corresponding to the electric window and the difference behavior corresponding to the electric curtain are both positive behavior attributes, a statistical calculation is performed based on E1 and E2 to obtain the behavior energy saving index; or, When the behavior attribute of the difference behavior corresponding to the electric window is a positive behavior attribute, and the behavior attribute of the difference behavior corresponding to the electric curtain is a negative behavior attribute, the behavior energy saving index is determined by the following formula: Wherein, E3 is the energy saving index of the behavior; or, When the behavior attribute of the difference behavior corresponding to the electric window is a negative behavior attribute, and the behavior attribute of the difference behavior corresponding to the electric curtain is a positive behavior attribute, the behavior energy saving index is determined by the following formula: Wherein, E3 is the energy saving index of the behavior.

4. An intelligent equipment joint control system suitable for heat metering statistics, characterized in that: include: The device monitoring module is configured to continuously monitor the smart devices in the monitored residence for a preset number of monitoring days under the condition of the same indoor temperature, and obtain the operating status of the smart devices on each natural day corresponding to the preset number of monitoring days; The temperature comparison module is configured to determine the outdoor temperatures corresponding to the natural days, and calculate the difference between the adjacent outdoor temperatures based on the natural days, and determine the natural days whose corresponding temperature differences are within the preset temperature range as the data comparison group; The difference determination module is configured to compare the operating states of the smart devices corresponding to the respective natural days in the same data comparison group, and when the comparison result indicates that the corresponding behavior has a difference, perform a difference calculation on the heat metering output values ​​corresponding to the respective natural days to obtain a heat metering difference, wherein the difference behavior indicates that the operating states of the smart devices corresponding to different natural days in the same data comparison group are inconsistent; The attribute determination module is configured to determine the behavior attribute corresponding to the difference behavior when the heat metering difference value is negatively decreasing, wherein the behavior attribute includes a positive behavior attribute and a negative behavior attribute, wherein the behavior attribute represents the behavior category of the smart device that affects the change of the heat metering output value; the positive behavior attribute represents the behavior characteristics of the smart device that can lead to reduced energy consumption and have a positive contribution to energy saving; the negative behavior attribute represents the behavior characteristics of the smart device that can lead to increased energy consumption and have an adverse effect on energy saving; An index determination module is configured to determine a behavior energy-saving index based on the behavior attributes corresponding to the difference behavior and the corresponding heat metering difference, wherein the behavior energy-saving index represents a quantitative evaluation index for measuring the contribution of specific behavior characteristics of the smart device to the energy-saving effect; The smart devices in the monitored residence are continuously monitored for a preset number of monitoring days, and the operating status of the smart devices on each natural day corresponding to the preset number of monitoring days is obtained, including: Establishing data communication with the smart device based on the Internet of Things technology, and performing device monitoring on the smart device for a preset number of monitoring days; Acquire the operating status of the smart device in real time on each natural day corresponding to the preset monitoring days, and obtain the operating status at different times corresponding to the same natural day; Based on each natural day, the time period is divided into morning period, noon period and evening period, and the state fusion is performed based on the operation state of each moment in the same time period to obtain the operation state of each time period corresponding to each time period; The smart devices include electric windows and / or electric curtains; Based on the running status at each moment in the same time period, the state fusion is performed to obtain the running status of each time period corresponding to each time period, including: When the smart device is an electric window, the moment opening and closing angle of the electric window is acquired at each moment, and the moment opening and closing angle is determined as the moment operation state corresponding to the electric window; The opening and closing angles at different times are grouped to obtain time period angle groups corresponding to different time periods; The average value of the opening and closing angles at each moment in the same time period angle group is calculated, and the obtained opening and closing angles of each time period are determined as the operation states of each time period corresponding to each time period; and / or, When the smart device is an electric curtain, the moment sliding distance of the electric curtain is acquired at each moment, and the moment sliding distance is determined as the moment operating state corresponding to the electric curtain; Grouping is performed based on the sliding distances at each moment corresponding to different moments, thereby obtaining time period sliding groups corresponding to different time periods; The sliding distances at each moment in the same time period sliding group are averaged, and the obtained sliding distances of each time period are determined as the operation states of each time period corresponding to each time period; The smart devices in the monitored residence are continuously monitored for a preset number of monitoring days, and the operating status of the smart devices on each natural day corresponding to the preset number of monitoring days is obtained, including: Based on each natural day, the time period is divided into a morning time period, a noon time period and an evening time period, and a device monitoring interface corresponding to the smart device is established, wherein the device monitoring interface includes a morning monitoring area corresponding to the morning time period, a noon monitoring area corresponding to the noon time period, and an evening monitoring area corresponding to the evening time period; In response to the interaction of the residential user terminal with any monitoring area, the current time is determined, and when the current time is in a time period corresponding to the monitoring area, a shooting unit pre-set in the residential user terminal is triggered to start; Acquire a state schematic diagram obtained by the residential user end based on image acquisition of the smart device by the shooting unit, and fill the state schematic diagram into the corresponding monitoring area; Based on the state diagrams corresponding to different monitoring areas, the operation states of each time period corresponding to each time period are obtained; The smart devices include electric windows and / or electric curtains; Based on the state diagrams corresponding to different monitoring areas, the operation states of each time period corresponding to each time period are obtained, including: In response to the state diagram being filled into the corresponding monitoring area, sending a state determination request to the residential user terminal, and establishing a scheduled task based on the sending time of the state determination request; If it is determined that the residential user terminal does not respond to the status determination request within the preset time corresponding to the scheduled task, performing image recognition on the status schematic diagram based on the scheduled task; When the smart device is an electric window, a window frame and an opening and closing window corresponding to the electric window located in the state diagram are determined based on the image recognition, and a time period opening and closing angle formed between the window frame and the opening and closing window is determined; The opening and closing angles of each time period corresponding to different monitoring areas are determined as the operation states of each time period corresponding to each time period; and / or, When the smart device is an electric curtain, the sliding track and the curtain body corresponding to the electric curtain located in the state diagram are determined based on the image recognition; Determine the sliding distance of the curtain body on the sliding track in each period, and determine the sliding distances of each period corresponding to different monitoring areas as the operating states of each period corresponding to each period; The operation states of the smart devices corresponding to the natural days in the same data comparison group are compared, and when the comparison result indicates that the corresponding behaviors are different, the heat metering output values ​​corresponding to the natural days are calculated to obtain the heat metering difference, including: When the smart device is an electric window, the opening and closing angles of the electric windows at different time periods corresponding to each natural day in the same data comparison group are calculated based on the difference of the same time period to obtain the angle differences corresponding to the different time periods; Compare each angle difference with a preset angle interval, and when any angle difference is not within the preset angle interval, determine the time period corresponding to the angle difference as corresponding to a difference behavior; and / or When the smart device is an electric curtain, the sliding distances of the electric curtains in different time periods corresponding to each natural day in the same data comparison group are calculated based on the difference of the same time period to obtain the distance differences corresponding to different time periods; Compare each distance difference with a preset distance interval, and when any distance difference is not within the preset distance interval, determine the time period corresponding to the distance difference as corresponding to a difference behavior; Based on the acquisition of heat metering output values ​​in different time periods corresponding to each natural day, output values ​​of each time period corresponding to different time periods of the same natural day are obtained; According to the date sequence, the output values ​​of each time period of each natural day in different time periods are calculated based on the difference of the same time period to obtain the heat metering difference of each time period corresponding to different time periods; Determining a behavior energy saving index based on the behavior attributes corresponding to the difference behavior and the corresponding heat metering difference value includes: When the smart device is an electric window, the behavior energy saving index is determined by the following formula: Wherein, E1 is the behavior energy saving coefficient of the electric window corresponding to the positive behavior attribute, X is the angle difference corresponding to the difference behavior, k1 is the angle normalization value, k2 is the heat metering normalization value, H is the time period heat metering difference corresponding to the difference behavior, and a is the angle weight value; or, When the smart device is an electric curtain, the behavior energy saving index is determined by the following formula: Wherein, E1 is the energy-saving coefficient of the electric curtain under the positive behavior attribute, L is the distance difference corresponding to the difference behavior, k3 is the distance normalization value, k2 is the heat metering normalization value, H is the heat metering difference of the time period corresponding to the difference behavior, and b is the angle weight value; or, When the smart devices are electric windows and electric curtains, and the electric windows and electric curtains corresponding to the same time period have different behaviors, the behavior energy-saving index is determined based on the behavior attributes of the different behaviors corresponding to the electric windows and the behavior attributes of the different behaviors corresponding to the electric curtains.

5. A computing device comprising: at least one processor; and A memory storing program instructions, wherein the program instructions are configured to be executed by the at least one processor, and the program instructions include instructions for executing the method according to any one of claims 1 to 3.

6. A readable storage medium storing program instructions, when the program instructions are read and executed by a computing device, the computing device executes the method according to any one of claims 1 to 3.

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