Door and window state detection method based on air conditioner
By calculating the air conditioner's set parameters and historical data, the status of doors and windows of the air conditioner can be determined. This solves the problems of hardware dependence and low detection accuracy in existing technologies, realizes efficient door and window status detection, reduces air conditioner costs, and improves comfort.
Patent Information
- Application Number
- CN202511046518.3
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-07-28
- Publication Date
- 2025-10-31
AI Technical Summary
Existing methods for detecting the condition of air-conditioned doors and windows require additional hardware or have low detection accuracy, resulting in energy waste and reduced comfort.
By acquiring the set temperature, set air volume, initial ambient temperature, initial ambient humidity, and room volume, the system uses historical air conditioning datasets and regression analysis to determine the room volume model, calculates the predicted time to reach the desired temperature, and combines this with the current ambient temperature to determine the status of doors and windows, without requiring additional hardware.
It improves the accuracy and applicability of door and window status detection, reduces air conditioner costs, and avoids misjudgments caused by room size and environmental factors.
Smart Images
Figure CN120868596A_ABST
Abstract
Description
Technical Field
[0001] This invention relates to the field of air conditioning technology, specifically to a method for detecting the status of doors and windows based on air conditioning. Background Technology
[0002] Currently, it's common for users to forget to close doors and windows while the air conditioner is running, leading to prolonged ineffective operation, energy waste, and difficulty in reaching the set indoor temperature, thus affecting comfort. Therefore, controlling air conditioner operation by detecting the status of doors and windows can prevent energy waste and provide users with a better experience.
[0003] In existing technologies, the status of doors and windows is mainly detected in two ways. For example, physical sensors (such as reed switches and infrared sensors) installed on doors and windows can be used to directly determine whether the doors and windows are closed. Alternatively, the status of doors and windows can be indirectly determined by monitoring abnormal fluctuations in environmental parameters (such as the rate of change of temperature and humidity and airflow speed).
[0004] However, the former requires additional hardware installation, which increases costs and complexity; the latter is easily affected by environmental interference, has a high misjudgment rate, and is difficult to adapt to the characteristics of different rooms and the operating conditions of air conditioning. Furthermore, some solutions only use simple fixed time threshold judgments, resulting in poor adaptability and low accuracy of the judgment method.
[0005] Accordingly, a new technical solution is needed in this field to solve the above problems. Summary of the Invention
[0006] To address at least one of the aforementioned problems in the prior art, namely, to resolve the issues of existing door and window status detection methods requiring additional hardware or having low detection accuracy, this application provides a door and window status detection method based on air conditioning, comprising:
[0007] Obtain the set temperature, set airflow, initial ambient temperature, initial ambient humidity, and room volume;
[0008] Based on the set temperature, the set air volume, the initial ambient temperature, the initial ambient humidity, and the room volume, the predicted time to reach the desired temperature is determined;
[0009] The status of doors and windows is determined based on the predicted temperature arrival time, the set temperature, and the current ambient temperature.
[0010] With the above technical solution, there is no need to add extra hardware to the air conditioner, which reduces the cost of the air conditioner. The calculation of the predicted temperature reaching time can be completed by the calculation program alone. This avoids the influence of factors such as room size, set temperature, and set air volume when determining the status of doors and windows based on the current ambient temperature after a fixed time threshold. This improves the accuracy of door and window status detection and the applicability of the detection method.
[0011] In the preferred embodiment of the above-mentioned air conditioning-based door and window status detection method, the room volume is determined based on the following method:
[0012] Based on historical air conditioning datasets and regression analysis, a room volume model was determined.
[0013] The room volume is determined based on the historical air conditioning dataset and the room volume model;
[0014] The room volume model is used to characterize the correspondence between the historical air conditioning dataset and the room volume. The historical air conditioning dataset includes multiple sets of air conditioning data, and each set of air conditioning data includes historical set temperature, historical set air volume, historical initial ambient temperature, historical initial ambient humidity, and historical actual temperature reaching time.
[0015] In the preferred embodiment of the above-mentioned air conditioning-based door and window status detection method, the room volume model is set as follows:
[0016]
[0017] Wherein, V is the room volume; k is the dynamic fitting comprehensive efficiency coefficient, generated and corrected based on the historical air conditioning dataset; P is the power, which corresponds to the historical set air volume; Treach is the historical actual temperature reaching time; c is the specific heat capacity of air; ρ is the air density, which corresponds to the historical initial ambient temperature and the historical initial ambient humidity; ΔT is the difference between the historical set temperature and the historical initial ambient temperature.
[0018] In the preferred embodiment of the above-mentioned air conditioning-based door and window status detection method, the historical air conditioning dataset is determined based on the following method:
[0019] When the air conditioner starts up and runs normally until it reaches the set temperature, record the air conditioner data for that time;
[0020] Based on multiple sets of air conditioning data, the historical air conditioning dataset is determined;
[0021] And / or
[0022] The detection method further includes:
[0023] After determining the predicted temperature arrival time, the predicted temperature arrival time is corrected based on the historical air conditioning dataset.
[0024] In the preferred embodiment of the above-mentioned air conditioning-based door and window status detection method, the step of determining the predicted temperature attainment time based on the set temperature, the set air volume, the initial ambient temperature, the initial ambient humidity, and the room volume further includes:
[0025] Based on the set temperature, the set air volume, the initial ambient temperature, the initial ambient humidity, the room volume, and the temperature reach prediction model, the predicted temperature reach time is determined;
[0026] The temperature reach prediction model is used to characterize the correspondence between the set temperature, the set air volume, the initial ambient temperature, the initial ambient humidity, the room volume, and the predicted temperature reach time.
[0027] In the preferred embodiment of the above-mentioned air conditioning-based door and window status detection method, the temperature arrival time prediction model is set as follows:
[0028]
[0029] Wherein, Texpect is the predicted time to reach the desired temperature, c is the specific heat capacity of air; ρ is the air density, which corresponds to the initial ambient temperature and the initial ambient humidity; V is the room volume; ΔT is the difference between the set temperature and the initial ambient temperature; k is the dynamic fitting comprehensive efficiency coefficient, which is generated and corrected based on the historical air conditioning dataset; and P is the power, which corresponds to the set air volume.
[0030] In the preferred embodiment of the above-mentioned air conditioning-based door and window status detection method, determining the door and window status based on the predicted temperature arrival time, the set temperature, and the current ambient temperature further includes:
[0031] Within the predicted temperature reach time, it is determined whether the current ambient temperature has reached the set temperature;
[0032] If so, the door / window status is determined to be closed; otherwise, the door / window status is determined to be open.
[0033] In the preferred embodiment of the above-mentioned air conditioning-based door and window status detection method, the detection method further includes:
[0034] Based on the status of the doors and windows, the air conditioner is selectively controlled to issue a reminder signal.
[0035] In the preferred embodiment of the above-mentioned air conditioner-based door and window status detection method, the step of selectively controlling the air conditioner to issue a reminder signal based on the door and window status further includes:
[0036] If the doors and windows are closed, the air conditioner will continue to operate.
[0037] If the doors and windows are in the open state, the air conditioner will be controlled to send a reminder signal.
[0038] In the preferred embodiment of the above-mentioned air conditioning-based door and window status detection method, the detection method further includes:
[0039] The air conditioner is controlled to operate in response to user feedback signals;
[0040] The feedback signals include door and window closing signals, status freeze signals, space update signals, and stop operation signals. Attached Figure Description
[0041] The air conditioning-based door and window status detection method of this application will be described below with reference to the accompanying drawings. In the drawings:
[0042] Figure 1 The flowchart shows the main steps of a door and window status detection method based on air conditioning, according to one embodiment of this application.
[0043] Figure 2 A flowchart illustrating the steps of determining a room volume model according to one embodiment of this application;
[0044] Figure 3 A flowchart illustrating the steps of another embodiment of the door and window status detection method based on air conditioning in this application. Detailed Implementation
[0045] Preferred embodiments of this application will now be described with reference to the accompanying drawings. Those skilled in the art should understand that these embodiments are merely illustrative of the technical principles of this application and are not intended to limit the scope of protection of this application. For example, although in this embodiment, the air conditioner interacts with the user after issuing a reminder signal, this is not intended to limit the scope of protection of this application. Those skilled in the art can make modifications as needed without departing from the principles of this application; for example, the interaction steps can be omitted.
[0046] As described in the background section, it is common for users to forget to close doors and windows when the air conditioner is running, resulting in prolonged ineffective operation and energy waste. Furthermore, the indoor temperature may not reach the set value, affecting comfort. Therefore, controlling the air conditioner's operation by detecting the status of doors and windows can prevent energy waste and provide users with a better experience.
[0047] In existing technologies, the status of doors and windows is mainly detected in two ways. For example, physical sensors (such as reed switches and infrared sensors) installed on doors and windows can be used to directly determine whether the doors and windows are closed. Alternatively, the status of doors and windows can be indirectly determined by monitoring abnormal fluctuations in environmental parameters (such as the rate of change of temperature and humidity and airflow speed).
[0048] However, the former requires additional hardware installation, which increases costs and complexity; the latter is easily affected by environmental interference, has a high misjudgment rate, and is difficult to adapt to the characteristics of different rooms and the operating conditions of air conditioning. Furthermore, some solutions only use simple fixed time threshold judgments, resulting in poor adaptability and low accuracy of the judgment method.
[0049] See below. Figure 1 The present application will now describe the door and window status detection method based on air conditioning. Figure 1 The flowchart below shows the main steps of an air-conditioning-based door and window status detection method according to one embodiment of this application. To address the problems of existing door and window status detection methods requiring additional hardware or having low detection accuracy, the air-conditioning-based door and window status detection method of this application includes the following steps:
[0050] S101, obtain the set temperature, set air volume, initial ambient temperature, initial ambient humidity and room volume;
[0051] S102 determines the predicted time to reach the desired temperature based on the set temperature, set air volume, initial ambient temperature, initial ambient humidity, and room volume;
[0052] S103 determines the status of doors and windows based on the predicted time to reach the desired temperature, the set temperature, and the current ambient temperature.
[0053] In this embodiment, the set temperature and set air volume can be manually set by the user or set by default when the unit is turned on. The initial ambient temperature and initial ambient humidity can be obtained by the temperature sensor and humidity sensor installed on the air conditioner itself. The room volume can be input by the technician during the installation of the air conditioner. The predicted temperature reaching time can be determined by a general calculation formula and the above variables. Within the predicted temperature reaching time, it can be determined whether the current ambient temperature has reached the set temperature. If so, the door and window status is determined to be closed; otherwise, the door and window status is determined to be open.
[0054] With the above technical solution, there is no need to add extra hardware to the air conditioner, which reduces the cost of the air conditioner. The calculation of the predicted temperature reaching time can be completed by the calculation program alone. This avoids the influence of factors such as room size, set temperature, and set air volume when determining the status of doors and windows based on the current ambient temperature after a fixed time threshold. This improves the accuracy of door and window status detection and the applicability of the detection method.
[0055] It should be explained that the general calculation formula is existing technology and will not be elaborated here. In addition, the setting for determining the status of doors and windows based on the predicted temperature reaching time, the set temperature, and the current ambient temperature is not static. In an alternative implementation, those skilled in the art can change the status requirement of "the current ambient temperature has reached the set temperature" as needed. For example, the current ambient temperature can be considered to have reached the set temperature when the absolute value of the difference between the current ambient temperature and the set temperature is less than a preset temperature threshold, such as 0.5 degrees Celsius.
[0056] See below. Figure 2 , Figure 2 This is a flowchart illustrating the steps involved in determining a room volume model according to one embodiment of this application.
[0057] Considering that the measurement error may be large when the room volume is manually entered by technicians or users, or that factors such as spatial layout and furnishings may affect the actual room volume, one possible implementation method is as follows: Figure 2 As shown, the room volume can be determined based on the following method:
[0058] S201, Based on historical air conditioning datasets and regression analysis, determine the room volume model;
[0059] S202, based on historical air conditioning datasets and room volume models, determines the room volume.
[0060] Among them, the room volume model is used to represent the correspondence between the historical air conditioning dataset and the room volume. The historical air conditioning dataset includes multiple sets of air conditioning data. Each set of air conditioning data includes the historical set temperature, historical set air volume, historical initial ambient temperature, historical initial ambient humidity, and historical actual temperature reaching time.
[0061] Specifically, the room volume model is set as follows:
[0062]
[0063] Where V is the room volume; k is the dynamic fitting comprehensive efficiency coefficient, generated and corrected based on historical air conditioning datasets; P is the power, which corresponds to the historical set air volume and can be obtained by looking up a table; Treach is the historical actual temperature reaching time; c is the specific heat capacity of air; ρ is the air density, which corresponds to the historical initial ambient temperature and historical initial ambient humidity; ΔT is the difference between the historical set temperature and the historical initial ambient temperature.
[0064] The historical air conditioning dataset was determined based on the following method:
[0065] Record the air conditioning data for that time when the air conditioner starts up and runs normally until the set temperature is reached;
[0066] Based on multiple sets of air conditioning data, a historical air conditioning dataset was determined.
[0067] In this embodiment, after obtaining multiple sets of air conditioning data, abnormal data can be processed. For example, Tukey's Fences can be used to remove air conditioning data corresponding to abnormal temperature arrival times. Furthermore, historical air conditioning data can be analyzed periodically or when new air conditioning data is added to the historical air conditioning dataset. Preset rules or air conditioning status information can be used to remove abnormal and unreliable actual temperature arrival time records to ensure data quality. Specific processing methods can be set based on existing technology and the needs of those skilled in the art, and will not be elaborated here. After determining the historical air conditioning dataset, sufficient air conditioning data can be used to estimate the key parameter characterizing room characteristics, namely room volume, through model fitting.
[0068] It should be explained that this embodiment only provides one possible method for handling abnormal data, but its setting is not mandatory. Those skilled in the art can change the method for handling abnormal data according to their needs, as long as it does not affect the data quality.
[0069] In one possible implementation, step S102, "determining the predicted time to reach the desired temperature based on the set temperature, set airflow, initial ambient temperature, initial ambient humidity, and room volume," further includes:
[0070] Based on the set temperature, set air volume, initial ambient temperature, initial ambient humidity, room volume, and temperature reach prediction model, the predicted temperature reach time is determined.
[0071] Among them, the time to reach temperature prediction model is used to characterize the correspondence between the set temperature, set air volume, initial ambient temperature, initial ambient humidity and room volume and the predicted time to reach temperature.
[0072] Specifically, the time to reach temperature prediction model is set as follows:
[0073]
[0074] Where Texpect is the predicted time to reach the desired temperature, c is the specific heat capacity of the air, ρ is the air density, which corresponds to the initial ambient temperature and humidity, V is the room volume, ΔT is the difference between the set temperature and the initial ambient temperature, k is the dynamic fitting comprehensive efficiency coefficient, which is generated and corrected based on historical air conditioning datasets, and P is the power, which corresponds to the set air volume and can be obtained by looking up a table.
[0075] In this embodiment, a temperature reach time prediction model can be trained using sufficient air conditioning data. When the air conditioner is started and running, the set temperature, set air volume, initial ambient temperature, initial ambient humidity, and room volume estimated from historical air conditioning datasets are input into the temperature reach time prediction model to obtain the predicted temperature reach time.
[0076] In some implementations, the detection method further includes:
[0077] After determining the predicted temperature arrival time, the predicted temperature arrival time is corrected based on historical air conditioning datasets.
[0078] In this embodiment, a correction coefficient can be determined using historical air conditioning datasets. This correction coefficient is then used to adjust the predicted temperature arrival time, adapting to different room volumes and operating conditions. The corrected predicted temperature arrival time is then used to determine the status of doors and windows. However, it should be noted that setting up the correction for the predicted time is not mandatory. In an alternative embodiment, this correction step can be omitted. In another alternative embodiment, the correction coefficient may not be based on historical air conditioning datasets. For example, those skilled in the art can experiment and pre-set a table comparing room volume and correction coefficients. After determining the predicted temperature arrival time, the correction coefficient can be obtained by looking up the table.
[0079] In some implementations, the detection method further includes:
[0080] Based on the status of doors and windows, the air conditioner can be selectively controlled to issue a reminder signal.
[0081] In this embodiment, if the doors and windows are closed, the air conditioner continues to operate; if the doors and windows are open, the air conditioner sends a reminder signal, for example, through the air conditioner display screen, a mobile app, or voice broadcast.
[0082] In some implementations, the detection method further includes:
[0083] It controls the operation of the air conditioner in response to user feedback signals;
[0084] The feedback signals include door and window closing signals, status freeze signals, space update signals, and stop operation signals.
[0085] In this implementation, when the air conditioner sends a reminder signal to the user, it can provide four options to provide feedback on the current situation. Specifically, the four feedback signals correspond to four options: The "Door and Window Closed" signal indicates that the user has closed the doors and windows, and the air conditioner can continue operating. If the user selects this option, the system confirms the reminder is lifted and allows the air conditioner to continue operating according to its original settings. The system can also briefly record this event. If the temperature reach time quickly returns to normal during subsequent operation, the confidence level is enhanced; if it is still too long, a second reminder can be issued. The "State Freeze" signal indicates that there is a need to open the doors and windows, and the air conditioner can continue operating. The system can record this event and will not trigger reminders due to excessively long temperature reach time in the present or for a period of time in the future, or it can increase the trigger threshold. The "Space Update" signal indicates that the room where the air conditioner is installed has been changed. In this case, the historical air conditioner dataset can be cleared, the room volume model reset, and relearned. The "Stop Running" signal indicates that the user has left the house and forgot to close the doors and windows. In this case, the air conditioner can be turned off or enter a low-power standby state to avoid energy waste.
[0086] It should be explained that the above settings are not static and can be modified according to the needs of those skilled in the art. In an alternative implementation, when the door and window are determined to be open, the air conditioner can be controlled to continue to operate normally and issue a reminder signal. After running for a certain period of time, if the current ambient temperature has not reached the set temperature, the air conditioner can be turned off directly.
[0087] See below. Figure 3 , Figure 3 This is a flowchart illustrating the steps of a door and window status detection method based on air conditioning, which is another embodiment of this application.
[0088] like Figure 3 As shown, in one possible implementation, the air conditioning-based door and window status detection method includes:
[0089] S301: Obtain the set temperature, set air volume, initial ambient temperature, initial ambient humidity, and room volume, and then execute S302;
[0090] S302, based on the set temperature, set air volume, initial ambient temperature, initial ambient humidity, room volume and temperature reach prediction model, determine the predicted temperature reach time, and then execute S303;
[0091] S303, Correct the predicted temperature arrival time based on the historical air conditioning dataset, and then execute S304;
[0092] S304: Within the predicted temperature reach time, determine whether the current ambient temperature has reached the set temperature. If yes, execute S307; otherwise, execute S305.
[0093] S305, control the air conditioner to send a reminder signal, and then execute S306;
[0094] S306 controls the operation of the air conditioner in response to user feedback signals;
[0095] S307 controls the air conditioner to continue running.
[0096] In this embodiment, when the air conditioner is turned on, or when the user manually sets the temperature or airflow, the set temperature, set airflow, initial ambient temperature, initial ambient humidity, and estimated room volume can be input into the temperature reach time prediction model to obtain the predicted temperature reach time. The predicted temperature reach time is then corrected based on historical air conditioning datasets. When the predicted temperature reach time is reached, it is determined whether the current ambient temperature has reached the set temperature. If so, it indicates that the air conditioner is operating normally and the doors and windows are closed. If not, it indicates that the doors and windows may be open. At this time, the air conditioner is controlled to send a reminder signal to the user and provides four options. The user selects the options to control the operation of the air conditioner. For specific interaction methods, please refer to the previous text, which will not be repeated here.
[0097] It should be noted that the order of the above steps is not fixed. Those skilled in the art can change the order of the steps or delete some steps as needed, as long as it does not affect the achievement of the purpose of this application. In one alternative embodiment, the step of correcting the predicted temperature reaching time can be omitted. In another alternative embodiment, the step of controlling the air conditioner in response to user feedback signals can be omitted. In this case, a certain period of time after the air conditioner issues the first reminder signal, it can be determined again whether the current ambient temperature has reached the set temperature. If not, the air conditioner can be directly controlled to turn off.
[0098] Those skilled in the art will understand that although some embodiments described herein include certain features included in other embodiments but not others, combinations of features from different embodiments are intended to be within the scope of this application and form different embodiments. For example, any of the claimed embodiments in the claims of this application can be used in any combination.
[0099] The technical solutions of this application have been described above with reference to the preferred embodiments shown in the accompanying drawings. However, it will be readily understood by those skilled in the art that the scope of protection of this application is obviously not limited to these specific embodiments. Without departing from the principles of this application, those skilled in the art can make equivalent changes or substitutions to the relevant technical features, and the technical solutions after these changes or substitutions will all fall within the scope of protection of this application.
Claims
1. A method for detecting the status of doors and windows based on air conditioning, characterized in that, include: Obtain the set temperature, set airflow, initial ambient temperature, initial ambient humidity, and room volume; Based on the set temperature, the set air volume, the initial ambient temperature, the initial ambient humidity, and the room volume, the predicted time to reach the desired temperature is determined; The status of doors and windows is determined based on the predicted temperature arrival time, the set temperature, and the current ambient temperature.
2. The door and window status detection method based on air conditioning according to claim 1, characterized in that, The room volume is determined based on the following method: Based on historical air conditioning datasets and regression analysis, a room volume model was determined. The room volume is determined based on the historical air conditioning dataset and the room volume model; The room volume model is used to characterize the correspondence between the historical air conditioning dataset and the room volume. The historical air conditioning dataset includes multiple sets of air conditioning data, and each set of air conditioning data includes historical set temperature, historical set air volume, historical initial ambient temperature, historical initial ambient humidity, and historical actual temperature reaching time.
3. The door and window status detection method based on air conditioning according to claim 2, characterized in that, The room volume model is set as follows: Wherein, V is the room volume; k is the dynamic fitting comprehensive efficiency coefficient, generated and corrected based on the historical air conditioning dataset; P is the power, which corresponds to the historical set air volume; Treach is the historical actual temperature reaching time; c is the specific heat capacity of air; ρ is the air density, which corresponds to the historical initial ambient temperature and the historical initial ambient humidity; ΔT is the difference between the historical set temperature and the historical initial ambient temperature.
4. The method for detecting the status of doors and windows based on air conditioning according to claim 2, characterized in that, The historical air conditioning dataset was determined based on the following method: When the air conditioner starts up and runs normally until it reaches the set temperature, record the air conditioner data for that time; Based on multiple sets of air conditioning data, the historical air conditioning dataset is determined; And / or The detection method further includes: After determining the predicted temperature arrival time, the predicted temperature arrival time is corrected based on the historical air conditioning dataset.
5. The method for detecting the status of doors and windows based on air conditioning according to claim 2, characterized in that, The determination of the predicted temperature reach time based on the set temperature, the set air volume, the initial ambient temperature, the initial ambient humidity, and the room volume further includes: Based on the set temperature, the set air volume, the initial ambient temperature, the initial ambient humidity, the room volume, and the temperature reach prediction model, the predicted temperature reach time is determined; The temperature reach prediction model is used to characterize the correspondence between the set temperature, the set air volume, the initial ambient temperature, the initial ambient humidity, the room volume, and the predicted temperature reach time.
6. The method for detecting the status of doors and windows based on air conditioning according to claim 5, characterized in that, The temperature rise time prediction model is set as follows: Wherein, Texpect is the predicted time to reach the desired temperature, c is the specific heat capacity of air; ρ is the air density, which corresponds to the initial ambient temperature and the initial ambient humidity; V is the room volume; ΔT is the difference between the set temperature and the initial ambient temperature; k is the dynamic fitting comprehensive efficiency coefficient, which is generated and corrected based on the historical air conditioning dataset; and P is the power, which corresponds to the set air volume.
7. The door and window status detection method based on air conditioning according to claim 1, characterized in that, The determination of the door and window status based on the predicted temperature arrival time, the set temperature, and the current ambient temperature further includes: Within the predicted temperature reach time, it is determined whether the current ambient temperature has reached the set temperature; If so, the door / window status is determined to be closed; otherwise, the door / window status is determined to be open.
8. The method for detecting the status of doors and windows of an air conditioner according to claim 1, characterized in that, The detection method further includes: Based on the status of the doors and windows, the air conditioner is selectively controlled to issue a reminder signal.
9. The method for detecting the status of doors and windows based on air conditioning according to claim 8, characterized in that, The selective control of the air conditioner to issue a reminder signal based on the status of the doors and windows further includes: If the doors and windows are closed, the air conditioner will continue to operate. If the doors and windows are in the open state, the air conditioner will be controlled to send a reminder signal.
10. The door and window status detection method based on air conditioning according to claim 9, characterized in that, The detection method further includes: The air conditioner is controlled to operate in response to user feedback signals; The feedback signals include door and window closing signals, status freeze signals, space update signals, and stop operation signals.