Multi-connected load remote control method and device

Abstract

The application relates to the technical field of air conditioner remote control, in particular to a multi-connected load remote control method and device, which comprises the following steps: collecting data of a target air conditioner remote controller based on an acceleration sensor to obtain the acceleration of the target air conditioner remote controller; judging the state of the target air conditioner remote controller based on the acceleration to obtain the operation state corresponding to the target air conditioner remote controller. The application judges the operation state by collecting the acceleration of the remote controller through the acceleration sensor, then wakes up the sensor group to acquire space-time data, and matches the habit control set constructed by the historical control data of the user, so that the personalized control command binding is realized. The data-based mode breaks the fixed mode of the traditional remote control method, and can automatically adapt and optimize the control according to the actual use behavior and habit of the user.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of air conditioner remote control, in particular to a multi-connected load remote control method and device. BACKGROUND

[0002] Multi-connected load refers to a load control system composed of multiple air conditioning systems. In such a system, multiple air conditioner indoor units are connected together through an outdoor unit and managed and controlled by a central control system.

[0003] Traditional remote control methods usually operate based on pre-set fixed instructions and patterns, which cannot be personalized according to the specific needs and behaviors of users. This means that users can only control the device in a pre-set way, lacking flexibility and customization. Moreover, the control strategy of traditional methods is fixed and cannot adapt to changes in user behavior. If the user's habits change, such as changes in frequency of use, operation method or environmental conditions, the traditional method may not be able to make timely adjustments, resulting in unsatisfactory control effect. SUMMARY

[0004] The technical problem to be solved by the present application is to overcome the shortcomings of the prior art and provide a multi-connected load remote control method and device.

[0005] The technical solution adopted to solve the above technical problems is a multi-connected load remote control method, comprising:

[0006] Data acquisition is performed on the target air conditioner remote control based on an acceleration sensor to obtain the acceleration of the target air conditioner remote control, and state judgment is performed on the target air conditioner remote control based on the acceleration to obtain the operation state corresponding to the target air conditioner remote control.

[0007] If the operation state is a use state, a sensor group in the target air conditioner remote control is woken up, data acquisition is performed on the target air conditioner remote control based on the sensor group to obtain the space-time data of the target air conditioner remote control.

[0008] A habit control set of the target user is constructed based on the historical control data of the target user, the space-time data is matched with the habit control set to obtain a habit control command.

[0009] The habit control command is bound to the corresponding control button in the target air conditioner remote control.

[0010] Preferably, the state judgment on the target air conditioner remote control based on the acceleration to obtain the operation state corresponding to the target air conditioner remote control comprises:

[0011] determine whether the acceleration conforms to a state determination formula, wherein the state determination formula of the target air conditioner remote controller is as follows:

[0012]

[0013] wherein t0 represents an initial time, Δt represents a preset time window, and is used to determine whether the acceleration before is stably close to 0, Δt1 represents a short time window in which the acceleration suddenly increases, A th represents an acceleration threshold value, T th represents a time threshold value in which the acceleration is greater than the acceleration threshold value, [t1, t2] represents a time interval in which the acceleration changes, and C represents an acceleration lower threshold value.

[0014] If the acceleration conforms to the state determination formula, it indicates that the operation state corresponding to the target air conditioner remote controller is a use state.

[0015] If the acceleration does not conform to the state determination formula, it indicates that the operation state corresponding to the target air conditioner remote controller is a non-use state.

[0016] Preferably, the space-time data of the target air conditioner remote controller includes positioning data, environmental data and time data, wherein the environmental data includes temperature data and humidity data.

[0017] Preferably, the habit control set of the target user is constructed based on historical control data of the target user, including:

[0018] A control event is defined to obtain a control record list corresponding to the control event, wherein the expression of the control record list is as follows:

[0019] R = {R ID , AC ID , [(t on , t off ) ∨ (t tune )], L, e};

[0020] wherein R represents the control record list, R ID represents the number of indoor units in the multi-connected load, AC ID represents the number of indoor units in the multi-connected load, t on represents a time at which the opening control occurs, t off represents a time at which the closing control occurs, t tune represents a time at which the adjusting control occurs, L represents a position at which the control event occurs, and e represents environmental data at which the control event occurs.

[0021] judging the historical control data based on the control record list to obtain a bias control type of the historical control data;

[0022] determining a habit control set of the target user based on the bias control type of the historical control data.

[0023] Preferably, the judging the historical control data based on the control record list to obtain a bias control type of the historical control data comprises:

[0024] dividing the historical control data into a control event set based on the control record list;

[0025] counting the time interval of the opening control, the closing control, the adjusting control and the next opening control, the next closing control and the next adjusting control of each control event in the control event set to obtain a time interval set corresponding to the control event set;

[0026] judging whether each time interval in the time interval set is a fixed value and counting the number of time intervals being the fixed value;

[0027] comparing the number of time intervals being the fixed value with a preset number threshold;

[0028] if the number of time intervals being the fixed value is greater than the preset number threshold, determining that the control event set is interval-fixed type, i.e. determining that the bias control type of the historical control data is interval-fixed type.

[0029] Preferably, the judging the historical control data based on the control record list to obtain a bias control type of the historical control data further comprises:

[0030] if the number of time intervals being the fixed value is less than or equal to the preset number threshold, calculating the standard deviation of the time interval set and comparing the standard deviation with a preset standard deviation threshold;

[0031] if the standard deviation is less than the preset standard deviation threshold, determining that the control event set is time period similar type, i.e. the bias control type of the historical control data is time period similar type;

[0032] if the standard deviation is greater than or equal to the preset standard deviation threshold, determining that the control event set is not fixed type, i.e. the bias control type of the historical control data is not fixed type.

[0033] Preferably, the determining a habit control set of the target user based on the bias control type of the historical control data comprises:

[0034] If the bias control type of the historical control data is interval fixed type, the target user's latest preset number of control events are added to the habit control set;

[0035] If the bias control type of the historical control data is time period similar type, control events in a specific time period and with similar operation modes are added to the habit control set;

[0036] If the bias control type of the historical control data is not fixed type, the most control events in a preset time are added to the habit control set.

[0037] Preferably, the spatio-temporal data is matched with the habit control set to obtain a habit control command, comprising:

[0038] extracting time data from the spatio-temporal data and marking as T sp extracting time data from the habit control set and marking as T hc ;

[0039] constructing a two-dimensional matrix D, wherein the row index of the two-dimensional matrix D represents T sp , and the column index of the two-dimensional matrix D represents T hc ;

[0040] initializing the two-dimensional matrix D to obtain a time distance matrix, wherein the formula of the initialization of the two-dimensional matrix D is as follows:

[0041] D(i,j) = min{D[(i-1,j)+dist(T sp (i),T hc (j))],D[(i,j-1)+

[0042] dist(T sp (i),T hc (j-1))],D[(i-1,j-1)+dist(T sp (i),T hc (j-2))]};

[0043] wherein D(i,j) represents the element of the i-th row and the j-th column in the two-dimensional matrix D, min represents the minimum value function, and dist(T sp (i),T hc (j)) represents the difference between the i-th time point in T sp (i) and the j-th time point in T hc (j).

[0044] Preferably, the spatio-temporal data is matched with the habit control set to obtain a habit control command, further comprising:

[0045] obtaining an element D(m, n) in a last row and a last column of the time distance matrix, wherein m represents a length of T sp , n represents a length of T hc , comparing the element D(m, n) with a preset time distance threshold value;

[0046] if the element D(m, n) is less than the preset time distance threshold value, determining that the space-time data matches the extracted time data in the habit control set, and the habit control command is a control command corresponding to a control event corresponding to the extracted time data in the habit control set;

[0047] if the element D(m, n) is greater than or equal to the preset time distance threshold value, extracting a next time data from the habit control set, and repeating the above operation.

[0048] The technical scheme adopted to solve the above technical problems is: a multi-connected load remote control device, which is suitable for the multi-connected load remote control method, comprising:

[0049] a state judgment unit, the state judgment unit is used for collecting data of a target air conditioner remote controller based on an acceleration sensor to obtain acceleration of the target air conditioner remote controller, and judging a state of the target air conditioner remote controller based on the acceleration to obtain an operation state corresponding to the target air conditioner remote controller;

[0050] a data collection unit, the data collection unit is used for waking up a sensor group in the target air conditioner remote controller if the operation state is a use state, collecting data of the target air conditioner remote controller based on the sensor group to obtain space-time data of the target air conditioner remote controller;

[0051] a habit control unit, the habit control unit is used for constructing a habit control set of a target user based on historical control data of the target user, and matching the space-time data with the habit control set to obtain a habit control command;

[0052] a command binding unit, the command binding unit is used for binding the habit control command to a corresponding control button in the target air conditioner remote controller.

[0053] The beneficial effects of the present application are as follows: (1) The present application determines the operation state by accelerating the acceleration sensor to collect the acceleration of the remote controller, and then wakes up the sensor group to obtain the space-time data, and matches with the habit control set constructed by the user's historical control data to realize the binding of personalized control commands. This data-based method breaks the fixed mode of the traditional remote control method, can automatically adapt and optimize the control according to the actual use behavior and habit of the user, embodies the concept of intelligent control, and provides more convenient and personalized operation experience for the user; (2) The present application combines acceleration data, space-time data and historical control data to comprehensively understand the use situation and habit of the user from different dimensions, so as to more accurately generate control commands suitable for the user and bind them. This multi-source data fusion method provides a richer information basis for remote control, which helps to improve the accuracy and adaptability of control; (3) The present application does not require the user to perform additional adaptation operation, can automatically adjust and customize the control command according to the historical data and current behavior of the user, and creates a dedicated remote control experience for each user. This improves the user operation convenience, and also improves the user's satisfaction and use experience of the air conditioning system. BRIEF DESCRIPTION OF DRAWINGS

[0054] Figure 1 A step flow diagram of the overall method in an embodiment proposed by the present application is shown in the figure;

[0055] Figure 2 A device architecture diagram of the overall device in an embodiment proposed by the present application is shown in the figure.

[0056] The figure shows: 1, state judgment unit; 2, data acquisition unit; 3, habit control unit; 4, command binding unit. DETAILED DESCRIPTION

[0057] Embodiment one, as shown in the figure, the multi-connected load remote control method proposed by the present application comprises: Figure 1 S1, data acquisition is performed on the target air conditioner remote controller based on the acceleration sensor to obtain the acceleration of the target air conditioner remote controller, and state judgment is performed on the target air conditioner remote controller based on the acceleration to obtain the operation state corresponding to the target air conditioner remote controller;

[0058] S2, if the operation state is the use state, the sensor group in the target air conditioner remote controller is woken up, and data acquisition is performed on the target air conditioner remote controller based on the sensor group to obtain the space-time data of the target air conditioner remote controller;

[0059] S3, the habit control set of the target user is constructed based on the historical control data of the target user, and the space-time data is matched with the habit control set to obtain the habit control command;

[0060]

[0061] ​S4, binding the habit control command to the corresponding control button of the target air conditioner remote controller.

[0062] In the second embodiment, the multi-connected load remote control method further comprises: judging the state of the target air conditioner remote controller based on the acceleration to obtain the operation state corresponding to the target air conditioner remote controller, including:

[0063] A1, judging whether the acceleration meets the state judgment formula, wherein the state judgment formula of the target air conditioner remote controller is as follows:

[0064]

[0065] wherein t0 represents the initial time, Δt represents the preset time window, and is used to judge whether the acceleration before the judgment is stable and close to 0, Δt1 represents a short time window in which the acceleration suddenly increases, A th represents the acceleration threshold, T th represents the time threshold in which the acceleration is greater than the acceleration threshold, [t1, t2] represents the time interval in which the acceleration changes, and C represents the lower limit threshold of the acceleration.

[0066] A2, if the acceleration meets the state judgment formula, it indicates that the operation state corresponding to the target air conditioner remote controller is the use state.

[0067] A3, if the acceleration does not meet the state judgment formula, it indicates that the operation state corresponding to the target air conditioner remote controller is the non-use state.

[0068] In this embodiment, there is a time interval [t1, t2], so that before t1, the acceleration is relatively stable and close to 0 (such as the absolute value is less than a certain small constant C), at t1, the acceleration suddenly increases and a(t1)>A th , and the acceleration continues to remain in A th for a period of time from t1 to t2, and the above time exceeds T th , it is determined that the operation state corresponding to the target air conditioner remote controller is the use state.

[0069] In an optional embodiment, the spatiotemporal data of the target air conditioner remote controller includes positioning data, environmental data and time data, wherein the environmental data includes temperature data and humidity data.

[0070] In an optional embodiment, the habit control set of the target user is constructed based on the historical control data of the target user, including:

[0071] B1, defining the control event to obtain the control record list corresponding to the control event, wherein the expression of the control record list is as follows:

[0072] R = {R ID , AC ID , [(t on , t off ) ∨ (t tune )], L, e};

[0073] wherein, R represents a control record list, R ID represents a number of indoor units in a multi-connected load, AC ID represents a number of indoor units in a multi-connected load, t on represents a time when the opening control occurs, t off represents a time when the closing control occurs, t tune represents a time when the adjustment control occurs, L represents a location when the control event occurs, and e represents environmental data when the control event occurs;

[0074] B2, judging the historical control data based on the control record list to obtain a biased control type of the historical control data;

[0075] B3, determining a habit control set of the target user based on the biased control type of the historical control data.

[0076] In an optional embodiment, the judging the historical control data based on the control record list to obtain a biased control type of the historical control data comprises:

[0077] C1, dividing the historical control data into a control event set based on the control record list;

[0078] C2, counting a time interval of an opening control, a closing control, and an adjustment control of each control event in the control event set and a time interval of a next opening control, a next closing control, and a next adjustment control to obtain a time interval set corresponding to the control event set;

[0079] C3, judging whether each time interval in the time interval set is a fixed value and counting a number of the time intervals being the fixed value;

[0080] C4, comparing the number of the time intervals being the fixed value with a preset number threshold;

[0081] C5, if the number of the time intervals being the fixed value is greater than the preset number threshold, determining that the control event set is an interval-fixed type, i.e., determining that the biased control type of the historical control data is the interval-fixed type.

[0082] In an optional embodiment, the judging the historical control data based on the control record list to obtain a biased control type of the historical control data further comprises:

[0083] C6, if the number of time intervals is less than or equal to a preset number threshold, calculating a standard deviation of the set of time intervals, and comparing the standard deviation with a preset standard deviation threshold;

[0084] C7, if the standard deviation is less than the preset standard deviation threshold, determining that the set of control events is of a time period similar type, i.e., the bias control type of the historical control data is of a time period similar type;

[0085] C8, if the standard deviation is greater than or equal to the preset standard deviation threshold, determining that the set of control events is of a non-fixed type, i.e., the bias control type of the historical control data is of a non-fixed type.

[0086] In an optional embodiment, the habit control set of the target user is determined based on the bias control type of the historical control data, comprising:

[0087] D1, if the bias control type of the historical control data is of an interval fixed type, adding the latest preset number of control events of the target user to the habit control set;

[0088] D2, if the bias control type of the historical control data is of a time period similar type, adding control events within a specific time period and having a similar operation mode to the habit control set;

[0089] D3, if the bias control type of the historical control data is of a non-fixed type, adding the most control events within a preset time to the habit control set.

[0090] It should be noted that the historical control data is first divided according to time, and control command sequences occurring in a specific time period (such as 7:00-9:00 am, 10:00-12:00 pm, etc.) are found, and then the similarity of the operation mode in these control command sequences is analyzed, such as in the time period from 7:00 am to 9:00 am, the temperature is around 26℃ when the air conditioner is turned on each time, and the temperature is around 24℃ when it is turned off, and the off time interval is also relatively fixed, so these control command sequences with similar characteristics are added to the habit control set, and the habit control set constructed in this way can more accurately reflect the control habits and modes of the target user in a specific time period, so as to make more accurate control and decision-making in the future; the historical control data is comprehensively sorted out, and control behavior modes with certain commonality under different time and different environmental conditions are found, such as although the specific time and parameters of each control are different, they all show similar behavior trends such as tending to quickly reduce the temperature when the temperature is high and tending to slowly increase the temperature when the temperature is low; the command sequences corresponding to these control behaviors with common trends are extracted, that is, although the specific values and times are not exactly the same, the similarity of the behavior mode is enough to be included in the habit control set, for example, sometimes the temperature is quickly adjusted to 26℃ when the temperature reaches 30℃ at about 3:00 pm, and sometimes the temperature is quickly adjusted to 26℃ when the temperature reaches 29℃ at about 4:00 pm, and these similar control behaviors can be classified and added to the habit control set.

[0091] In an optional embodiment, the spatiotemporal data is matched with the habit control set to obtain habit control commands, comprising:

[0092] E1, extracting time data from the spatiotemporal data and marking it as T sp , extracting time data from the habit control set and marking it as T hc ;

[0093] E2, constructing a two-dimensional matrix D, wherein the row index of the two-dimensional matrix D represents T sp , and the column index of the two-dimensional matrix D represents T hc ;

[0094] E3, initializing the two-dimensional matrix D to obtain a time distance matrix, wherein the formula for initializing the two-dimensional matrix D is as follows:

[0095] D(i,j)=min{D[(i-1,j)+dist(T sp (i),T hc (j))],D[(i,j-1)+

[0096] dist(T sp (i),T hc(j-1))], D[(i-1,j-1)+dist(T sp (i), T hc (j-2))]};

[0097] wherein D(i,j) represents an element in the i-th row and the j-th column of the two-dimensional matrix D, min represents a minimum function, dist(T sp (i), T hc (j)) represents a difference between the i-th time point in T sp (i) and the j-th time point in T hc (j).

[0098] In an optional embodiment, matching the spatiotemporal data with the habit control set to obtain the habit control command further comprises:

[0099] E4, obtaining an element D(m,n) in the last row and the last column of the time distance matrix, wherein m represents the length of T sp , n represents the length of T hc , and comparing the element D(m,n) with a preset time distance threshold value;

[0100] E5, if the element D(m,n) is less than the preset time distance threshold value, determining that the spatiotemporal data matches the extracted time data in the habit control set, and the habit control command is a control command corresponding to a control event corresponding to the extracted time data in the habit control set;

[0101] E6, if the element D(m,n) is greater than or equal to the preset time distance threshold value, extracting the next time data from the habit control set, and repeating the above operation.

[0102] Embodiment three, as shown in Figure 2 The application provides a multi-connected load remote control device and a multi-connected load remote control method.

[0103] The state judgment unit 1 is configured to collect data of the target air conditioner remote controller based on the acceleration sensor to obtain the acceleration of the target air conditioner remote controller, and judge the state of the target air conditioner remote controller based on the acceleration to obtain the operation state corresponding to the target air conditioner remote controller.

[0104] The data collection unit 2 is configured to wake up the sensor group in the target air conditioner remote controller if the operation state is the use state, and collect data of the target air conditioner remote controller based on the sensor group to obtain the spatiotemporal data of the target air conditioner remote controller.

[0105] The habit control unit 3 is configured to construct a habit control set of the target user based on historical control data of the target user, and match the spatio-temporal data with the habit control set to obtain a habit control command.

[0106] The command binding unit 4 is configured to bind the habit control command to a corresponding control button in the target air conditioner remote controller.

[0107] The above detailed description of the embodiments of the present application is made in conjunction with the accompanying drawings, but the present application is not limited thereto, and various changes can be made within the knowledge of those skilled in the art without departing from the spirit of the present application.

Claims

1. A method for remote control of a multi-connected load, characterized in that, The method comprises the following steps: Data acquisition is performed on the target air conditioner remote controller based on an acceleration sensor to obtain the acceleration of the target air conditioner remote controller, and state judgment is performed on the target air conditioner remote controller based on the acceleration to obtain the operation state corresponding to the target air conditioner remote controller; If the operation state is a use state, a sensor group in the target air conditioner remote controller is woken up, and data acquisition is performed on the target air conditioner remote controller based on the sensor group to obtain the space-time data of the target air conditioner remote controller; A habit control set of a target user is constructed based on historical control data of the target user, and the space-time data is matched with the habit control set to obtain a habit control command; The habit control command is bound to a corresponding control button in the target air conditioner remote controller; The method for constructing the habit control set of the target user based on the historical control data of the target user comprises the following steps: A control event is defined to obtain a control record list corresponding to the control event, wherein the expression of the control record list is as follows: ； wherein, represents a control record list, represents a number of an indoor unit in a multi-connected load, represents a number of an indoor unit in a multi-connected load, represents a time when the opening control occurs, represents a time when the closing control occurs, represents a time when the adjustment control occurs, represents a location when the control event occurs, represents environmental data when the control event occurs; The historical control data is judged based on the control record list to obtain the bias control type of the historical control data; The habit control set of the target user is constructed based on the bias control type of the historical control data; The state judgment of the target air conditioner remote controller based on the acceleration comprises the following steps: It is judged whether the acceleration conforms to a state judgment formula, wherein the state judgment formula of the target air conditioner remote controller is as follows: ； wherein, denotes an initial time point, denotes a preset time window, and is used to determine whether the previous acceleration is stably close to 0, denotes a short time window in which the acceleration suddenly increases, denotes an acceleration threshold value, denotes a time threshold value in which the acceleration is greater than the acceleration threshold value, denotes a time interval of acceleration change, denotes an acceleration lower threshold value; If the acceleration conforms to the state judgment formula, it indicates that the operation state corresponding to the target air conditioner remote controller is a use state; If the acceleration does not conform to the state judgment formula, it indicates that the operation state corresponding to the target air conditioner remote controller is a non-use state; The space-time data of the target air conditioner remote controller comprises positioning data, environmental data and time data, wherein the environmental data comprises temperature data and humidity data; The judgment of the historical control data based on the control record list to obtain the bias control type of the historical control data comprises the following steps: The historical control data is divided into a control event set based on the control record list; The time interval of the opening control, the closing control and the adjusting control of each control event in the control event set and the time interval of the next opening control, the next closing control and the next adjusting control are counted to obtain a time interval set corresponding to the control event set; It is judged whether each time interval in the time interval set is a fixed value, and the number of time intervals that are fixed values is counted; The number of time intervals that are fixed values is compared with a preset number threshold; If the number of time intervals that are fixed values is greater than the preset number threshold, it is determined that the control event set is an interval fixed type, that is, it is determined that the bias control type of the historical control data is an interval fixed type; The judgment of the historical control data based on the control record list to obtain the bias control type of the historical control data further comprises the following steps: If the number of time intervals is less than or equal to a preset number threshold, a standard deviation of the set of time intervals is calculated, and the standard deviation is compared with a preset standard deviation threshold; If the standard deviation is less than the preset standard deviation threshold, it is determined that the set of control events is of a time period similar type, i.e., the biased control type of the historical control data is of a time period similar type; If the standard deviation is greater than or equal to the preset standard deviation threshold, it is determined that the set of control events is of a non-fixed type, i.e., the biased control type of the historical control data is of a non-fixed type.

2. The multi-connected load remote control method according to claim 1, characterized by, Based on the biased control type of the historical control data, a habit control set of the target user is constructed, including: If the biased control type of the historical control data is of an interval fixed type, a preset number of latest control events of the target user are added to the habit control set; If the biased control type of the historical control data is of a time period similar type, control events within a specific time period and having similar operation modes are added to the habit control set; If the biased control type of the historical control data is of a non-fixed type, the most control events within a preset time are added to the habit control set.

3. The multi-connected load remote control method according to claim 2, wherein The spatio-temporal data is matched with the habit control set to obtain a habit control command, including: extracting time data from the spatiotemporal data and labeling as extracting time data from the habit control set and labeling as ; constructing a two-dimensional matrix wherein a row index of the two-dimensional matrix represents a column index of the two-dimensional matrix represents ; The two-dimensional matrix is initialized to obtain a time distance matrix, wherein the two-dimensional matrix is initialized according to the following formula: ； wherein, denotes a two-dimensional matrix the element in the row and the column, denotes a minimum function, denotes the element in the time point and the difference between the time point.

4. The multi-connected load remote control method according to claim 3, wherein The spatio-temporal data is matched with the habit control set to obtain a habit control command, further including: obtaining an element in the last row and the last column of the time distance matrix wherein, denotes a length of, denotes a length of, comparing the element with a preset time distance threshold value; if the element is less than a preset time distance threshold, it is determined that the spatio-temporal data matches the extracted time data in the habit control set, and the habit control command is the control command corresponding to the control event corresponding to the extracted time data in the habit control set; If the element is greater than or equal to a preset time distance threshold, the next time data is extracted from the habit control set, and the above operation is repeated.

5. A multi-connected load remote control device suitable for the multi-connected load remote control method according to any one of claims 1 to 4, characterized by, including: A state judgment unit (1) is configured to collect data of a target air conditioner remote controller based on an acceleration sensor to obtain an acceleration of the target air conditioner remote controller, and judge a state of the target air conditioner remote controller based on the acceleration to obtain an operation state corresponding to the target air conditioner remote controller; A data collection unit (2) is configured to wake up a sensor group in the target air conditioner remote controller if the operation state is a use state, and collect data of the target air conditioner remote controller based on the sensor group to obtain spatio-temporal data of the target air conditioner remote controller; A habit control unit (3) is configured to construct a habit control set of a target user based on historical control data of the target user, and match the spatio-temporal data with the habit control set to obtain a habit control command; A command binding unit (4) is configured to bind the habit control command to a corresponding control button in the target air conditioner remote controller. The habit control set of the target user is constructed based on the historical control data of the target user, including: A control event is defined to obtain a control record list corresponding to the control event, wherein an expression of the control record list is as follows: ； wherein, represents a control record list, represents a number of an indoor unit in a multi-connected load, represents a number of an indoor unit in a multi-connected load, represents a time when the opening control occurs, represents a time when the closing control occurs, represents a time when the adjustment control occurs, represents a location when the control event occurs, represents environmental data when the control event occurs; The historical control data is judged based on the control record list to obtain a biased control type of the historical control data; The habit control set of the target user is constructed based on the biased control type of the historical control data; Judging a state of the target air conditioner remote controller based on the acceleration to obtain an operation state corresponding to the target air conditioner remote controller, comprising: Judging whether the acceleration conforms to a state judging formula, wherein the state judging formula of the target air conditioner remote controller is as follows: ； wherein, denotes an initial time point, denotes a preset time window, and is used to determine whether the previous acceleration is stably close to 0, denotes a short time window in which the acceleration suddenly increases, denotes an acceleration threshold value, denotes a time threshold value in which the acceleration is greater than the acceleration threshold value, denotes a time interval of acceleration change, denotes a lower acceleration threshold value; If the acceleration conforms to the state judging formula, it indicates that the operation state corresponding to the target air conditioner remote controller is a use state; If the acceleration does not conform to the state judging formula, it indicates that the operation state corresponding to the target air conditioner remote controller is a non-use state; The space-time data of the target air conditioner remote controller comprises positioning data, environmental data and time data, wherein the environmental data comprises temperature data and humidity data; Judging the historical control data based on the control record list to obtain a biased control type of the historical control data, comprising: Dividing the historical control data into a control event set based on the control record list; Counting time intervals of opening control, closing control and adjusting control and next opening control, closing control and adjusting control of each control event in the control event set to obtain a time interval set corresponding to the control event set; Judging whether each time interval in the time interval set is a fixed value and counting a number of time intervals being fixed values; Comparing the number of time intervals being fixed values with a preset number threshold; If the number of time intervals being fixed values is greater than the preset number threshold, it is determined that the control event set is interval fixed type, i.e. the biased control type of the historical control data is interval fixed type; Judging the historical control data based on the control record list to obtain a biased control type of the historical control data, further comprising: If the number of time intervals being fixed values is less than or equal to the preset number threshold, calculating a standard deviation of the time interval set and comparing the standard deviation with a preset standard deviation threshold; If the standard deviation is less than the preset standard deviation threshold, it is determined that the control event set is time period similar type, i.e. the biased control type of the historical control data is time period similar type; If the standard deviation is greater than or equal to the preset standard deviation threshold, it is determined that the control event set is not fixed type, i.e. the biased control type of the historical control data is not fixed type.

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