Multi-connected load remote control method and equipment

Abstract

The invention relates to the technical field of air conditioner remote control, in particular to a multi-connected load remote control method and equipment, and the method comprises the steps: carrying out the data collection of a target air conditioner remote controller based on an acceleration sensor to obtain the acceleration of the target air conditioner remote controller, and carrying out the state judgment of the target air conditioner remote controller based on the acceleration; the operation state corresponding to the target air conditioner remote controller is obtained. The acceleration sensor is used for collecting the acceleration of the remote controller to judge the operation state, then the sensor group is awakened to obtain the spatio-temporal data, the spatio-temporal data is matched with the habit control set constructed by the user historical control data, personalized control command binding is achieved, the fixed mode of a traditional remote control method is broken through in the data-based mode, and the user experience is improved. And automatic adaptation and optimization control can be realized according to actual use behaviors and habits of the user.

Description

Technical Field

[0001] The present invention relates to the technical field of air conditioner remote control, and in particular to a multi-connected load remote control method and equipment. Background Art

[0002] Multi-connected load refers to a load control system consisting of multiple air-conditioning systems. In this system, multiple air-conditioning 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 preset fixed instructions and modes, and cannot be personalized according to the user's specific needs and behaviors. This means that users can only control the device in a preset manner, lacking flexibility and customization; and the control strategy of traditional methods is fixed and cannot adapt to changes in user usage behavior. If the user's habits change, such as changes in usage frequency, operating methods or environmental conditions, traditional methods may not be able to make corresponding adjustments in time, resulting in unsatisfactory control effects. Summary of the invention

[0004] The technical problem to be solved by the present invention is to overcome the disadvantages of the above-mentioned 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, including:

[0006] Based on the acceleration sensor, data of the target air conditioner remote controller is collected to obtain the acceleration of the target air conditioner remote controller, and based on the acceleration, the state of the target air conditioner remote controller is judged to obtain the operation state corresponding to the target air conditioner remote controller;

[0007] If the operation state is the use state, waking up the sensor group in the target air-conditioning remote controller, and collecting data of the target air-conditioning remote controller based on the sensor group to obtain the spatiotemporal data of the target air-conditioning remote controller;

[0008] Building a habit control set of the target user based on the historical control data of the target user, and matching the spatiotemporal data with the habit control set to obtain a habit control command;

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

[0010] Preferably, 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 includes:

[0011] It is determined whether the acceleration meets the state determination formula, wherein the state determination formula of the target air conditioner remote controller is as follows:

[0012]

[0013] Among them, t0 represents the initial moment, Δt represents the preset time window and is used to determine whether the previous acceleration is stable and close to 0, Δt1 represents the short time window when the acceleration suddenly increases, and A th represents the acceleration threshold, T th Indicates the time threshold when the acceleration is greater than the acceleration threshold, [t1, t2] indicates the time interval of acceleration change, and C indicates the lower limit threshold of acceleration;

[0014] If the acceleration satisfies the state judgment formula, it indicates that the operation state corresponding to the target air conditioner remote controller is in use state;

[0015] 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 not in use.

[0016] Preferably, 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.

[0017] Preferably, constructing the habit control set of the target user based on the historical control data of the target user includes:

[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] Among them, R represents the control record list, R ID Indicates the number of the indoor unit in the multi-connected load, AC ID Indicates the number of the indoor unit in the multi-connected load, t on Indicates the time when the control is turned on, t off Indicates the time when the shutdown control occurs, t tune represents the time when the regulation control occurs, L represents the location when the control event occurs, and e represents the environmental data when the control event occurs;

[0021] Judging the historical control data based on the control record list to obtain the biased control type of the historical control data;

[0022] The habitual control set of the target user is constructed based on the biased control type determination of the historical control data.

[0023] Preferably, judging the historical control data based on the control record list to obtain the biased control type of the historical control data includes:

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

[0025] The time interval between the start control, the stop control and the adjustment control of each control event in the control event set and the next start control, the stop control and the adjustment control is counted to obtain a time interval set corresponding to the control event set;

[0026] Determine whether each time interval in the time interval set is a fixed value, and count the number of time intervals that are fixed values;

[0027] Comparing the number of times the time interval is a fixed value with a preset number threshold;

[0028] If the number of time intervals with fixed values ​​is greater than a preset number threshold, the control event set is determined to be of the fixed interval type, that is, the bias control type of the historical control data is determined to be of the fixed interval type.

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

[0030] If the number of the time intervals that are fixed values ​​is less than or equal to a 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 a preset standard deviation threshold, the control event set is determined to be a time period similarity type, that is, the biased control type of the historical control data is a time period similarity type;

[0032] If the standard deviation is greater than or equal to a preset standard deviation threshold, it is determined that the control event set is of an unfixed type, that is, the biased control type of the historical control data is of an unfixed type.

[0033] Preferably, determining and constructing the habitual control set of the target user based on the biased control type of the historical control data includes:

[0034] If the biased control type of the historical control data is a fixed interval type, adding a preset number of control events of the target user most recently to the habitual control set;

[0035] If the biased control type of the historical control data is a time period similarity type, then control events within a specific time period and having a similar operation mode are added to the habitual control set;

[0036] If the biased control type of the historical control data is an unfixed type, the most control events within a preset time are added to the habitual control set.

[0037] Preferably, matching the spatiotemporal data with the custom control set to obtain a custom control command comprises:

[0038] The time data is extracted from the spatiotemporal data and marked as T sp , extract the time data from the habit control set and mark it as T hc ;

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

[0040] The two-dimensional matrix D is initialized to obtain a time distance matrix, wherein the initialization formula 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] Where D(i,j) represents the element in the i-th row and j-th column of the two-dimensional matrix D, min represents the minimum function, and dist(T sp (i),T hc (j)) indicates T sp (i) The i-th time point and T hc The difference between the jth time points in (j).

[0044] Preferably, matching the spatiotemporal data with the custom control set to obtain a custom control command further comprises:

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

[0046] If the element D(m,n) is less than a preset time distance threshold, it is determined that the spatiotemporal data matches the time data extracted from the habitual control set, and the habitual control command is a control command corresponding to the control event corresponding to the time data extracted from the habitual control set;

[0047] If the element D(m,n) 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.

[0048] The technical solution adopted to solve the above technical problems is: a multi-connected load remote control device, which is applicable to the multi-connected load remote control method, including:

[0049] A state judgment unit, the state judgment unit is used 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 to 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;

[0050] A data acquisition unit, wherein if the operation state is the use state, the data acquisition unit is used to wake up the sensor group in the target air-conditioning remote controller, and collect data of the target air-conditioning remote controller based on the sensor group to obtain the spatiotemporal data of the target air-conditioning remote controller;

[0051] A habit control unit, the habit control unit is used to construct a habit control set of the target user based on the historical control data of the target user, and match the spatiotemporal data with the habit control set to obtain a habit control command;

[0052] A command binding unit, wherein the command binding unit is used to bind the customary control command to a corresponding control button in the target air conditioner remote controller.

[0053] The beneficial effects of the present invention are as follows: (1) The present invention uses an acceleration sensor to collect the acceleration of the remote control to determine the operating state, and then wakes up the sensor group to obtain spatiotemporal data, and matches it with the habitual control set constructed by the user's historical control data to achieve personalized control command binding. This data-based method breaks the fixed pattern of traditional remote control methods, and can automatically adapt and optimize control according to the user's actual usage behavior and habits, embodying the concept of intelligent control and providing users with a more convenient and personalized operation experience; (2) The present invention combines acceleration data, spatiotemporal data and historical control data to fully understand the user's usage scenarios and habits from different dimensions, so that control commands suitable for the user can be generated more accurately and bound. 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 invention does not require users to perform additional adaptation operations, and can automatically adjust and customize control commands according to the user's historical data and current behavior to create a unique remote control experience for each user. This not only improves the user's operating convenience, but also improves the user's satisfaction and usage experience of the air-conditioning system. BRIEF DESCRIPTION OF THE DRAWINGS

[0054] Figure 1 A schematic flow chart of the steps of an overall method in an embodiment of the present invention;

[0055] Figure 2 A schematic diagram of the device architecture of an overall device in an embodiment of the present invention.

[0056] Figure numerals: 1. state judgment unit; 2. data collection unit; 3. habit control unit; 4. command binding unit. DETAILED DESCRIPTION

[0057] Embodiment 1, as Figure 1 As shown, the multi-connected load remote control method proposed by the present invention includes:

[0058] S1. 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, and 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;

[0059] S2. If the operation state is in use, the sensor group in the target air conditioner remote controller is awakened, and data of the target air conditioner remote controller is collected based on the sensor group to obtain spatiotemporal data of the target air conditioner remote controller;

[0060] S3, constructing a habit control set of the target user based on the historical control data of the target user, and matching the spatiotemporal data with the habit control set to obtain a habit control command;

[0061] S4. Bind the customary control command to the corresponding control button in the target air conditioner remote controller.

[0062] Embodiment 2, the multi-load remote control method proposed by the present invention, compared with embodiment 1, this embodiment further includes: judging the state of the target air conditioner remote control based on acceleration to obtain the operation state corresponding to the target air conditioner remote control, including:

[0063] A1. Determine whether the acceleration meets the state judgment formula. The state judgment formula of the target air conditioner remote controller is as follows:

[0064]

[0065] Among them, t0 represents the initial moment, Δt represents the preset time window and is used to determine whether the previous acceleration is stable and close to 0, Δt1 represents the short time window when the acceleration suddenly increases, and A th represents the acceleration threshold, T th Indicates the time threshold when the acceleration is greater than the acceleration threshold, [t1, t2] indicates the time interval of acceleration change, and C indicates the lower limit threshold of 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 in use;

[0067] A3. 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 not in use.

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

[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, constructing a habit control set of the target user based on the historical control data of the target user includes:

[0071] B1. Define the control event to obtain the control record list corresponding to the control event, where 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] Among them, R represents the control record list, R ID Indicates the number of the indoor unit in the multi-connected load, AC ID Indicates the number of the indoor unit in the multi-connected load, t on Indicates the time when the control is turned on, t off Indicates the time when the shutdown control occurs, t tune represents the time when the regulation control occurs, L represents the location when the control event occurs, and e represents the environmental data when the control event occurs;

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

[0075] B3. Determine the biased control type based on historical control data and build a habitual control set for the target user.

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

[0077] C1. Divide historical control data into control event sets based on the control record list;

[0078] C2. Counting the time interval between the start control, the stop control and the adjustment control of each control event in the control event set and the next start control, the stop control and the adjustment control, so as to obtain the time interval set corresponding to the control event set;

[0079] C3, determining whether each time interval in the time interval set is a fixed value, and counting the number of time intervals that are fixed values;

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

[0081] C5. If the number of time intervals with fixed values ​​is greater than a preset number threshold, the control event set is determined to be of the interval fixed type, that is, the bias control type of the historical control data is determined to be of the interval fixed type.

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

[0083] C6. If the number of time intervals with fixed values ​​is less than or equal to a preset number threshold, the standard deviation of the time interval set is calculated, and the standard deviation is compared with a preset standard deviation threshold;

[0084] C7. If the standard deviation is less than the preset standard deviation threshold, the control event set is determined to be a period-similar type, that is, the biased control type of the historical control data is a period-similar type;

[0085] C8. If the standard deviation is greater than or equal to the preset standard deviation threshold, the control event set is determined to be non-fixed, that is, the biased control type of the historical control data is non-fixed.

[0086] In an optional embodiment, determining and building a habitual control set of a target user based on the biased control type of historical control data includes:

[0087] D1. If the bias control type of the historical control data is fixed interval type, then add the target user's most recent preset number of control events to the habit control set;

[0088] D2. If the biased control type of the historical control data is the time period similarity type, then the control events with similar operation modes within a specific time period are added to the habitual control set;

[0089] D3. If the biased control type of the historical control data is unfixed, the most control events within the preset time are added to the habitual control set.

[0090] It should be noted that the historical control data is first divided according to time to find out those control command sequences that occur in specific time periods (such as 7 to 9 a.m. and 10 to 12 p.m. every day), and then analyze the similarity of the operating modes in these control command sequences. For example, in the period from 7 to 9 a.m., the temperature is around 26°C each time the air conditioner is turned on, and around 24°C when it is turned off, and the shutdown time interval is relatively fixed. These control command sequences with similar characteristics are added to the habit control set. The habit control set constructed in this way can more accurately reflect the control habits and modes of the target users in specific time periods, so as to carry out more accurate control and decision-making later; the historical control data is comprehensively sorted out to find out those in different Control behavior patterns with certain commonalities under different time and environmental conditions. For example, although the specific time and parameters of each control are different, they all show similar behavioral trends such as tending to quickly lower 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. Even if the specific values ​​and time are not exactly the same each time, the similarities of the behavior patterns are prominent enough to be included in the habit control set. For example, sometimes when the temperature reaches 30℃ around 3 pm, the temperature will be quickly adjusted to 26℃, and sometimes when the temperature reaches 29℃ around 4 pm, it will also be quickly adjusted to 26℃. These similar control behaviors can be classified as one and added to the habit control set.

[0091] In an optional embodiment, the spatiotemporal data is matched with the custom control set to obtain the custom control command, including:

[0092] E1. Extract time data from spatiotemporal data and mark it as T sp , extract the time data from the habit control set and mark it as T hc ;

[0093] E2. Construct a two-dimensional matrix D, where the row index of the two-dimensional matrix D represents T sp , the column index of the two-dimensional matrix D represents T hc ;

[0094] E3. Initialize the two-dimensional matrix D to obtain a time distance matrix, wherein the initialization formula of 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] Where D(i,j) represents the element in the i-th row and j-th column of the two-dimensional matrix D, min represents the minimum function, and dist(T sp (i),T hc (j)) indicates T sp (i) The i-th time point and T hc The difference between the jth time points in (j).

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

[0099] E4. Get the element D(m,n) in the last row and last column of the time distance matrix, where m represents T sp The length of T hc length, comparing the element D(m,n) with the preset time distance threshold;

[0100] E5. If the element D(m,n) is less than the preset time distance threshold, it is determined that the spatiotemporal data matches the time data extracted from the habitual control set, and the habitual control command is the control command corresponding to the control event corresponding to the time data extracted from the habitual control set;

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

[0102] Embodiment three, as Figure 2 As shown, the multi-connected load remote control device proposed by the present invention is applicable to a multi-connected load remote control method, including:

[0103] A state judgment unit 1 is used to collect data of a target air conditioner remote controller based on an acceleration sensor to obtain the acceleration of the target air conditioner remote controller, and to 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 acquisition unit 2 is used 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] A habit control unit 3, which is used to construct a habit control set of the target user based on the historical control data of the target user, and match the spatiotemporal data with the habit control set to obtain a habit control command;

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

[0107] The embodiments of the present invention are described in detail above with reference to the accompanying drawings, but the present invention is not limited thereto, and various changes can be made within the knowledge scope of technicians in the relevant technical field without departing from the purpose of the present invention.

Claims

1. A multi-connected load remote control method, characterized in that: include: Based on the acceleration sensor, data of the target air conditioner remote controller is collected to obtain the acceleration of the target air conditioner remote controller, and based on the acceleration, the state of the target air conditioner remote controller is judged to obtain the operation state corresponding to the target air conditioner remote controller; If the operation state is the use state, waking up the sensor group in the target air-conditioning remote controller, and collecting data of the target air-conditioning remote controller based on the sensor group to obtain the spatiotemporal data of the target air-conditioning remote controller; Building a habit control set of the target user based on the historical control data of the target user, and matching the spatiotemporal data with the habit control set to obtain a habit control command; The custom control command is bound to a corresponding control button in the target air conditioner remote controller.

2. The multi-connected load remote control method according to claim 1, characterized in that: The state of the target air conditioner remote controller is judged based on the acceleration to obtain the operation state corresponding to the target air conditioner remote controller, including: It is determined whether the acceleration meets the state determination formula, wherein the state determination formula of the target air conditioner remote controller is as follows: Among them, t0 represents the initial moment, Δt represents the preset time window and is used to determine whether the previous acceleration is stable and close to 0, Δt1 represents the short time window when the acceleration suddenly increases, and A th represents the acceleration threshold, T th Indicates the time threshold when the acceleration is greater than the acceleration threshold, [t1, t2] indicates the time interval of acceleration change, and C indicates the lower limit threshold of acceleration; If the acceleration satisfies the state judgment formula, it indicates that the operation state corresponding to the target air conditioner remote controller is in 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 not in use.

3. The multi-connected load remote control method according to claim 1, characterized in that: 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.

4. The multi-connected load remote control method according to claim 1, characterized in that: Constructing a habit control set of the target user based on the historical control data of the target user includes: 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: R={R ID , AND ID , [(p on , p off )∨(p tune )],L,e}; Among them, R represents the control record list, R ID Indicates the number of the indoor unit in the multi-connected load, AC ID Indicates the number of the indoor unit in the multi-connected load, t on Indicates the time when the control is turned on, t off Indicates the time when the shutdown control occurs, t tune represents the time when the regulation control occurs, L represents the location when the control event occurs, and e represents the environmental data when the control event occurs; Judging the historical control data based on the control record list to obtain the biased control type of the historical control data; The habitual control set of the target user is constructed based on the biased control type determination of the historical control data.

5. The multi-connected load remote control method according to claim 4, characterized in that: The historical control data is judged based on the control record list to obtain the biased control type of the historical control data, including: dividing the historical control data into a control event set based on the control record list; The time interval between the start control, the stop control and the adjustment control of each control event in the control event set and the next start control, the stop control and the adjustment control is counted to obtain a time interval set corresponding to the control event set; Determine whether each time interval in the time interval set is a fixed value, and count the number of time intervals that are fixed values; Comparing the number of times the time interval is a fixed value with a preset number threshold; If the number of time intervals with fixed values ​​is greater than a preset number threshold, the control event set is determined to be of the fixed interval type, that is, the bias control type of the historical control data is determined to be of the fixed interval type.

6. The multi-connected load remote control method according to claim 5, characterized in that: The historical control data is judged based on the control record list to obtain the biased control type of the historical control data, and further includes: If the number of the time intervals that are fixed values ​​is less than or equal to a preset number threshold, calculating the 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 a preset standard deviation threshold, the control event set is determined to be a time period similarity type, that is, the biased control type of the historical control data is a time period similarity type; If the standard deviation is greater than or equal to a preset standard deviation threshold, it is determined that the control event set is of an unfixed type, that is, the biased control type of the historical control data is of an unfixed type.

7. The multi-connected load remote control method according to claim 6, characterized in that: Determining and building the habitual control set of the target user based on the biased control type of the historical control data includes: If the biased control type of the historical control data is a fixed interval type, adding a preset number of control events of the target user most recently to the habitual control set; If the biased control type of the historical control data is a time period similarity type, then control events within a specific time period and having a similar operation mode are added to the habitual control set; If the biased control type of the historical control data is an unfixed type, the most control events within a preset time are added to the habitual control set.

8. The multi-connected load remote control method according to claim 7, characterized in that: Matching the spatiotemporal data with the custom control set to obtain a custom control command includes: The time data is extracted from the spatiotemporal data and marked as T sp , extract the time data from the habit control set and mark it as T hc ; Construct a two-dimensional matrix D, where the row index of the two-dimensional matrix D represents T sp , the column index of the two-dimensional matrix D represents T hc ; The two-dimensional matrix D is initialized to obtain a time distance matrix, wherein the initialization formula of the two-dimensional matrix D is as follows: D(i,j)=min{D[(i-1,j)+dist(T sp (i),T hc (j))],D[(i,j-1)+dist(T sp (i),T hc (j-1))],D[(i-1,j-1)+dist(T sp (i),T hc (j-2))]}; Where D(i,j) represents the element in the i-th row and j-th column of the two-dimensional matrix D, min represents the minimum function, and dist(T sp (i),T hc (j)) indicates T sp (i) The i-th time point and T hc The difference between the jth time points in (j).

9. The multi-connected load remote control method according to claim 8, characterized in that: Matching the spatiotemporal data with the custom control set to obtain a custom control command, further comprising: Get the element D(m,n) in the last row and last column of the time distance matrix, where m represents T sp The length of T hc length, comparing the element D(m,n) with a preset time distance threshold; If the element D(m,n) is less than a preset time distance threshold, it is determined that the spatiotemporal data matches the time data extracted from the habitual control set, and the habitual control command is a control command corresponding to the control event corresponding to the time data extracted from the habitual control set; If the element D(m,n) 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.

10. A multi-connected load remote control device, which is applicable to the multi-connected load remote control method according to any one of claims 1 to 9, characterized in that: include: A state judgment unit (1), the state judgment unit (1) being used 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 to judge the 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), the data collection unit (2) being used to wake up a sensor group in the target air-conditioning remote controller if the operation state is a use state, and to collect data on the target air-conditioning remote controller based on the sensor group, so as to obtain spatiotemporal data of the target air-conditioning remote controller; A habit control unit (3), the habit control unit (3) being used to construct a habit control set of the target user based on the historical control data of the target user, and to match the spatiotemporal data with the habit control set to obtain a habit control command; A command binding unit (4), the command binding unit (4) is used to bind the customary control command to the corresponding control button in the target air conditioner remote controller.

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