Intelligent terminal controller and control method for intelligent air conditioner

Abstract

This invention relates to the field of air conditioning control technology, specifically to an intelligent terminal controller and control method for a smart air conditioner. The controller includes an image acquisition module, an instruction pairing module, a parameter adjustment module, and an execution module. The output of the image acquisition module is connected to the input of the instruction pairing module, and the output of the instruction pairing module is electrically connected to the inputs of the parameter adjustment module and the execution module. This invention can analyze the user's intention to cancel multiple consecutive commands based on the frequency of these commands. If the user intends to continue canceling commands, the system predicts the air conditioner parameter values ​​for the current time period based on the air conditioner's historical usage records. The predicted air conditioner parameters and the initial air conditioner parameters are then recommended to the user. If the user selects the recommended parameters, the system can achieve the goal of continuously canceling commands in one go, allowing for skip-canceling cancellations, shortening the cancellation steps, and improving efficiency.

Description

Technical Field

[0001] This invention relates to the field of air conditioning control technology, specifically to an intelligent terminal controller and control method for an intelligent air conditioner. Background Technology

[0002] Smart air conditioners are air conditioners with automatic adjustment functions. They can analyze and judge signals from sensors such as temperature, humidity, and air cleanliness based on external climate conditions and user-set indicators, and automatically turn on functions such as cooling, heating, dehumidification, and air purification.

[0003] Smart air conditioners can generally be controlled using various methods, such as remote control, mobile phone, or buttons on the air conditioner unit's control panel. With technological advancements, some smart air conditioners on the market now employ gesture control technology, allowing users to control the air conditioner with simple body movements, eliminating the need for cumbersome button operations or searching for the remote.

[0004] When controlling the system through physical gestures, errors in operation commands are inevitable. However, canceling erroneous commands is cumbersome and time-consuming. For example, if the initial parameter when turning on the air conditioner is C, and the user increases the air conditioner parameter value to C+K, and then discovers the command is incorrect, the user's goal is to decrease the air conditioner parameter value to CK. The conventional operation would be to first return to the initial parameter C, and then readjust the parameter until the air conditioner parameter is adjusted to CK. The above cancellation process is cumbersome and time-consuming. Summary of the Invention

[0005] The purpose of this invention is to provide an intelligent terminal controller and control method for an intelligent air conditioner to solve the problems raised in the prior art.

[0006] To achieve the above objectives, the present invention provides the following technical solution: an intelligent terminal controller for an intelligent air conditioner, the intelligent terminal controller comprising an image acquisition module, an instruction pairing module, a parameter adjustment module, and an execution module;

[0007] The image acquisition module is used to capture the user's body movements;

[0008] The instruction pairing module is used to analyze the collected limb movements, determine the operation instructions corresponding to the limb movements, and activate the corresponding operation instructions.

[0009] The parameter adjustment module adjusts the air conditioning parameters within the range of the wake-up operation commands;

[0010] The execution module is used to mark adjustment progress nodes and determine the adjustment progress node to be rolled back when the user executes the undo adjustment command;

[0011] The output of the image acquisition module is connected to the input of the instruction pairing module, and the output of the instruction pairing module is electrically connected to the inputs of the parameter adjustment module and the execution module.

[0012] Furthermore, the image acquisition module includes a camera, a setting unit, and an image analysis unit;

[0013] The camera is used to capture the user's body movements;

[0014] The setting unit is used to set the duration of the limb movement and the movement path of the limb movement.

[0015] The image analysis unit is used to determine the type of the user's limb movement and analyze the corresponding operation command.

[0016] Furthermore, the instruction pairing module includes a wake-up unit, an operation instruction selection unit, and a tagging unit;

[0017] The wake-up unit is used to wake up the corresponding operation command when the user makes a specified limb movement;

[0018] The selection operation instruction unit is used to determine whether to adjust the air conditioning parameters after the wake-up operation instruction is given. If the air conditioning parameters are to be adjusted, the air conditioning parameters are adjusted according to the movement path of the limb movement.

[0019] The marking unit is used to mark each changed air conditioning parameter as a new adjustment progress node, and to sort the adjustment progress nodes according to the order of adjustment, marking the adjustment type of each adjustment progress node. The adjustment type includes positive parameter type and negative parameter type. If the parameter value of the current adjustment progress node is greater than the parameter value of the previous adjustment progress node, the current adjustment progress node is marked as positive parameter type. If the parameter value of the current adjustment progress node is less than the parameter value of the previous adjustment progress node, the current adjustment progress node is marked as decreasing parameter type.

[0020] Furthermore, the parameter adjustment module includes a unit for determining adjustment commands and a unit for canceling adjustment commands;

[0021] After a user adjusts the air conditioning parameters once, a new adjustment progress node is generated and marked as the target adjustment progress node. Then, the user's next operation command is obtained to get the next adjustment progress node, which is marked as the auxiliary adjustment progress node.

[0022] When the adjustment types of the auxiliary adjustment progress node and the target adjustment progress node are the same, the adjustment command unit issues a user-selected execution adjustment command; if the adjustment types of the auxiliary adjustment progress node and the target adjustment progress node are different, the cancellation adjustment command unit issues a user-selected execution cancellation adjustment command.

[0023] Furthermore, the execution module includes a unit for recommending and canceling nodes and a unit for regenerating operation commands;

[0024] The recommended cancellation node unit is used to extract air conditioning parameters from the historical record within the same time period within I days prior to the current adjustment when the cancellation adjustment command is executed m times consecutively and the cancellation frequency f > frequency threshold F. It then calculates the push value for each type of air conditioning parameter, marks the air conditioning parameter corresponding to the largest push value as the target air conditioning parameter. If the target air conditioning parameter value is within the range of the air conditioning parameter value of the initial node and the air conditioning parameter value of the new adjustment progress node, the target air conditioning parameter is recommended to the user. If the target air conditioning parameter value is outside the range of the air conditioning parameter value of the initial node and the air conditioning parameter value of the new adjustment progress node, the air conditioning parameter of the initial node is recommended to the user.

[0025] The re-generated operation command unit is used to confirm the operation command again, and the user makes physical actions according to the prompts to adjust the air conditioning parameters.

[0026] A control method for an intelligent air conditioner, applied to an intelligent terminal controller of an intelligent air conditioner, the control method comprising the following steps:

[0027] Step S1: Set the limb movements and their corresponding operation commands, as well as the conditions for limb movements to wake up the operation commands;

[0028] Step S2: Collect images of the user's body movements, determine the operation command awakened by the body movements, and adjust the air conditioning parameters through the operation command. Each time the air conditioning parameters are adjusted, an adjustment progress node is marked.

[0029] Step S3: After a new adjustment progress node is generated, the user can choose to execute the confirm adjustment command or cancel the adjustment command. If the user executes the confirm adjustment command, the air conditioning parameters will continue to be adjusted within the range of the current operation command. If the user executes the cancel adjustment command, the adjustment progress node to be returned to will be determined.

[0030] Step S4: Confirm the operation command again. The user performs the physical actions according to the prompts to adjust the air conditioning parameters.

[0031] Furthermore, step S1 includes: setting limb movements, wherein the limb movements include one or more combinations of head movements, facial movements, hand movements and leg movements;

[0032] Set operation commands, which include temperature adjustment commands, fan speed adjustment commands, and mode switching commands;

[0033] Set the duration and movement path of the limb movement;

[0034] The system maps body movements to operating commands, and when a specified body movement is performed, the corresponding operating command is activated, and the air conditioning parameters are adjusted according to the movement path of the body movement.

[0035] Furthermore, step S2 includes:

[0036] Step S201: Set the collection range, guide the user to make body movements within the collection range, and wake up the corresponding operation command based on the body movement;

[0037] Step S202: Obtain the current air conditioning parameters of the awakened operation command, mark it as the initial node, mark each changed air conditioning parameter as a new adjustment progress node, sort the adjustment progress nodes according to the order of adjustment, and mark the adjustment type of each adjustment progress node. The adjustment type includes positive parameter type and negative parameter type.

[0038] If the parameter value of the current adjustment progress node is greater than the parameter value of the previous adjustment progress node, the current adjustment progress node is marked as a positive parameter type. If the parameter value of the current adjustment progress node is less than the parameter value of the previous adjustment progress node, the current adjustment progress node is marked as a decreasing parameter type.

[0039] Furthermore, step S3 includes:

[0040] Step S301: After the user adjusts the air conditioner parameters once, a new adjustment progress node is generated and marked as the target adjustment progress node. The user's next operation command is then obtained to get the next adjustment progress node, which is marked as an auxiliary adjustment progress node. If the adjustment type of the auxiliary adjustment progress node is the same as that of the target adjustment progress node, it is determined that the user has selected to execute the confirm adjustment command; if the adjustment type of the auxiliary adjustment progress node is different from that of the target adjustment progress node, it is determined that the user has selected to execute the cancel adjustment command.

[0041] Step S302: If the cancellation adjustment command is executed continuously m times, obtain the execution time tn of the cancellation adjustment command and calculate the cancellation frequency f. The calculation formula is f = (t1 + t2 + t3 + ... + tn) / m, where t1, t2, t3...tn represent the execution time between the first and second cancellation adjustment commands, the execution time between the second and third cancellation adjustment commands, the execution time between the third and fourth cancellation adjustment commands, and the execution time between the (m-1)th and the mth cancellation adjustment commands, respectively.

[0042] Step S303: If the cancellation frequency f > frequency threshold F, then obtain the time period [T1, T2] of the current air conditioning parameter adjustment, in days, obtain the air conditioning parameters in the same time period within I days before this adjustment in the historical records, forming a historical data set A, A = {a1, a2, a3, ..., ai}, where a1, a2, a3, ..., ai represent the air conditioning parameters of day 1, day 2, day 3, ..., day i within I days, respectively;

[0043] Data with identical air conditioner parameters in set A are grouped into categories, and the number of data points in each category is recorded to form a data set K, K = {k1, k2, k3, ..., kj}, where k1, k2, k3, ..., kj represent the number of data points with identical air conditioner parameters in category 1, category 2, category 3, ..., category j, respectively. The push value Q for each category of data in set K is calculated using the formula: Q = [(kj / Kj)] 总 )*β1]*[(1 / (T1+T2+T3+......+Tj))*β2], where K 总 Let K represent the total number of air conditioning parameters in set K; T1, T2, T3, ..., Tj represent the number of days between the recording date of the first air conditioning parameter and the current adjustment date, the number of days between the recording date of the second air conditioning parameter and the current adjustment date, the number of days between the recording date of the third air conditioning parameter and the current adjustment date, and the number of days between the recording date of the j-th air conditioning parameter and the current adjustment date, respectively; β1 and β2 are weight parameters; * represents a multiplication sign;

[0044] Mark the air conditioner parameter corresponding to the largest push value as the target air conditioner parameter. If the target air conditioner parameter value is within the range of the air conditioner parameter value of the initial node and the air conditioner parameter value of the new adjustment progress node, then recommend the target air conditioner parameter to the user; if the target air conditioner parameter value is outside the range of the air conditioner parameter value of the initial node and the air conditioner parameter value of the new adjustment progress node, then recommend the air conditioner parameter of the initial node to the user.

[0045] If the user selects the recommended target air conditioning parameters, the process will directly return to the adjustment progress node corresponding to the target air conditioning parameters; if the user selects the recommended initial node's air conditioning parameters, the process will directly return to the adjustment progress node corresponding to the initial node; if the user does not select recommended air conditioning parameters, the process will return to the previous adjustment progress node after executing the undo command.

[0046] Compared with the prior art, the beneficial effects of the present invention are:

[0047] 1. This invention can intelligently adjust air conditioning parameters through body movements. When a user makes multiple consecutive undo commands, the invention analyzes the user's undo intention based on the frequency of the undo commands. If the user intends to continue making undo commands, the invention predicts the air conditioning parameter values ​​for the current time period based on the air conditioning's historical usage records. The predicted air conditioning parameters and the initial air conditioning parameters are then recommended to the user. If the user selects the recommended air conditioning parameters, the purpose of making consecutive undo commands can be achieved in one go, allowing the user to perform skip-undo, shortening the undo steps, and improving efficiency. Attached Figure Description

[0048] Figure 1 This is a flowchart illustrating a control method for an intelligent air conditioner according to the present invention. Detailed Implementation

[0049] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0050] Example: Figure 1 As shown, the present invention provides an intelligent terminal controller for an intelligent air conditioner. The intelligent terminal controller includes an image acquisition module, an instruction pairing module, a parameter adjustment module, and an execution module. The output terminal of the image acquisition module is connected to the input terminal of the instruction pairing module, and the output terminal of the instruction pairing module is electrically connected to the input terminals of the parameter adjustment module and the execution module.

[0051] The image acquisition module is used to acquire the user's body movements; the image acquisition module includes a camera, a setting unit, and an image analysis unit.

[0052] The camera is used to capture the user's body movements;

[0053] The setting unit is used to set the duration of the limb movement and the movement path of the limb movement.

[0054] The image analysis unit is used to determine the type of the user's limb movement and analyze the corresponding operation command.

[0055] The instruction pairing module is used to analyze the collected limb movements, determine the operation instruction corresponding to the limb movement, and wake up the corresponding operation instruction; the instruction pairing module includes a wake-up unit, an operation instruction selection unit, and a marking unit;

[0056] The wake-up unit is used to wake up the corresponding operation command when the user makes a specified limb movement;

[0057] The selection operation instruction unit is used to determine whether to adjust the air conditioning parameters after the wake-up operation instruction is given. If the air conditioning parameters are to be adjusted, the air conditioning parameters are adjusted according to the movement path of the limb movement.

[0058] The marking unit is used to mark each changed air conditioning parameter as a new adjustment progress node, and to sort the adjustment progress nodes according to the order of adjustment, marking the adjustment type of each adjustment progress node. The adjustment type includes positive parameter type and negative parameter type. If the parameter value of the current adjustment progress node is greater than the parameter value of the previous adjustment progress node, the current adjustment progress node is marked as positive parameter type. If the parameter value of the current adjustment progress node is less than the parameter value of the previous adjustment progress node, the current adjustment progress node is marked as decreasing parameter type.

[0059] The parameter adjustment module adjusts the air conditioning parameters within the range of the wake-up operation command; the parameter adjustment module includes a unit for determining the adjustment command and a unit for canceling the adjustment command.

[0060] After a user adjusts the air conditioning parameters once, a new adjustment progress node is generated and marked as the target adjustment progress node. Then, the user's next operation command is obtained to get the next adjustment progress node, which is marked as the auxiliary adjustment progress node.

[0061] When the adjustment types of the auxiliary adjustment progress node and the target adjustment progress node are the same, the adjustment command unit issues a user-selected execution adjustment command; if the adjustment types of the auxiliary adjustment progress node and the target adjustment progress node are different, the cancellation adjustment command unit issues a user-selected execution cancellation adjustment command.

[0062] The execution module is used to mark adjustment progress nodes and determine the adjustment progress node to be rolled back when the user executes the undo adjustment command;

[0063] The execution module includes a unit for recommending and canceling nodes and a unit for regenerating operation commands;

[0064] The recommended cancellation node unit is used to extract air conditioning parameters from the historical record within the same time period within I days prior to the current adjustment when the cancellation adjustment command is executed m times consecutively and the cancellation frequency f > frequency threshold F. It then calculates the push value for each type of air conditioning parameter, marks the air conditioning parameter corresponding to the largest push value as the target air conditioning parameter. If the target air conditioning parameter value is within the range of the air conditioning parameter value of the initial node and the air conditioning parameter value of the new adjustment progress node, the target air conditioning parameter is recommended to the user. If the target air conditioning parameter value is outside the range of the air conditioning parameter value of the initial node and the air conditioning parameter value of the new adjustment progress node, the air conditioning parameter of the initial node is recommended to the user.

[0065] The re-generated operation command unit is used to confirm the operation command again, and the user makes physical actions according to the prompts to adjust the air conditioning parameters.

[0066] A control method for an intelligent air conditioner, applied to an intelligent terminal controller of an intelligent air conditioner, the control method comprising the following steps:

[0067] Step S1: Set the limb movements and their corresponding operation commands, as well as the conditions for limb movements to wake up the operation commands;

[0068] Step S1 includes: setting limb movements, wherein the limb movements include one or more combinations of head movements, facial movements, hand movements and leg movements;

[0069] Set operation commands, which include temperature adjustment commands, fan speed adjustment commands, and mode switching commands;

[0070] Set the duration and movement path of the limb movement;

[0071] The system maps body movements to operating commands, and when a specified body movement is performed, the corresponding operating command is activated, and the air conditioning parameters are adjusted according to the movement path of the body movement.

[0072] For example, the first body movement is set to extend the index finger, and the second body movement is set to extend both the index and middle fingers. The first body movement corresponds to the operation command for adjusting the air conditioner temperature parameter, and the second body movement corresponds to the operation command for adjusting the air conditioner fan speed parameter. When the duration of the first body movement reaches the set 10 seconds, the operation command for adjusting the air conditioner temperature parameter can be activated. At this time, the display terminal will show the body movement guidance, such as moving the palm to the left to decrease the air conditioner temperature parameter, and moving the palm to the right to increase the air conditioner temperature parameter. After the user performs the specified body movement according to the guidance, the air conditioner parameter is adjusted.

[0073] Step S2: Acquire images of the user's body movements, determine the operation command triggered by the body movements, and adjust the air conditioning parameters according to the operation command. Each adjustment of the air conditioning parameters is marked as an adjustment progress node. Step S2 includes:

[0074] Step S201: Set the collection range, guide the user to make body movements within the collection range, and wake up the corresponding operation command based on the body movement;

[0075] Step S202: Obtain the current air conditioning parameters of the awakened operation command, mark it as the initial node, mark each changed air conditioning parameter as a new adjustment progress node, and sort the adjustment progress nodes according to the order of adjustment. Mark the adjustment type of each adjustment progress node. The adjustment type includes positive parameter type and negative parameter type. The positive parameter type is to increase or increase the air conditioning parameter based on the air conditioning parameter corresponding to the initial node. The negative parameter type is the opposite of the positive parameter type. The negative parameter type is to decrease or decrease the air conditioning parameter based on the air conditioning parameter corresponding to the initial node.

[0076] If the parameter value of the current adjustment progress node is greater than the parameter value of the previous adjustment progress node, the current adjustment progress node is marked as a positive parameter type. If the parameter value of the current adjustment progress node is less than the parameter value of the previous adjustment progress node, the current adjustment progress node is marked as a decreasing parameter type.

[0077] For example, when the wake-up command is to adjust the air conditioner temperature parameter, the air conditioner temperature at the time of wake-up is marked as the initial temperature, which is 20°C. If the user issues a command to increase the air conditioner temperature, adjusting it to 21°C, then the parameter value of the current adjustment progress node is 21°C, and the adjustment type of this adjustment progress node is a positive parameter type. If the user continues to issue a command to decrease the air conditioner temperature, adjusting it to 20.5°C, then the parameter value of the next adjustment progress node is 20.5°C, and the adjustment type of this adjustment progress node is a negative parameter type.

[0078] Step S3: After a new adjustment progress node is generated, the user can choose to execute the confirm adjustment command or cancel the adjustment command. If the user executes the confirm adjustment command, the air conditioning parameters will continue to be adjusted within the range of the current operation command. If the user executes the cancel adjustment command, the adjustment progress node to be returned to will be determined.

[0079] Step S3 includes:

[0080] Step S301: After the user adjusts the air conditioner parameters once, a new adjustment progress node is generated and marked as the target adjustment progress node. The user's next operation command is then obtained to get the next adjustment progress node, which is marked as an auxiliary adjustment progress node. If the adjustment type of the auxiliary adjustment progress node is the same as that of the target adjustment progress node, it is determined that the user has selected to execute the confirm adjustment command; if the adjustment type of the auxiliary adjustment progress node is different from that of the target adjustment progress node, it is determined that the user has selected to execute the cancel adjustment command.

[0081] Step S302: If the cancellation adjustment command is executed continuously m times, where m is a set value that can be set according to the actual situation, then obtain the execution time tn of the cancellation adjustment command and calculate the cancellation frequency f. The calculation formula is f = (t1 + t2 + t3 + ... + tn) / m, where t1, t2, t3...tn represent the execution time between the first cancellation adjustment command and the second cancellation adjustment command, the execution time between the second cancellation adjustment command and the third cancellation adjustment command, the execution time between the third cancellation adjustment command and the fourth cancellation adjustment command, and the execution time between the (m-1)th cancellation adjustment command and the mth cancellation adjustment command, respectively.

[0082] Step S303: If the cancellation frequency f > frequency threshold F, where the frequency threshold F is a set value that can be calculated according to the prediction formula or set manually, then obtain the time period [T1, T2] for the current air conditioning parameter adjustment. In the days, obtain the air conditioning parameters in the same time period within the I days before this adjustment in the historical records to form a historical data set A, A = {a1, a2, a3, ..., ai}, where a1, a2, a3, ..., ai represent the air conditioning parameters of the 1st day, the 2nd day, the 3rd day, ..., the ith day within the I days, respectively.

[0083] Data with identical air conditioner parameters in set A are grouped into categories, and the number of data points in each category is recorded to form a data set K, K = {k1, k2, k3, ..., kj}, where k1, k2, k3, ..., kj represent the number of data points with identical air conditioner parameters in category 1, category 2, category 3, ..., category j, respectively. The push value Q for each category of data in set K is calculated using the formula: Q = [(kj / Kj)] 总 )*β1]*[(1 / (T1+T2+T3+......+Tj))*β2], where K 总Let K represent the total number of air conditioning parameters in set K; T1, T2, T3, ..., Tj represent the number of days between the recording date of the first air conditioning parameter and the current adjustment date, the number of days between the recording date of the second air conditioning parameter and the current adjustment date, the number of days between the recording date of the third air conditioning parameter and the current adjustment date, and the number of days between the recording date of the j-th air conditioning parameter and the current adjustment date, respectively; β1 and β2 are weight parameters; * represents a multiplication sign;

[0084] Mark the air conditioner parameter corresponding to the largest push value as the target air conditioner parameter. If the target air conditioner parameter value is within the range of the air conditioner parameter value of the initial node and the air conditioner parameter value of the new adjustment progress node, then recommend the target air conditioner parameter to the user; if the target air conditioner parameter value is outside the range of the air conditioner parameter value of the initial node and the air conditioner parameter value of the new adjustment progress node, then recommend the air conditioner parameter of the initial node to the user.

[0085] If the user selects the recommended target air conditioning parameters, the process will directly return to the adjustment progress node corresponding to the target air conditioning parameters; if the user selects the recommended initial node's air conditioning parameters, the process will directly return to the adjustment progress node corresponding to the initial node; if the user does not select recommended air conditioning parameters, the process will return to the previous adjustment progress node after executing the undo command.

[0086] For example: If the initial temperature of the initial node is 20°C, and the user issues an adjustment command to adjust the air conditioner temperature to 21°C, the adjustment type of this adjustment progress node is positive parameter type; if the user issues a second adjustment command to adjust the air conditioner temperature to 22°C, the adjustment type of this adjustment progress node is positive parameter type; if the user issues a third adjustment command to adjust the air conditioner temperature to 21.5°C, the adjustment type of this adjustment progress node is negative parameter type; if the user issues a fourth adjustment command to adjust the air conditioner temperature to 21°C, the adjustment type of this adjustment progress node is negative parameter type.

[0087] If m is set to 2, then the execution times of the third and fourth adjustment commands are obtained. That is, the time required to adjust the air conditioner temperature from 22°C in the second adjustment command to 21.5°C in the third adjustment command is taken as the execution time t1 of the third adjustment command, and the time required to adjust the air conditioner temperature from 21.5°C in the third adjustment command to 21°C in the fourth adjustment command is taken as the execution time t2 of the fourth adjustment command. When the cancellation frequency reaches the set frequency threshold, it is determined that the user is performing multiple cancellation operations. At this time, the air conditioner parameter values ​​for the current time period can be predicted based on historical records and recommended to the user, or the air conditioner parameters of the initial node can be recommended to the user, so that the user can perform skip cancellation, shorten the cancellation steps, and improve efficiency.

[0088] Step S4: Confirm the operation command again. The user performs the physical actions according to the prompts to adjust the air conditioning parameters.

[0089] It will be apparent to those skilled in the art that the present invention is not limited to the details of the exemplary embodiments described above, and that the invention can be implemented in other specific forms without departing from its spirit or essential characteristics. Therefore, the embodiments should be considered in all respects as exemplary and non-limiting, and the scope of the invention is defined by the appended claims rather than the foregoing description. Thus, all variations falling within the meaning and scope of equivalents of the claims are intended to be included within the present invention. No reference numerals in the claims should be construed as limiting the scope of the claims.

Claims

1. A smart terminal controller for an intelligent air conditioner, characterized in that: The intelligent terminal controller includes an image acquisition module, an instruction pairing module, a parameter adjustment module, and an execution module; The image acquisition module is used to capture the user's body movements; The instruction pairing module is used to analyze the collected limb movements, determine the operation instructions corresponding to the limb movements, and activate the corresponding operation instructions. The parameter adjustment module adjusts the air conditioning parameters within the range of the wake-up operation commands; The execution module is used to mark adjustment progress nodes and determine the adjustment progress node to be rolled back when the user executes the undo adjustment command; The output of the image acquisition module is connected to the input of the instruction pairing module, and the output of the instruction pairing module is electrically connected to the inputs of the parameter adjustment module and the execution module. The execution module includes a unit for recommending and canceling nodes and a unit for regenerating operation commands; The recommended cancellation node unit is used to extract air conditioning parameters from the historical record within the same time period within I days prior to the current adjustment when the cancellation adjustment command is executed m times consecutively and the cancellation frequency f > frequency threshold F. It then calculates the push value for each type of air conditioning parameter, marks the air conditioning parameter corresponding to the largest push value as the target air conditioning parameter. If the target air conditioning parameter value is within the range of the air conditioning parameter value of the initial node and the air conditioning parameter value of the new adjustment progress node, the target air conditioning parameter is recommended to the user. If the target air conditioning parameter value is outside the range of the air conditioning parameter value of the initial node and the air conditioning parameter value of the new adjustment progress node, the air conditioning parameter of the initial node is recommended to the user. The re-generated operation command unit is used to confirm the operation command again, and the user makes physical actions according to the prompts to adjust the air conditioning parameters.

2. The intelligent terminal controller for an intelligent air conditioner according to claim 1, characterized in that: The image acquisition module includes a camera, a setting unit, and an image analysis unit; The camera is used to capture the user's body movements; The setting unit is used to set the duration of the limb movement and the movement path of the limb movement. The image analysis unit is used to determine the type of the user's limb movement and analyze the corresponding operation command.

3. The intelligent terminal controller for an intelligent air conditioner according to claim 2, characterized in that: The instruction pairing module includes a wake-up unit, an operation instruction selection unit, and a marking unit; The wake-up unit is used to wake up the corresponding operation command when the user makes a specified limb movement; The selection operation instruction unit is used to determine whether to adjust the air conditioning parameters after the wake-up operation instruction is given. If the air conditioning parameters are to be adjusted, the air conditioning parameters are adjusted according to the movement path of the limb movement. The marking unit is used to mark each changed air conditioning parameter as a new adjustment progress node, and to sort the adjustment progress nodes according to the order of adjustment, and to mark the adjustment type of each adjustment progress node, including positive parameter type and negative parameter type. If the parameter value of the current adjustment progress node is greater than the parameter value of the previous adjustment progress node, the current adjustment progress node is marked as a positive parameter type. If the parameter value of the current adjustment progress node is less than the parameter value of the previous adjustment progress node, the current adjustment progress node is marked as a decreasing parameter type.

4. The intelligent terminal controller for an intelligent air conditioner according to claim 3, characterized in that: The parameter adjustment module includes a unit for determining adjustment commands and a unit for canceling adjustment commands; After a user adjusts the air conditioning parameters once, a new adjustment progress node is generated and marked as the target adjustment progress node. Then, the user's next operation command is obtained to get the next adjustment progress node, which is marked as the auxiliary adjustment progress node. When the adjustment types of the auxiliary adjustment progress node and the target adjustment progress node are the same, the adjustment command unit issues a user-selected execution adjustment command; if the adjustment types of the auxiliary adjustment progress node and the target adjustment progress node are different, the cancellation adjustment command unit issues a user-selected execution cancellation adjustment command.

5. A control method for an intelligent air conditioner, applied to an intelligent terminal controller of an intelligent air conditioner as described in any one of claims 1-4, characterized in that: The control method includes the following steps: Step S1: Set the limb movements and their corresponding operation commands, as well as the conditions for limb movements to wake up the operation commands; Step S2: Collect images of the user's body movements, determine the operation command awakened by the body movements, and adjust the air conditioning parameters through the operation command. Each time the air conditioning parameters are adjusted, an adjustment progress node is marked. Step S3: After a new adjustment progress node is generated, the user can choose to execute the confirm adjustment command or cancel the adjustment command. If the user executes the confirm adjustment command, the air conditioning parameters will continue to be adjusted within the range of the current operation command. If the user executes the cancel adjustment command, the adjustment progress node to be returned to will be determined. Step S4: Confirm the operation command again. The user performs the physical actions according to the prompts to adjust the air conditioning parameters.

6. The control method for an intelligent air conditioner according to claim 5, characterized in that: Step S1 includes: setting limb movements, wherein the limb movements include one or more combinations of head movements, facial movements, hand movements and leg movements; Set operation commands, which include temperature adjustment commands, fan speed adjustment commands, and mode switching commands; Set the duration and movement path of the limb movement; The system maps body movements to operating commands, and when a specified body movement is performed, the corresponding operating command is activated, and the air conditioning parameters are adjusted according to the movement path of the body movement.

7. The control method for an intelligent air conditioner according to claim 6, characterized in that: The step S2 comprises: Step S201: Set the collection range, guide the user to make body movements within the collection range, and wake up the corresponding operation command based on the body movement; Step S202: Obtain the current air conditioning parameters of the awakened operation command, mark it as the initial node, mark each changed air conditioning parameter as a new adjustment progress node, sort the adjustment progress nodes according to the order of adjustment, and mark the adjustment type of each adjustment progress node. The adjustment type includes positive parameter type and negative parameter type. If the parameter value of the current adjustment progress node is greater than the parameter value of the previous adjustment progress node, the current adjustment progress node is marked as a positive parameter type. If the parameter value of the current adjustment progress node is less than the parameter value of the previous adjustment progress node, the current adjustment progress node is marked as a decreasing parameter type.

8. The control method for an intelligent air conditioner according to claim 7, characterized in that: The step S3 comprises: Step S301: After the user adjusts the air conditioner parameters once, a new adjustment progress node is generated and marked as the target adjustment progress node. The user's next operation command is then obtained to get the next adjustment progress node, which is marked as an auxiliary adjustment progress node. If the adjustment type of the auxiliary adjustment progress node is the same as that of the target adjustment progress node, it is determined that the user has selected to execute the confirm adjustment command; if the adjustment type of the auxiliary adjustment progress node is different from that of the target adjustment progress node, it is determined that the user has selected to execute the cancel adjustment command. Step S302: If the cancellation adjustment command is executed continuously m times, the execution time tn of the cancellation adjustment command is obtained, and the cancellation frequency f is calculated. The calculation formula is f = (t1 + t2 + t3 + ... + tn) / m, where t1, t2, t3...tn represent the execution time between the first cancellation adjustment command and the second cancellation adjustment command, the execution time between the second cancellation adjustment command and the third cancellation adjustment command, the execution time between the third cancellation adjustment command and the fourth cancellation adjustment command, and the execution time between the (m-1)th cancellation adjustment command and the mth cancellation adjustment command, respectively. Step S303: If the cancellation frequency f > frequency threshold F, then obtain the time period [T1, T2] of the current air conditioning parameter adjustment, in days, obtain the air conditioning parameters in the same time period within I days before this adjustment in the historical records, forming a historical data set A, A={a1, a2, a3, ..., ai}, where a1, a2, a3, ..., ai represent the air conditioning parameters of day 1, day 2, day 3, ..., day i within I days, respectively; Data with identical air conditioner parameters in set A are grouped into categories, and the number of data points in each category is recorded to form a data set K, K = {k1, k2, k3, ..., kj}, where k1, k2, k3, ..., kj represent the number of data points with identical air conditioner parameters in category 1, category 2, category 3, ..., category j, respectively. The push value Q for each category of data in set K is calculated using the formula: Q = [(kj / Kj)]. 总 )*β1]*[(1 / (T1+T2+T3+......+Tj))*β2], where K 总 Let K represent the total number of air conditioning parameters in set K; T1, T2, T3, ..., Tj represent the number of days between the recording date of the first air conditioning parameter and the current adjustment date, the number of days between the recording date of the second air conditioning parameter and the current adjustment date, the number of days between the recording date of the third air conditioning parameter and the current adjustment date, and the number of days between the recording date of the j-th air conditioning parameter and the current adjustment date, respectively; β1 and β2 are weight parameters; * represents a multiplication sign; Mark the air conditioner parameter corresponding to the largest push value as the target air conditioner parameter. If the target air conditioner parameter value is within the range of the air conditioner parameter value of the initial node and the air conditioner parameter value of the new adjustment progress node, then recommend the target air conditioner parameter to the user; if the target air conditioner parameter value is outside the range of the air conditioner parameter value of the initial node and the air conditioner parameter value of the new adjustment progress node, then recommend the air conditioner parameter of the initial node to the user. If the user selects the recommended target air conditioning parameters, the process will directly return to the adjustment progress node corresponding to the target air conditioning parameters; if the user selects the recommended initial node's air conditioning parameters, the process will directly return to the adjustment progress node corresponding to the initial node; if the user does not select recommended air conditioning parameters, the process will return to the previous adjustment progress node after executing the undo command.

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