Remote control method and system for smart home and intelligent cabin

Abstract

The invention discloses a remote control method and system for a smart home and an intelligent cabin, and belongs to the technical field of smart homes. Comprising the steps of obtaining voice connection data, generating a target center control awakening instruction, marking a target awakening node and recording the target awakening node in a database, and awakening a target center control; based on the number of people in the service area covered by the target awakening node, constructing a target number of people set, and calculating a conversion index of the number of people in the target area to predict the number of people in the target area of the closing node; extracting influence factors of the environment configuration instruction, calculating a recommendation index of instruction combination data and generating a recommendation sequence for a user to select; according to the method, the number of people in the target area of the closed node is predicted through the conversion index of the number of people in the target area, so that the waste of resources is reduced, and the accuracy of instruction recommendation is improved; and the recommendation index of the instruction combination data is further calculated, so that the recommendation accuracy of the instruction combination data is improved, and the user experience is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of vehicle-home interconnection, and particularly to a method and system for remote control of smart home and intelligent cockpit. Background Art

[0002] With the rapid development of Internet of Things technology, smart home and intelligent cockpit have become an indispensable part of modern life, and remote operations can be realized through their respective central controls; however, in the prior art, the control of smart home is mainly by mobile phone, which may cause safety problems when driving a car; at the same time, it is rather troublesome to use the smart home to control the vehicle central control, and users need to use different devices and APPs respectively during operation, with cumbersome operation and low efficiency, greatly affecting the user experience.

[0003] Therefore, how to realize the interconnection between intelligent cockpit and smart home and improve the user experience has become a problem to be solved by us. Summary of the Invention

[0004] The purpose of the present invention is to provide a method and system for remote control of smart home and intelligent cockpit to solve the problems raised in the above background art.

[0005] To solve the above technical problems, the present invention provides the following technical solutions:

[0006] A method for remote control of smart home and intelligent cockpit, the method comprising the following steps:

[0007] Step S100: Wake up the service central control, generate a target central control wake-up instruction by obtaining voice connection data, mark and record the time point or event of the target wake-up node in the database; verify the voice connection data through a preset voice verification system, and when the verification is successful, send the target central control wake-up instruction to the target central control to wake up the target central control;

[0008] Step S200: Extract the number of people in the service area covered by the target wake-up node in the database, construct a target number set, calculate the conversion index of the number of people in the target area, and predict the number of people in the target area covered by the closing node;

[0009] Step S300: Extract different instruction combination data with the same predicted number of people in the target area from the database, construct an instruction combination set, extract the influencing factors of the environment configuration instruction according to historical data or real-time sensor data, calculate the recommendation index of the instruction combination data, and count the recommendation indexes of all elements in the instruction combination set to generate a recommendation sequence, and feedback the first three instruction combinations of the recommendation sequence to the service central control;

[0010] Step S400: The service central control combines the three instruction data and displays and audibly feedbacks it to the user through the panel. After the user selects the instruction combination, the selected instruction combination data is recorded in the database and fed back to the target central control. The target central control turns on the corresponding device and notifies the user that the corresponding device has been turned on.

[0011] Further, the specific implementation process of step S100 includes:

[0012] With user authorization, voice data of the user is collected through an audio sensor, keywords in the voice data are extracted according to a preset keyword library, and a service central control wake-up instruction is generated to wake up the service central control;

[0013] Voice connection data is obtained through the service central control, keywords in the voice connection data are extracted according to the keyword library, a target central control wake-up instruction is generated, and the time point or event of the target wake-up node is marked and recorded in the database. The target wake-up node represents the time point or event of the system trigger event;

[0014] The voice connection data is verified through a preset voice verification system. When the verification is successful, the service central control establishes a communication connection with the target central control and sends a target central control wake-up instruction to wake up the target central control. The central control includes a smart home central control and a smart cockpit central control.

[0015] It should be noted that what this invention realizes is the mutual control between the smart home and the smart cockpit. When the target central control is the smart home central control, the service central control is the smart cockpit central control. When the user arrives home, they can directly establish a connection between the smart cockpit central control and the smart home central control through the smart cockpit central control, so as to perform voice control on the smart home, such as closing the curtains in advance, feeding the pet, and turning on the air conditioner. This not only reduces the risk of controlling the smart home with a mobile phone during driving but also avoids the problem that different smart homes require different APPs for control, optimizing the control steps and improving the user experience.

[0016] Further, the specific implementation process of step S200 includes:

[0017] The target central control extracts the number of people in the service area covered by the database at the target wake-up node, denoted as A. The service area represents the dynamic or static communication range covered by the service central control, and the target area represents the dynamic or static communication range covered by the target central control; and predicts the number of people in the target area covered by the closing node. The closing node represents the time point when the door induction signal in the target area first triggers a closing operation after the target wake-up node is triggered, and the target wake-up node and the closing node are in one-to-one correspondence;

[0018] Extract the number of people in the target area covered by the closing node when the number of people in the service area covered by the database at the target wake-up node is A, and construct a target number set B = {b n|n = 1, 2, …, N}, where b n represents the number of people in the target area covered by the nth closed node, and N represents the total number of types of the number of people in the target area covered by the closed node;

[0019] When the number of people in the service area in the statistical database is A, the number of people in the target area covered by the closed node is b n The number of data, and calculate the conversion index of the number of people b n in the target area: Among them, represents the conversion index when the number of people in the target area covered by the closed node is b when the number of people in the service area in the database is A n , represents the number of data when the number of people in the service area in the database is A and the number of people in the target area covered by the closed node is b n ; represents the number of data when the number of people in the service area in the database is A and the number of people in the target area covered by the closed node is b m ;

[0020] Statistically calculate the conversion indices corresponding to all elements of the target number set in the target area, and extract the number of people in the target area with the highest conversion index as the predicted number of people in the target area covered by the closed node.

[0021] It should be noted that for the prediction of the number of people in the target area of the closed node, when the user controls the intelligent cockpit through the intelligent home central control voice, the number of people traveling is not fixed, and the adjustment of multiple seats is related to the number of people traveling, that is, related to the number of people appearing in the target area; at the same time, when the user controls the intelligent home through the intelligent cockpit central control voice, whether multiple rooms of the intelligent home are turned on is related to the number of people returning home. The more people return home, the more intelligent home appliances such as air conditioners are turned on; therefore, through the predicted number of people in the target area of the closed node, not only can the waste of resources caused by turning on unnecessary intelligent homes be avoided, but also the user experience can be improved.

[0022] Furthermore, the specific implementation process of the step S300 includes:

[0023] Extract different instruction combination data with the same predicted number of people in the target area from the database, and construct an instruction combination set U = {u i |i = 1, 2, …, I}, where the u i represents the ith instruction combination data corresponding to the predicted number of people in the target area, and I represents the total number of types of instruction combination data corresponding to the predicted number of people in the target area. Each instruction combination data is generated based on the historical operation records and real-time sensor data in the database and consists of one or more preset environment configuration instructions;

[0024] Extract the influencing factors of the environmental configuration instruction according to historical data or real-time sensor data. The influencing factors include the wake-up time period, light intensity, and temperature difference. Among them, the wake-up time period data is provided by the time module, and the light intensity and temperature difference data are collected by real-time sensors and recorded in the database. The environmental configuration instruction corresponds to the dynamic adjustment of one or more influencing factors.

[0025] Extract the wake-up time period data and calculate the instruction combination data u i The occurrence probability where T represents the wake-up time period where the target wake-up node is located, represents the number of instruction combination data u i when the wake-up time period is T, represents the number of instruction combination data u d when the wake-up time period is T, represents the total number of instruction combination data when the wake-up time period is T;

[0026] Extract the light intensity within the target area covered by the target wake-up node and calculate the occurrence probability of the instruction combination data u i The occurrence probability where Q represents the light intensity within the target area covered by the target wake-up node, represents the number of instruction combination data u i when the light intensity within the target area is Q, represents the number of instruction combination data u d when the light intensity within the target area is Q, represents the total number of instruction combination data when the light intensity within the target area is Q;

[0027] Extract the temperature difference between the service area and the target area covered by the target wake-up node and calculate the occurrence probability of the instruction combination data u i The occurrence probability where H represents the temperature difference between the service area and the target area covered by the target wake-up node, represents the number of instruction combination data u i when the temperature difference between the service area and the target area is H, represents the number of instruction combination data u d when the temperature difference between the service area and the target area is H, represents the total number of instruction combination data when the temperature difference between the service area and the target area is H;

[0028] Based on the influencing factors of the environmental configuration instruction, calculate the recommendation index of the instruction combination data u i The recommendation index: Among them, p(T∪Q∪H) represents the probability of the occurrence of the instruction combination data u when at least one of the wake-up time period is T, the light intensity in the target area is Q, and the temperature difference between the service area and the target area is H. i The probability of occurrence, p(T∩Q∩H) represents the probability of the occurrence of the instruction combination data u when the wake-up time period is T, the light intensity in the target area is Q, and the temperature difference between the service area and the target area is H. i The probability of occurrence;

[0029] Statistically calculate the recommendation index of all elements in the instruction combination set, generate a recommendation sequence from largest to smallest according to the recommendation index, and feedback the first three instruction combination data in the recommendation sequence to the service central control.

[0030] It should be noted that the recommendation index of the instruction set data is analyzed based on the user's historical data for user preference analysis, which saves the user's decision-making time and improves the user experience.

[0031] Furthermore, the specific implementation process of the step S400 includes:

[0032] The service central control displays the three instruction combination data on the service central control panel through a preset recommendation template, and generates voice data through a preset voice template and feedbacks it to the user. Among them, the preset recommendation template includes the interface logic rules for displaying the recommendation sequence, and the preset voice template includes the voice generation rules for voice feedback; when the user selects an instruction combination, record the selected instruction combination data in the database and feedback it to the target central control;

[0033] The target central control operates the corresponding device according to the selected instruction combination data. When the corresponding device is turned on, voice data is generated through the preset voice template of the service central control and feedback to the user.

[0034] A remote control system for a smart home and a smart cockpit, the system includes: a wake-up module, a prediction module, a matching module, and a control module;

[0035] The wake-up module includes an instruction unit and a wake-up unit. The instruction unit is used to wake up the service central control, generate a target central control wake-up instruction, mark the target wake-up node and record it in the database; the wake-up unit is used to establish a communication connection with the target central control and wake up the target central control;

[0036] The prediction module includes a conversion unit and a prediction unit. The conversion unit constructs an instruction combination set by extracting the number of people in the service area covered by the target wake-up node in the database, and calculates the conversion index of the number of people in the target area; the prediction unit predicts the number of people in the target area covered by the shutdown node based on the conversion index of the number of people in the target area;

[0037] The matching module includes a matching unit and a statistical unit. The matching unit constructs a set of instruction combinations by extracting different instruction combination data with the same predicted number of people in the target area of the database, extracts the influencing factors of the environment configuration instructions according to historical data or real-time sensor data, and calculates the recommendation index of the instruction combination data. The statistical unit generates a recommendation sequence by sorting all elements in the instruction combination set according to the recommendation index from largest to smallest, and feeds back the first three instruction combinations in the recommendation sequence to the service control center.

[0038] For the control module, the service control center feeds the three instruction combination data to the user through panel display and voice. When the user selects an instruction combination, the selected instruction combination data is recorded in the database and fed back to the target control center. The target control center turns on the corresponding device and notifies the user that the corresponding device has been turned on.

[0039] Furthermore, the wake-up module includes an instruction unit and a wake-up unit.

[0040] The instruction unit collects the user's voice data through an audio sensor, extracts keywords from the voice data according to a preset keyword library to generate a service control center wake-up instruction to wake up the service control center. It obtains voice connection data through the service control center, extracts keywords from the voice connection data according to the keyword library to generate a target control center wake-up instruction, marks and records the time point or event of the target wake-up node in the database, where the target wake-up node represents the time point or event of the system triggering an event.

[0041] The wake-up unit verifies the voice connection data obtained by the instruction unit through a preset voice verification system. When the verification is successful, the service control center establishes a communication connection with the target control center and sends a target control center wake-up instruction to wake up the target control center. The control center includes a smart home control center and a smart cockpit control center.

[0042] Furthermore, the prediction module includes a conversion unit and a prediction unit.

[0043] The conversion unit, based on the target wake-up node recorded by the wake-up module, extracts the number of people in the target area covered by the closing node when the number of people in the service area covered by the target wake-up node is A in the database to construct a target number set. By counting the number of data where the number of people in the target area of the closing node is b when the number of people in the service area of the database is A n calculate the conversion index of the number of people b in the target area. n

[0044] The prediction unit calculates the conversion index corresponding to all elements of the target number set in the target area through the conversion unit, and extracts the number of people in the target area with the highest conversion index as the predicted number of people in the target area covered by the closing node.

[0045] Further, the matching module includes a matching unit and a statistical unit;

[0046] The matching unit extracts different instruction combination data with the same predicted number of people in the target area covered by the target wake-up node from the database based on the predicted number of people in the target area covered by the closed node, and constructs an instruction combination set; extracts the influencing factors of the environment configuration instruction according to historical data or real-time sensor data, calculates the occurrence probability of the instruction combination data when calculating the wake-up time period, the light intensity in the target area covered by the target wake-up node, and the temperature difference between the service area and the target area covered by the target wake-up node, so as to calculate the recommendation index of the instruction combination data;

[0047] The statistical unit calculates the recommendation index of all elements in the instruction combination set according to the matching unit, generates a recommendation sequence from largest to smallest according to the recommendation index, and feeds back the first three instruction combination data in the recommendation sequence to the service central control.

[0048] Further, for the control module, the service central control displays the three instruction combination data on the service central control panel through a preset recommendation template, and generates voice data through a preset voice template and feeds it back to the user. Among them, the preset recommendation template includes the interface logic rules for displaying the recommendation sequence, and the preset voice template includes the voice generation rules for voice feedback; when the user selects an instruction combination, the selected instruction combination data is recorded in the database and fed back to the target central control; the target central control operates the corresponding device according to the selected instruction combination data. When the corresponding device is turned on, voice data is generated through the preset voice template of the service central control and fed back to the user.

[0049] Compared with the prior art, the beneficial effects achieved by the present invention are as follows: In a method and system for remote control of a smart home and a smart cockpit provided by the present invention, it includes obtaining voice connection data, generating a target central control wake-up instruction, marking the target wake-up node and recording it in the database to wake up the target central control; constructing a target number set based on the number of people in the service area of the target wake-up node, and calculating the conversion index of the number of people in the target area to predict the number of people in the target area of the closed node; extracting the influencing factors of the environment configuration instruction according to historical data or real-time sensor data, calculating the recommendation index of the instruction combination data and generating a recommendation sequence for the user to select an instruction combination; by calculating the conversion index of the number of people in the target area, the present invention predicts the number of people in the target area of the closed node, which not only reduces the waste of resources, but also improves the accuracy of instruction recommendation; further calculates the recommendation index of the instruction combination data to improve the accuracy of instruction combination matching and improve the user experience. Description of the Drawings

[0050] The accompanying drawings are used to provide a further understanding of the present invention, and constitute a part of the specification. They are used together with the embodiments of the present invention to explain the present invention, and do not constitute a limitation to the present invention.

[0051] Figure 1 is a schematic structural diagram of an embodiment of the present invention;

[0052] Figure 2 is a method flowchart of an embodiment of the present invention. Detailed implementation manners

[0053] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0054] Please refer to Figure 1 , in the first embodiment: A remote control system for smart home and smart cockpit, the system includes: a wake-up module, a prediction module, a matching module, and a control module;

[0055] The wake-up module includes an instruction unit and a wake-up unit. The instruction unit is used to wake up the service central control, generate a target central control wake-up instruction, mark the target wake-up node and record it in the database; the wake-up unit is used to establish a communication connection with the target central control and wake up the target central control.

[0056] The prediction module includes a conversion unit and a prediction unit. The conversion unit constructs an instruction combination set by extracting the number of people in the service area covered by the target wake-up node in the database, and calculates the conversion index of the number of people in the target area; the prediction unit predicts the number of people in the target area covered by the closed node based on the conversion index of the number of people in the target area.

[0057] The matching module includes a matching unit and a statistics unit. The matching unit constructs an instruction combination set by extracting different instruction combination data with the same predicted number of people in the target area from the database, extracts the influencing factors of the environmental configuration instruction according to historical data or real-time sensor data, and calculates the recommendation index of the instruction combination data; the statistics unit sorts all elements in the instruction combination set according to the recommendation index from large to small to generate a recommendation sequence, and feeds back the first three instruction combinations in the recommendation sequence to the service central control.

[0058] The control module, the service central control feeds the three instruction combination data to the user through panel display and voice. When the user selects an instruction combination, the selected instruction combination data is recorded in the database and fed back to the target central control. The target central control turns on the corresponding device and notifies the user that the corresponding device has been turned on.

[0059] Further, the wake-up module includes an instruction unit and a wake-up unit;

[0060] The instruction unit collects the user's voice data through an audio sensor, extracts keywords from the voice data according to a preset keyword library, generates a service central control wake-up instruction to wake up the service central control; obtains voice connection data through the service central control, extracts keywords from the voice connection data according to the keyword library, generates a target central control wake-up instruction, marks and records the time point or event of the target wake-up node in the database, and the target wake-up node represents the time point or event of the system triggering event;

[0061] The wake-up unit verifies the voice connection data obtained by the instruction unit through a preset voice verification system. When the verification is successful, the service central control establishes a communication connection with the target central control and sends a target central control wake-up instruction to wake up the target central control. The central control includes a smart home central control and a smart cockpit central control.

[0062] Further, the prediction module includes a conversion unit and a prediction unit;

[0063] The conversion unit, based on the target wake-up node recorded by the wake-up module, extracts the number of people in the target area covered by the closing node when the number of people in the service area covered by the target wake-up node is A, and constructs a target number set; by counting the number of data with the number of people in the target area covered by the closing node being b n when the number of people in the service area in the database is A, calculates the conversion index of the number of people b in the target area n ;

[0064] The prediction unit calculates the conversion index corresponding to all elements of the target number set in the target area through the conversion unit, and extracts the number of people in the target area with the highest conversion index as the predicted number of people in the target area covered by the closing node.

[0065] Further, the matching module includes a matching unit and a statistics unit;

[0066] The matching unit, based on the predicted number of people in the target area covered by the closing node, extracts different instruction combination data with the same predicted number of people in the target area covered by the target wake-up node in the database, and constructs an instruction combination set; extracts the influencing factors of the environment configuration instruction according to historical data or real-time sensor data, and calculates the occurrence probability of the instruction combination data when calculating the wake-up time period, the light intensity in the target area covered by the target wake-up node, and the temperature difference between the service area and the target area covered by the target wake-up node, so as to calculate the recommendation index of the instruction combination data;

[0067] The statistical unit calculates the recommendation index for all elements in the instruction combination set according to the matching unit, generates a recommendation sequence from largest to smallest based on the recommendation index, and feeds back the first three instruction combination data in the recommendation sequence to the service central control.

[0068] Further, for the control module, the service central control displays the three instruction combination data on the service central control panel through a preset recommendation template, and generates voice data through a preset voice template and feeds it back to the user. Among them, the preset recommendation template includes the interface logic rules for displaying the recommendation sequence, and the preset voice template includes the voice generation rules for voice feedback; when the user selects an instruction combination, the selected instruction combination data is recorded in the database and fed back to the target central control; the target central control operates the corresponding device according to the selected instruction combination data, and when the corresponding device is turned on, voice data is generated through the preset voice template of the service central control and fed back to the user.

[0069] Please refer to Figure 2 , in the second embodiment: A method for remote control of smart home and smart cockpit, the method includes the following steps:

[0070] Step S100: Wake up the service central control, generate a target central control wake-up instruction by obtaining voice connection data, mark and record the time point or event of the target wake-up node in the database; verify the voice connection data through a preset voice verification system, and when the verification is successful, send the target central control wake-up instruction to the target central control to wake up the target central control;

[0071] Step S200: Extract the number of people in the service area covered by the target wake-up node in the database, construct a target number set, calculate the conversion index of the number of people in the target area, and predict the number of people in the target area covered by the closed node;

[0072] Step S300: Extract different instruction combination data with the same predicted number of people in the target area from the database, construct an instruction combination set, extract the influencing factors of the environmental configuration instruction according to historical data or real-time sensor data, calculate the recommendation index of the instruction combination data, and count the recommendation index of all elements in the instruction combination set to generate a recommendation sequence, and feed back the first three instructions in the recommendation sequence to the service central control;

[0073] Step S400: The service central control displays and gives voice feedback of the three instruction combination data to the user. When the user selects an instruction combination, the selected instruction combination data is recorded in the database and fed back to the target central control, and the target central control turns on the corresponding device and notifies the user that the corresponding device has been turned on.

[0074] Further, the specific implementation process of the step S100 includes:

[0075] Upon user authorization, voice data of the user is collected through an audio sensor, keywords in the voice data are extracted according to a preset keyword library, a service central control wake-up instruction is generated to wake up the service central control;

[0076] Voice connection data is obtained through the service central control, keywords in the voice connection data are extracted according to the keyword library, a target central control wake-up instruction is generated, and the time point or event of the target wake-up node is marked and recorded in the database, where the target wake-up node represents the time point or event of the system triggering event;

[0077] The voice connection data is verified through a preset voice verification system. When the verification is successful, the service central control establishes a communication connection with the target central control and sends a target central control wake-up instruction to wake up the target central control, where the central control includes a smart home central control and a smart cockpit central control.

[0078] Further, the specific implementation process of step S200 includes:

[0079] The target central control extracts the number of people in the service area covered by the target wake-up node in the database, denoted as A, where the service area represents the dynamic or static communication range covered by the service central control, and the target area represents the dynamic or static communication range covered by the target central control; and predicts the number of people in the target area covered by the closing node, where the closing node represents the time point when the door induction signal in the target area first triggers a closing operation after the target wake-up node is triggered, and the target wake-up node and the closing node are in one-to-one correspondence;

[0080] Extract the number of people in the target area covered by the closing node when the number of people in the service area covered by the target wake-up node in the database is A, and construct a target number set B = {b n |n = 1, 2,..., N}, where b n represents the number of people in the nth target area covered by the closing node, and N represents the total number of types of the number of people in the target area covered by the closing node;

[0081] Count the number of data when the number of people in the service area in the database is A and the number of people in the target area covered by the closing node is b n and calculate the conversion index of the number of people b n in the target area: Among them, represents the conversion index of the number of people b n in the target area covered by the closing node when the number of people in the service area in the database is A, represents the number of data when the number of people in the service area in the database is A and the number of people in the target area covered by the closing node is b n in the database, represents the number of people in the service area in the database is A and the number of people in the target area covered by the closing node is bm The number of data at a certain time;

[0082] Statistically analyze the conversion indices corresponding to all elements of the target number set in the target area, and extract the number of people in the target area with the highest conversion index as the predicted number of people in the target area covered by the closing node.

[0083] For example: when the user controls the intelligent cockpit through the voice control of the smart home central control, according to the moment when the user issues an intelligent cockpit central control wake-up command to the smart home central control, it is marked as the target wake-up node; according to the target wake-up node, when extracting the target wake-up node, the number of people in the service area of the smart home central control is 5, and the target number set B = {b 1 , b 2 , b 3}; the number of people in the target area of the closing node is the number of data of b 1 which is 500, the number of people in the target area of the closing node is the number of data of b 2 which is 674, the number of people in the target area of the closing node is the number of data of b 3 which is 482, then Therefore, the predicted number of people in the target area of the closing node is b 2 .

[0084] Furthermore, the specific implementation process of the step S300 includes:

[0085] Extract different instruction combination data with the same predicted number of people in the target area from the database, and construct an instruction combination set U = {u i | i = 1, 2,..., I}, where the u i represents the i-th instruction combination data corresponding to the predicted number of people in the target area, I represents the total number of types of instruction combination data corresponding to the predicted number of people in the target area, and each instruction combination data is generated based on the historical operation records and real-time sensor data in the database and consists of one or more preset environment configuration instructions;

[0086] Extract the influencing factors of the environment configuration instructions according to the historical data or real-time sensor data. The influencing factors include the wake-up time period, light intensity, and temperature difference. Among them, the wake-up time period data is provided by the time module, and the light intensity and temperature difference data are collected by the real-time sensor and recorded in the database. The environment configuration instructions correspond to the dynamic adjustment of one or more influencing factors;

[0087] Extract the wake-up time period data, and calculate the occurrence probability of the instruction combination data u i where T represents the wake-up time period where the target wake-up node is located, represents the number of the instruction combination data u at the wake-up time period of T, i and Denote the number of instruction combination data u when the wake-up time period is T d as Denote the total number of instruction combination data when the wake-up time period is T

[0088] Extract the light intensity within the target area covered by the target wake-up node, and calculate the occurrence probability of the instruction combination data u i where Q represents the light intensity within the target area covered by the target wake-up node, Denote the number of instruction combination data u when the light intensity within the target area is Q as i Denote the number of instruction combination data u when the light intensity within the target area is Q as d Denote the number of instruction combination data u when the light intensity within the target area is Q Denote the total number of instruction combination data when the light intensity within the target area is Q

[0089] Extract the temperature difference between the service area and the target area covered by the target wake-up node, and calculate the occurrence probability of the instruction combination data u i where H represents the temperature difference between the service area and the target area covered by the target wake-up node, Denote the number of instruction combination data u when the temperature difference between the service area and the target area is H as i Denote the number of instruction combination data u when the temperature difference between the service area and the target area is H as d Denote the number of instruction combination data u when the temperature difference between the service area and the target area is H Denote the total number of instruction combination data when the temperature difference between the service area and the target area is H

[0090] Calculate the recommendation index of the instruction combination data u based on the influencing factors of the environment configuration instruction i as where p(T∪Q∪H) represents the occurrence probability of the instruction combination data u when at least one of the wake-up time period is T, the light intensity within the target area is Q, and the temperature difference between the service area and the target area is H occurs, and p(T∩Q∩H) represents the occurrence probability of the instruction combination data u when the wake-up time period is T, the light intensity within the target area is Q, and the temperature difference between the service area and the target area is H i occurs; i

[0091] Statistically calculate the recommendation index of all elements in the instruction combination set, generate a recommendation sequence from largest to smallest according to the recommendation index, and feedback the first three instruction combination data in the recommendation sequence to the service control center

[0092] Furthermore, the specific implementation process of the step S400 includes:

[0093] The service central control displays the combined data of three instructions on the service central control panel through a preset recommendation template, and generates voice data through a preset voice template and feeds it back to the user. Among them, the preset recommendation template includes an interface logic rule for displaying a recommendation sequence, and the preset voice template includes a voice generation rule for voice feedback; when the user selects an instruction combination, the selected instruction combination data is recorded in the database and fed back to the target central control;

[0094] The target central control operates the corresponding device according to the selected instruction combination data. When the corresponding device is turned on, voice data is generated through the preset voice template of the service central control and fed back to the user.

[0095] It should be noted that in this article, relational terms such as first and second are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual relationship or order between these entities or operations. Moreover, the term "comprising", "including" or any other variation thereof is intended to cover non-exclusive inclusion, so that a process, method, article or device comprising a series of elements includes not only those elements, but also other elements not expressly listed, or elements inherent to such process, method, article or device.

[0096] Finally, it should be noted that the above are only preferred embodiments of the present invention and are not used to limit the present invention. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art can still modify the technical solutions described in the foregoing embodiments, or perform equivalent replacements for some of the technical features. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included within the protection scope of the present invention.

Claims

1. A remote control method for smart home and smart cockpit, characterized in that: The method comprises the following steps: Step S100: Wake up the service central control, generate a target central control wake-up instruction by acquiring voice connection data, mark the time point or event of the target wake-up node and record it in the database; verify the voice connection data through a preset voice verification system, and when the verification is successful, send the target central control wake-up instruction to the target central control to wake up the target central control; Step S200: extracting the number of people in the service area covered by the target wake-up node from the database, constructing a target number set, and calculating the conversion index of the number of people in the target area, and predicting the number of people in the target area covered by the shutdown node; Step S300: extract different instruction combination data for the same predicted number of people in the target area in the database, construct an instruction combination set, extract the influencing factors of the environment configuration instructions according to historical data or real-time sensor data, calculate the recommendation index of the instruction combination data, and count the recommendation index of all elements in the instruction combination set to generate a recommendation sequence, and feed back the first three instruction combinations of the recommendation sequence to the service central control; Step S400: The service central control displays the three command combination data to the user through the panel and voice feedback. When the user selects the command combination, the selected command combination data is recorded in the database and fed back to the target central control. The target central control turns on the corresponding device and notifies the user that the corresponding device has been turned on.

2. A method for remote control of smart home and smart cockpit according to claim 1, characterized in that: The specific implementation process of step S100 includes: With the user's authorization, the user's voice data is collected through the audio sensor, keywords in the voice data are extracted according to the preset keyword library, and a service central control wake-up instruction is generated to wake up the service central control; Acquire voice connection data through the service central control, extract keywords in the voice connection data according to the keyword library, generate a target central control wake-up instruction, mark the time point or event of the target wake-up node and record it in the database, where the target wake-up node represents the time point or event of the system triggering event; The voice connection data is verified through a preset voice verification system. When the verification is successful, the service central control establishes a communication connection with the target central control, and sends a target central control wake-up command to the target central control to wake up the target central control. The central control includes a smart home central control and a smart cockpit central control.

3. A remote control method for smart home and smart cockpit according to claim 2, characterized in that: The specific implementation process of step S200 includes: The target central control extracts the number of people in the service area covered by the target wake-up node from the database, denoted as A, where the service area represents the dynamic or static communication range covered by the service central control, and the target area represents the dynamic or static communication range covered by the target central control; and predicts the number of people in the target area covered by the closing node, where the closing node represents the time point when the door sensing signal in the target area triggers the closing operation for the first time after the target wake-up node is triggered, and the target wake-up node corresponds to the closing node one by one; When the number of people in the service area covered by the target wake-up node is A, the number of people in the target area covered by the shutdown node is extracted from the database, and the target number set B = {b n |n=1,2,…,N}, where b n represents the number of people of the nth type in the target area covered by the closed node, and N represents the total number of types of people in the target area covered by the closed node; When the number of people in the service area of ​​the statistical database is A, the number of people in the target area covered by the closed node is b n The number of data is calculated as b in the target area. n Conversion index: in, Indicates that when the number of people in the service area of ​​the database is A, the number of people in the target area covered by the closed node is b n The conversion index, Indicates that the number of people in the service area of ​​the database is A and the number of people in the target area covered by the closed node is b n The number of data at Indicates that the number of people in the service area of ​​the database is A and the number of people in the target area covered by the closed node is b m The number of data at the time; The conversion indexes corresponding to all elements of the target number set in the target area are counted, and the number of people in the target area with the highest conversion index is extracted as the predicted number of people in the target area covered by the closed node.

4. A method for remote control of smart home and smart cockpit according to claim 3, characterized in that: The specific implementation process of step S300 includes: Extract different instruction combination data of the same predicted number of people in the target area from the database and construct the instruction combination set U = {u i |i=1,2,…,I}, where u i represents the i-th type of instruction combination data corresponding to the predicted number of people in the target area, I represents the total number of instruction combination data types corresponding to the predicted number of people in the target area, each instruction combination data is generated based on the historical operation records and real-time sensor data in the database, and is composed of one or more preset environment configuration instructions; Extracting influencing factors of the environment configuration instruction according to historical data or real-time sensor data, the influencing factors include wake-up time period, light intensity and temperature difference, wherein the wake-up time period data is provided by the time module, the light intensity and temperature difference data are collected by the real-time sensor and recorded in the database, and the environment configuration instruction corresponds to the dynamic adjustment of one or more influencing factors; Extract wake-up time period data and calculate instruction combination data u i The probability of occurrence Where T represents the wake-up time period of the target wake-up node. Indicates the instruction combination data u when the wake-up time period is T i The number of Indicates the instruction combination data u when the wake-up time period is T d The number of Indicates the total number of instruction combination data when the wake-up time period is T; Extract the light intensity in the target area covered by the target wake-up node and calculate the instruction combination data u i The probability of occurrence Among them, Q represents the light intensity in the target area covered by the target wake-up node, Indicates the instruction combination data u when the light intensity in the target area is Q i The number of Indicates the instruction combination data u when the light intensity in the target area is Q d Number of Indicates the total number of instruction combination data when the light intensity in the target area is Q; Extract the temperature difference between the service area covered by the target wake-up node and the target area, and calculate the instruction combination data u i The probability of occurrence Where H represents the temperature difference between the service area covered by the target wake-up node and the target area. Indicates the instruction combination data u when the temperature difference between the service area and the target area is H i The number of Indicates the instruction combination data u when the temperature difference between the service area and the target area is H d The number of It indicates the total number of instruction combination data when the temperature difference between the service area and the target area is H; Based on the influencing factors of the environment configuration instructions, calculate the instruction combination data u i Recommendation index: Among them, p(T∪Q∪H) indicates that the wake-up time period is T, the light intensity in the target area is Q, and the temperature difference between the service area and the target area is H. When at least one of the following occurs, the instruction combination data u i The probability of occurrence, p(T∩Q∩H) represents the instruction combination data u when the wake-up time period is T, the light intensity in the target area is Q, and the temperature difference between the service area and the target area is H i Probability of occurrence; The recommendation index of all elements in the instruction combination set is counted, and a recommendation sequence is generated from large to small according to the recommendation index, and the data of the first three instruction combinations in the recommendation sequence are fed back to the service control.

5. A method for remote control of smart home and smart cockpit according to claim 4, characterized in that: The specific implementation process of step S400 includes: The service central control displays the three command combination data on the service central control panel through a preset recommendation template, and generates voice data to feedback to the user through a preset voice template, wherein the preset recommendation template includes an interface logic rule for displaying a recommendation sequence, and the preset voice template includes a voice generation rule for voice feedback; when the user selects a command combination, the selected command combination data is recorded in a database and fed back to the target central control; The target central control runs the corresponding device according to the selected instruction combination data. When the corresponding device is turned on, voice data is generated through the preset voice template of the service central control and fed back to the user.

6. A remote control system for smart home and smart cockpit, characterized in that: The system comprises: a wake-up module, a prediction module, a matching module and a control module; The wake-up module includes an instruction unit and a wake-up unit, wherein the instruction unit is used to wake up the service central control, generate a target central control wake-up instruction, mark the target wake-up node and record it in the database; the wake-up unit is used to establish a communication connection with the target central control and wake up the target central control; The prediction module includes a conversion unit and a prediction unit. The conversion unit constructs an instruction combination set by extracting the number of people in the service area covered by the target wake-up node from the database, and calculates the conversion index of the number of people in the target area. The prediction unit predicts the number of people in the target area covered by the shutdown node based on the conversion index of the number of people in the target area. The matching module includes a matching unit and a statistical unit. The matching unit constructs an instruction combination set by extracting different instruction combination data of the same predicted number of people in the target area in the database, extracts the influencing factors of the environment configuration instructions according to historical data or real-time sensor data, and calculates the recommendation index of the instruction combination data; the statistical unit generates a recommendation sequence by statistically analyzing the recommendation indexes of all elements in the instruction combination set, and sorting them from large to small according to the recommendation indexes, and feeds back the first three instruction combinations of the recommendation sequence to the service central control; The control module and the service central control feed back the three command combination data to the user through the panel display and voice. When the user selects the command combination, the selected command combination data is recorded in the database and fed back to the target central control. The target central control turns on the corresponding device and notifies the user that the corresponding device has been turned on.

7. The remote control system for smart home and smart cockpit according to claim 6, characterized in that: The wake-up module includes an instruction unit and a wake-up unit; The instruction unit collects the user's voice data through the audio sensor, extracts keywords from the voice data according to a preset keyword library, generates a service central control wake-up instruction, and wakes up the service central control; obtains voice connection data through the service central control, extracts keywords from the voice connection data according to the keyword library, generates a target central control wake-up instruction, marks the time point or event of the target wake-up node and records it in the database, and the target wake-up node represents the time point or event of the system triggering event; The wake-up unit verifies the voice connection data obtained by the instruction unit through a preset voice verification system. When the verification is successful, the service central control establishes a communication connection with the target central control and sends a target central control wake-up instruction to the target central control to wake up the target central control. The central control includes a smart home central control and a smart cockpit central control.

8. The remote control system for smart home and smart cockpit according to claim 7, characterized in that: The prediction module includes a conversion unit and a prediction unit; The conversion unit extracts the number of people in the target area covered by the target awakening node from the database when the number of people in the service area covered by the target awakening node is A, and constructs a target number set; when the number of people in the service area is A in the database, the number of people in the target area covered by the closed node is b. n The number of data is calculated as b in the target area. n Conversion index; The prediction unit calculates the conversion indexes corresponding to all elements of the target number set in the target area through the conversion unit, and extracts the number of people in the target area with the highest conversion index as the predicted number of people in the target area covered by the closed node.

9. The remote control system for smart home and smart cockpit according to claim 8, characterized in that: The matching module includes a matching unit and a statistical unit; The matching unit extracts different instruction combination data of the same predicted number of people in the target area covered by the target wake-up node in the database based on the predicted number of people in the target area covered by the shutdown node, and constructs an instruction combination set; extracts the influencing factors of the environmental configuration instructions according to the historical data or the real-time sensor data, and calculates the probability of occurrence of the instruction combination data when calculating the wake-up time period, the light intensity in the target area covered by the target wake-up node, and the temperature difference between the service area covered by the target wake-up node and the target area, so as to calculate the recommendation index of the instruction combination data; The statistical unit calculates the recommendation indexes of all elements in the instruction combination set according to the matching unit, generates a recommendation sequence from large to small according to the recommendation indexes, and feeds back the first three instruction combination data of the recommendation sequence to the service central control.

10. The remote control system for smart home and smart cockpit according to claim 9, characterized in that: The control module, the service central control displays the three command combination data on the service central control panel through the preset recommendation template, and generates voice data through the preset voice template to feed back to the user, wherein the preset recommendation template includes the interface logic rules for displaying the recommendation sequence, and the preset voice template includes the voice generation rules for voice feedback; when the user selects the command combination, the selected command combination data is recorded in the database and fed back to the target central control; the target central control runs the corresponding device according to the selected command combination data, and when the corresponding device is turned on, the voice data is generated through the preset voice template of the service central control to feed back to the user.

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