LU508024B1 - A smart home control system and method based on Internet of Things - Google Patents

A smart home control system and method based on Internet of Things Download PDF

Info

Publication number
LU508024B1
LU508024B1 LU508024A LU508024A LU508024B1 LU 508024 B1 LU508024 B1 LU 508024B1 LU 508024 A LU508024 A LU 508024A LU 508024 A LU508024 A LU 508024A LU 508024 B1 LU508024 B1 LU 508024B1
Authority
LU
Luxembourg
Prior art keywords
user
data
module
time
equipment
Prior art date
Application number
LU508024A
Other languages
German (de)
Inventor
Xin Li
Original Assignee
Chongqing Vocational Inst Eng
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Chongqing Vocational Inst Eng filed Critical Chongqing Vocational Inst Eng
Priority to LU508024A priority Critical patent/LU508024B1/en
Application granted granted Critical
Publication of LU508024B1 publication Critical patent/LU508024B1/en

Links

Classifications

    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L12/00—Data switching networks
    • H04L12/02—Details
    • H04L12/12—Arrangements for remote connection or disconnection of substations or of equipment thereof
    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B15/00—Systems controlled by a computer
    • G05B15/02—Systems controlled by a computer electric
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L12/00—Data switching networks
    • H04L12/28—Data switching networks characterised by path configuration, e.g. LAN [Local Area Networks] or WAN [Wide Area Networks]
    • H04L12/2803—Home automation networks
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L67/00—Network arrangements or protocols for supporting network services or applications
    • H04L67/01—Protocols
    • H04L67/12—Protocols specially adapted for proprietary or special-purpose networking environments, e.g. medical networks, sensor networks, networks in vehicles or remote metering networks
    • H04L67/125—Protocols specially adapted for proprietary or special-purpose networking environments, e.g. medical networks, sensor networks, networks in vehicles or remote metering networks involving control of end-device applications over a network
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L67/00—Network arrangements or protocols for supporting network services or applications
    • H04L67/50—Network services
    • H04L67/535—Tracking the activity of the user
    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B2219/00—Program-control systems
    • G05B2219/20—Pc systems
    • G05B2219/26—Pc applications
    • G05B2219/2642—Domotique, domestic, home control, automation, smart house
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L67/00—Network arrangements or protocols for supporting network services or applications
    • H04L67/2866—Architectures; Arrangements
    • H04L67/30—Profiles
    • H04L67/306—User profiles

Landscapes

  • Engineering & Computer Science (AREA)
  • Computer Networks & Wireless Communication (AREA)
  • Signal Processing (AREA)
  • General Engineering & Computer Science (AREA)
  • Automation & Control Theory (AREA)
  • Health & Medical Sciences (AREA)
  • Computer Hardware Design (AREA)
  • Computing Systems (AREA)
  • General Health & Medical Sciences (AREA)
  • Medical Informatics (AREA)
  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Telephonic Communication Services (AREA)

Abstract

The invention relates to the technical field of intelligent home control and discloses an intelligent home control system based on the Internet of Things The invention predicts the next operation prediction of the user in real time by using the sensor data and the user input through the user behavior prediction module. The invention continuously optimizes the prediction of the next operation of the user in advance before the actual operation of the user through the regression model. The invention starts in advance through the real-time prediction result or the state of the equipment is already good before the operation of the user so as to respond quickly when the user needs, thus achieving the beneficial effect of faster interaction time of the household equipment.

Description

A smart home control system and method based on the Internet of Things LU508024
Technical fields
The present invention relates to the field of smart home control technology, specifically a smart home control system and method based on the Internet of Things.
Background technology
Smart home is the embodiment of IOT under the influence of the Internet. Smart home through the Intemet of Things technology will be home to a variety of equipment (such as audio and video equipment, lighting systems, curtain control, air conditioning control, network appliances, etc.) connected together to achieve interactive control and other functions and means.
Compared with ordinary home, smart home not only has the traditional function of living, both building, network communication, information appliances, equipment automation, providing a full range of information interaction functions. However, for the commonly used garbage cans and other equipment in the family, the interactive control under the Internet of Things has not been realized, thus, for the use of the family, the garbage cans do not bring the intelligent experience under the smart home for the user, and the convenience of its use needs to be further improved.
After searching, it is found that a smart home control system and method based on the Internet of Things with the public number of CN110488616A include an intelligent garbage can and a mobile terminal. The intelligent garbage can includes a processor and a visual sensor connected to the processor, speakers, voice acquisition unit, walking unit, weighing sensor and wireless communication unit; The vision sensor is used to collect the user's image, the speaker is used to output confirmation information according to the first control command, the voice acquisition unit is used to collect the user's feedback information, the walking unit is used to move to the user according to the second control command, the weighing sensor is used to measure the weight information of garbage, and the wireless communication module is used to upload the weight information to the mobile terminal; The processor is used to output the first control instruction according to the gesture action of the image analysis user, calculate the distance and plan the moving path, and output the second control instruction; The mobile terminal is used to receive weight information. The invention can realize intelligent human-computer interaction control, and its intelligent experience is better.
In the aforementioned technical solutions to improve the trash can so that it can carry out human-computer interaction, but still need to collect the information of the user to the trash can walk to determine the interaction, and so on the same pool, air conditioning, computers and lamps, these home equipment into the system need to collect the information of the user's obvious use of 1 the information to be able to carry out the interaction, at this time the user has been close to the | U508024 body of the device, the interaction time is too slow, can not predict the user's thoughts in time. By this time, the user is already close to the device, and the interaction time is too slow to anticipate the user's thoughts in time. invention content
Technical issues addressed.
In view of the shortcomings of the existing technology, the present invention provides a smart home control system and method based on the Internet of Things, which has the advantages of faster interaction time of home equipment, and the system can clearly prejudge the user's intention and start the home equipment that the user needs to use in advance, so as to solve the problems of the above technology.
Technical Programs.
In order to achieve the above purpose, the present invention provides the following technical solution: an intelligent home control system based on the Internet of Things, said control system comprising a historical information collection module, a user behavior prediction module, a device control and pre-starting module, an interaction feedback module, a mobile terminal module and a data communication and security module, said control system.
Historical information collection module is used to record the user's detailed information in the use of home equipment, including operating time, operating frequency, characteristic actions: gestures and voice commands and equipment status changes, the collected user data is stored in the database to support long-term data accumulation and querying, the application of data analysis technology to identify the user's behavioral patterns, the pattern for a specific period of time for the commonly used equipment and operating habits, based on the historical data to establish a user behavioral model, predict the possible operation of a specific situation; historical data to establish a user behavioral model, predict the possible operation of a specific situation Based on the historical data, user behavior model is established to predict the possible operation of the user in a specific situation.
The said user behavior prediction module is used to combine real-time data from sensors and user input, compare with the behavior model provided by the historical information collection module, predict the user's next operation in real time, use the regression model to continuously optimize the prediction accuracy, and process user behavior data in different time periods and scenarios.
Equipment control and pre-start module is used to communicate with home equipment, control the switching state of the equipment, adjust the parameters, according to the results of user 2 behavior prediction, pre-start or adjust the state of the equipment, real-time reception of the user's | U508024 feedback and actual operation, dynamic adjustment of the equipment settings.
The interaction feedback module is used to recognize the user's gestures, voice commands and other interaction modes through the camera and microphone, provide instant feedback according to the user's actual operation, confirm the operation through voice prompts or show the device status through the display.
The mobile terminal module is used to recommend commonly used settings and operations according to the user's historical behavior and current needs, enhancing the user's control convenience.
The data communication and security module is used to encrypt and protect user data to ensure information security.
Preferably, the expression for recording detailed information of a user in the use of a home device in said historical information collection module is.
H(t) = [T;(t), F,(t), M; (1), 0;(t), 5; (4)]
Among them.H;(t)denotes the useriDuring operating hours, thetthe history of the information recorded, theT;(t)denotes the userithe specific time of the operation. F;(t)denotes the useriFrequency of operation of equipment M;(t)denotes the useriCharacteristic actions used during operation include gestures and voice commands, the6;(t)denotes the useriThe change of state of the device during operation, theS;(t)denotes the useriSpecific operational actions on the equipment.
Preferably, the expression for establishing a user behavior model based on historical data in said historical information collection module is.
Ye = bi _1 + O2Ye_2 + + DpYe_p +0161 +06 5 + ++ + 046g + Er
Among themY,lts timetof the observations, the6,,0,,…, Ogis a moving averageMACoefficients.
Preferably, the real-time predictive behavior formula in said user behavior prediction module is. fe =f (X, ©) where , , and X,It is real-time data that includes sensor data and user input data.® are the model parameters.and the historical behavioral model isŸ;is the output of a predictive model constructed on the basis of historical data, and the actual observed behavior isY;;
The regression model optimization expression is.
The objective of the regression model is to optimize the prediction accuracy by minimizing 3 the prediction error,which is defined as.E, = Y, — %; LU508024
The loss function for the regression model is. L(©) = SM EZ, of whichNis the number of observed data points in the time period or scenario.
The optimization objective of the regression model is to minimize the loss function. 6 = argmin L (0).
Preferably, said data expression for processing user behavior data for different time periods and scenarios in the module for behavior prediction is.¥; = f(X,, ©, T,, S,) Among themT,is time characterized as a time period or date.
Said user behavior prediction module is comprehensively expressed as.
N
Y, = f(X,, ©), of which®* = arg min Li SC —f(Xe 0)” t=1
At the same time, the regression model was adjusted to time and scenario characteristics.
Ÿ = F(X, 0", Tu Sç)-
Preferably, said device control and startup module adjusts a device state expression as.
S = g(%)
The calculation of the device control command is represented as follows.
U, = Control(S, Se) where the current state of the device is thatS,, the target state isS,, predicted to beŸ,. the control instructions for the equipment areU,, the adjustment rule function isg(Ÿ;) °
Preferably, the timely feedback expression in said interactive feedback module is.
F, = Feedback (A (fa. f(S0, £00) fgU)is a gesture recognition function, thef,(X,)is a function that recognizes other interactions. Feedbackis a function that generates feedback based on the interaction state.
Preferably, the recommended expression in said mobile general segment module is.
R = Recommend(f, (H), f.(C))
His the user's historical behavioral data, theCis the current demand data. (fn (H)is a function that processes historical behavioral data, the(f,(C)is a function that processes the current demand data, theRecommendis the function that generates the recommendation results.
Preferably, said data communication and security module data encryption expression is.
C = E(D,K)
Among themDis plaintext data. Fis the encryption algorithm. 4
Key generation and management is a process to ensure the security of encryption key K. Key | U508024 generation is represented by the function K=G, where G is the key generation algorithm:
K=G.
A smart home control system and method based on the Internet of Things, comprising the steps of.
Step 1, data collection: the historical information collection module continuously records the user's operation data, including time, frequency, action and equipment status.
Step 2: Pattern recognition and modeling: through the analysis of historical data, identify user behavioral patterns and construct behavioral models.
Step 3, real-time prediction: user behavior prediction module based on real-time data and historical models, predicting the user's upcoming operations.
Step 4: equipment pre-start: the equipment control module, based on the prediction results, in advance of the start-up or adjustment of equipment settings to ensure that the equipment has been prepared before the actual operation of the user.
Step 5, interactive feedback: interactive feedback module real-time processing of user operations, providing instant feedback and personalized settings.
Step 6: Feedback and Optimization: The system records the user's feedback and actual operation data for subsequent analysis and optimization to improve prediction accuracy and user experience.
Compared with the prior art, the present invention provides a smart home control system and method based on the Internet of Things, with the following beneficial effects. 1, the present invention through the user behavior prediction module using sensor data and user input real-time prediction of the user's next operation, prediction through the regression model 1s constantly optimized, before the user's actual operation, in advance to prepare, through the real- time prediction results, in advance of the startup or adjustment of the device state in the user's operation before the user has been ready to the state of the device, so that in the user's need to respond quickly, the interaction feedback module by the The interaction feedback module provides instant feedback by recognizing user gestures and voice commands through the camera and microphone. The system can quickly recognize the user's interaction mode and provide instant feedback through voice prompts or the display screen. The history information collection module records the user's detailed operation data, including operation time, frequency, action and device status, which is used to build a user behavior model so that the system can understand the user's habits and preferences, based on which the system more accurately predicts the user's needs and further shortens the response time to achieve the goal of home device interaction. Based on these 5 data, the system can more accurately predict user needs and further shorten the response time, LU508024 which achieves the beneficial effect of faster interaction time of home devices. 2, the invention through the history of information collection module records the user in the home equipment use of detailed information, including operating time, operating frequency, characteristics of the action: gestures and voice commands, equipment status changes, the data is stored in the database and used for analysis, the household behavior prediction module combined with the sensor data and the user's real-time inputs, the use of history of behavioral models to predict the user's next operation, through the regression model Through the regression model, the prediction accuracy is continuously optimized, which makes the system's prediction of the user's intention more accurate. The system processes the user's operation feedback in real time through the interactive feedback module to further optimize the pre-starting and adjusting process of the equipment, and the actual operation of the user and the feedback data are used to continuously improve the prediction model, so that the system can more accurately predict the user's intention to achieve the beneficial effect of the system being able to clearly predict the user's intention and start up the home equipment in advance of the user's intention. The system is able to predict the user's intention more accurately and achieve the beneficial effect that the system can clearly predict the user's intention and activate the home equipments in advance.
The accompanying illustration
Figure 1 shows a schematic diagram of the method flow of the present invention.
Specific implementations
The following will be combined with the accompanying drawings in the embodiments of the present invention, the technical solutions in the embodiments of the present invention are clearly and completely described, obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by the ordinary technical personnel in the field without making creative labor under the premise, are within the scope of protection of the present invention.
Referring to FIG. 1, a smart home control system based on the Internet of Things, said control system comprising a historical information collection module, a user behavior prediction module, a device control and pre-starting module, an interaction feedback module, a mobile terminal module, and a data communication and security module, said control system.
Historical information collection module is used to record the user's detailed information in the use of home equipment, including operating time, operating frequency, characteristic actions: gestures and voice commands and equipment status changes, the collected user data is stored in 6 the database to support long-term data accumulation and querying, the application of data analysis | U508024 technology to identify the user's behavioral patterns, the pattern for a specific period of time for the commonly used equipment and operating habits, based on the historical data to establish a user behavioral model, predict the possible operation of a specific situation; historical data to establish a user behavioral model, predict the possible operation of a specific situation Based on the historical data, user behavior model is established to predict the possible operation of the user in a specific situation.
The said user behavior prediction module is used to combine real-time data from sensors and user input, compare with the behavior model provided by the historical information collection module, predict the user's next operation in real time, use the regression model to continuously optimize the prediction accuracy, and process user behavior data in different time periods and scenarios.
Equipment control and pre-start module is used to communicate with home equipment, control the switching state of the equipment, adjust the parameters, according to the results of user behavior prediction, pre-start or adjust the state of the equipment, real-time reception of the user's feedback and actual operation, dynamic adjustment of the equipment settings.
The interaction feedback module is used to recognize the user's gestures, voice commands and other interaction modes through the camera and microphone, provide instant feedback according to the user's actual operation, confirm the operation through voice prompts or show the device status through the display.
The mobile terminal module is used to recommend commonly used settings and operations according to the user's historical behavior and current needs, enhancing the user's control convenience.
The data communication and security module is used to encrypt and protect user data to ensure information security.
Said control method is generated based on a control system, said control method being.
Step 1, data collection: the historical information collection module continuously records the user's operation data, including time, frequency, action and equipment status.
Step 2: Pattern recognition and modeling: through the analysis of historical data, identify user behavioral patterns and construct behavioral models.
Step 3. real-time prediction: user behavior prediction module based on real-time data and historical models, predicting the user's upcoming operations.
Step 4: equipment pre-start: the equipment control module, based on the prediction results, in advance of the start-up or adjustment of equipment settings to ensure that the equipment has 7 been prepared before the actual operation of the user. LU508024
Step 5, interactive feedback: interactive feedback module real-time processing of user operations, providing instant feedback and personalized settings.
Step 6: Feedback and Optimization: The system records the user's feedback and actual operation data for subsequent analysis and optimization to improve prediction accuracy and user experience.
The user behavior prediction module uses sensor data and user input to predict the user's next operation in real time, and this prediction 1s continuously optimized through regression models to prepare the user in advance before the actual operation. In this way, the system can quickly respond to the user's needs, thus reducing the waiting time.
The prediction model is built based on real-time and historical data and optimized by regression model. The optimization of the model improves the accuracy by minimizing the prediction error and makes the prediction more accurate.
The device control and pre-start module starts or adjusts the device state in advance by predicting the results in real time. This means that the system has already prepared the state of the equipment before the user operates it, so that it can respond quickly when the user needs it. For example, if the system predicts that the user is about to turn on the air conditioner, it will start the air conditioner in advance and adjust it to the right temperature, so that the user can experience the expected effect immediately during operation.
The module also dynamically receives the user's feedback and actual operation, real-time adjustment of device settings, to further optimize the user experience and response speed.
The interaction feedback module recognizes the user's gestures and voice commands through the camera and microphone, and provides instant feedback. The system can quickly recognize the user's interaction mode and provide instant feedback through voice prompts or the display screen.
Timely feedback can reduce the interaction delay between the user and the system, so that the user's commands can be responded to quickly.
The historical information collection module records detailed user operation data, including operation time, frequency, actions and device status. These data are used to build user behavior models, which enable the system to understand user habits and preferences. Based on these data, the system can more accurately predict user needs and further shorten response time.
The mobile terminal module recommends commonly used settings and operations based on the user's historical behavior and current needs, and the recommendation system enables users to quickly find the required functions or settings, reducing the number of operating steps and thus improving interaction efficiency. 8
Although embodiments of the present invention have been shown and described, it is LU508024 understood to one of ordinary skill in the art that a wide variety of changes, modifications, substitutions, and variations of these embodiments can be made without departing from the principle and spirit of the present invention, the scope of which is limited by the appended claims and their equivalents. 9

Claims (10)

Claims LU508024
1. À smart home control system based on the Internet of Things, characterized in that said control system comprises a historical information collection module, a user behavior prediction module, a device control and pre-starting module, an interactive feedback module, a mobile terminal module, and a data communication and security module, said control system. Historical information collection module is used to record the user's detailed information in the use of home equipment, including operating time, operating frequency, characteristic actions: gestures and voice commands and equipment status changes, the collected user data is stored in the database to support long-term data accumulation and querying, the application of data analysis technology to identify the user's behavioral patterns, the pattern for a specific period of time for the commonly used equipment and operating habits, based on the historical data to establish a user behavioral model, predict the possible operation of a specific situation; historical data to establish a user behavioral model, predict the possible operation of a specific situation Based on the historical data, user behavior model is established to predict the possible operation of the user in a specific situation. The said user behavior prediction module is used to combine real-time data from sensors and user input, compare with the behavior model provided by the historical information collection module, predict the user's next operation in real time, use the regression model to continuously optimize the prediction accuracy, and process user behavior data in different time periods and scenarios. Equipment control and pre-start module is used to communicate with home equipment, control the switching state of the equipment, adjust the parameters, according to the results of user behavior prediction, pre-start or adjust the state of the equipment, real-time reception of the user's feedback and actual operation, dynamic adjustment of the equipment settings. The interaction feedback module is used to recognize the user's gestures, voice commands and other interaction modes through the camera and microphone, provide instant feedback according to the user's actual operation, confirm the operation through voice prompts or show the device status through the display. The mobile terminal module is used to recommend commonly used settings and operations according to the user's historical behavior and current needs, enhancing the user's control convenience. The data communication and security module is used to encrypt and protect user data to ensure information security.
2. A smart home control system based on the Internet of Things according to claim 1, 10 characterized in that: the expression for recording the user's detailed information in the use of a LU508024 home device in said historical information collection module is. H(t) = [T;(t), F,(t), M; (t), 0;(t), S,(4)] Among them.H;(t)denotes the useriDuring operating hours, thetthe history of the information recorded, theT;(t)denotes the userithe specific time of the operation.F;(t)denotes the useriFrequency of operation of equipment.M;(t)denotes the useriCharacteristic actions used during operation include gestures and voice commands, the6;(t)denotes the useriThe change of state of the device during operation, theS;(t)denotes the useriSpecific operational actions on the equipment.
3. a smart home control system based on the Internet of Things according to claim 1, characterized in that: the expression for establishing a user behavior model based on historical data in said historical information collection module 1s. Ye = PaYess + Date-z ++ PpYe-p +0160 +0260 0+ +0564 + Et Among themYIt's timetof the observations, the6;,0,,..,0,is a moving averageMACoefficients.
4. a smart home control system based on the Internet of Things according to claim 1, characterized in that: the real-time predictive behavior formula in said user behavior prediction module is. fr = f(X, ©) where , , and X,It is real-time data that includes sensor data and user input data.® are the model parameters,and the historical behavioral model isŸ,is the output of a predictive model constructed on the basis of historical data, and the actual observed behavior 1sY, ; The regression model optimization expression is. The objective of the regression model is to optimize the prediction accuracy by minimizing the prediction error,which is defined as.E, = Y, — %; The loss function for the regression model is. L(©) = SM EZ, of whichNis the number of observed data points in the time period or scenario. The optimization objective of the regression model is to minimize the loss function. 0= argmin L (©.
5. a smart home control system based on the Internet of Things according to claim 4, characterized in that: said data expression for processing user behavior data under different time periods and scenarios in the behavior prediction module is.Ÿ, = f(X,, ©, Te, S,) Among themT,is time characterized as a time period or date. 11
Said user behavior prediction module is comprehensively expressed as. LU508024 N % = f(X,, ©), of which@* = arg min id SC —f(Xe, 0)” t=1 At the same time, the regression model was adjusted to time and scenario characteristics. Ÿ = F(X, 0", Tu Sç)-
6. A smart home control system based on the Internet of Things according to claim 1, characterized in that: the expression for adjusting the state of a device in said device control and startup module 1s. S =9(%) The calculation of the device control command is represented as follows. U, = Control(S, S:) where the current state of the device is thatS,, the target state isS,, predicted to beŸ,. the control instructions for the equipment areU,, the adjustment rule function isg(Ÿ;) °
7. A smart home control system based on the Internet of Things according to claim 1, characterized in that: the timely feedback expression in said interactive feedback module is. F, = Feedback (A (fa. f(S0, £00) fo(I)is a gesture recognition function, thef,(X,)is a function that recognizes other interactions. Feedbackis a function that generates feedback based on the interaction state.
8. A smart home control system based on the Internet of Things according to claim 1, characterized in that: the recommended expression in said mobile total segment module is. R= Recommend(fn(H), f(C)) His the user's historical behavioral data, theCis the current demand data. (f, (H)is a function that processes historical behavioral data, the(f,(C)is a function that processes the current demand data, theRecommendis the function that generates the recommendation results.
9. A smart home control system based on the Internet of Things according to claim 1, characterized in that: said data encryption expression of the data communication and security module is. C = E(D,K) Among themDis plaintext data. Fis the encryption algorithm. Key generation and management is a process to ensure the security of encryption key K. Key generation is represented by the function K=G, where G is the key generation algorithm:
K=G. 12
10. a smart home control method based on the Internet of Things according to claim 5, LU508024 characterized in that said control method is generated based on a control system, said control method being.
Step 1, data collection: the historical information collection module continuously records the user's operation data, including time, frequency, action and equipment status.
Step 2: Pattern recognition and modeling: through the analysis of historical data, identify user behavioral patterns and construct behavioral models.
Step 3, real-time prediction: user behavior prediction module based on real-time data and historical models, predicting the user's upcoming operations.
Step 4: equipment pre-start: the equipment control module, based on the prediction results, in advance of the start-up or adjustment of equipment settings to ensure that the equipment has been prepared before the actual operation of the user.
Step 5, interactive feedback: interactive feedback module real-time processing of user operations, providing instant feedback and personalized settings.
Step 6: Feedback and Optimization: The system records the user's feedback and actual operation data for subsequent analysis and optimization to improve prediction accuracy and user experience.
13
LU508024A 2024-08-16 2024-08-16 A smart home control system and method based on Internet of Things LU508024B1 (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
LU508024A LU508024B1 (en) 2024-08-16 2024-08-16 A smart home control system and method based on Internet of Things

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
LU508024A LU508024B1 (en) 2024-08-16 2024-08-16 A smart home control system and method based on Internet of Things

Publications (1)

Publication Number Publication Date
LU508024B1 true LU508024B1 (en) 2025-02-19

Family

ID=94640017

Family Applications (1)

Application Number Title Priority Date Filing Date
LU508024A LU508024B1 (en) 2024-08-16 2024-08-16 A smart home control system and method based on Internet of Things

Country Status (1)

Country Link
LU (1) LU508024B1 (en)

Similar Documents

Publication Publication Date Title
JP6861373B2 (en) Control method and control system
EP4530889A1 (en) Device configuration method and system, and computer device and readable storage medium
CN104915225A (en) Method and device for controlling intelligent device
AU2013205564A1 (en) Integrative and multi-purpose location estimation
CN112702633A (en) Multimedia intelligent playing method and device, playing equipment and storage medium
CN104865927A (en) Method and apparatus for constructing user model, and equipment control method and apparatus
CN112770166A (en) Multimedia intelligent playing method and device, playing equipment and storage medium
JP2021179642A (en) Voice interactive processing methods, devices, electronics, storage media and programs
CN118942455A (en) Voice remote control method and remote control system
CN119247808A (en) Equipment control method, large model training method and device
CN111722693B (en) Power consumption adjusting method and device, storage medium, server and terminal
CN118585340A (en) A method for constructing edge data services and a method for training language models
LU508024B1 (en) A smart home control system and method based on Internet of Things
KR20150110877A (en) User based home automation method, apparatus thereof, and supporting method and apparatus therefor
CN114840761A (en) Push model training method, device, equipment, storage medium and program product
CN118450062B (en) Frame synchronization cooperative control method and control system based on double-machine linkage
CN115325603B (en) Method and device for adjusting backwater temperature of heat pump unit
CN115524991B (en) A method, device, switch and computer-readable storage medium for controlling intelligent equipment
CN117348434A (en) Intelligent home management system based on user living habit
WO2024008013A1 (en) Intelligent household device linkage scheme recommendation method and related apparatus
CN109408164A (en) Control method, apparatus, equipment and the readable storage medium storing program for executing of screen display content
CN115604046A (en) Electronic device control method, device and system, device and medium
CN114782221A (en) Hotel guest room service management system
CN115586727A (en) Automatic configuration method and device, control method and device, equipment and medium
CN121037209A (en) Equipment configuration methods, apparatus, electronic devices and readable storage media

Legal Events

Date Code Title Description
FG Patent granted

Effective date: 20250219