194 results about "Home setting" patented technology

The invention discloses an intelligent household electrical appliance interaction control method and system, and the method comprises the following steps: collecting the operation state parameters, environment perception data and user behavior characteristics of each household electrical appliance in a living space in real time, and generating an environment perception data packet through a multi-modal data fusion model; constructing a user habit preference model library, generating a household appliance control strategy decision tree in combination with historical interaction records, and matching an optimal control strategy set according to a real-time scene type; and when a user active intervention signal or an environment sudden change event is detected, a dynamic strategy reconstruction mechanism is triggered, an instruction updating request carrying a priority identifier is broadcasted to the associated household appliance group, and a redistribution control instruction set is generated. The method has the following advantages and effects: multi-source environment data can be deeply fused, the user habit model is constructed in real time, and the method has a dynamic strategy reconstruction capability so as to solve the problems of response lag, strategy stiffness and energy efficiency imbalance in a complex home environment in the prior art.

According to the intelligent home environment intelligent regulation and control system and the control method thereof, various intelligent sensors are arranged, various environment data such as indoor temperature, humidity and illumination are monitored in real time, the data are preprocessed and then sent to a data analysis layer, data features are extracted according to the monitored data and historical data based on the deep learning technology, and user preferences are deduced; the control parameters are adjusted and sent to the equipment control layer, a specific instruction is sent to an indoor smart home, an air conditioner, a humidifier or a curtain and the like are controlled to accurately control the indoor environment, the living preference of a user is met, and in the process, the effect monitoring and dynamic adjusting layer monitors the adjusting condition in real time, and the user experience is improved. If the ideal effect is not achieved after adjustment, the equipment control layer is controlled to continue adjustment, in the process, the abnormal condition of the system is detected, the power consumption of the equipment and other data are monitored at the same time, normal work of the system is guaranteed, possible faults are predicted, a user is reminded in time, and safe and energy-saving operation of the whole system is guaranteed.

A smart lighting device, and a system including one or more smart lighting devices, that are well-suited for use in at-home setting. The devices may be configured as night lights, and can provide continuous monitoring of a person in the at-home setting and provide alerts to the person of potential fall risk areas in the home. Further, the devices may provide alerts to others (other designated persons / organizations), e.g., in the event of a fall or fall risk. Further, the devices may recognize unknown persons in the home, and provide alerts to others. The system may be configured to route these alerts to according to user preference and / or a severity of the detected situation / alert.

The invention relates to the technical field of smart home, and discloses a smart home environment regulation and control method and device based on multi-modal behavior perception, and the method and device can understand the home environment parameter preference of a user in different scenes through a home habit reference value. The current physiological state, behavior mode and environment condition of the user can be comprehensively captured by collecting multi-mode sensing data. And calculating a multi-modal data deviation value to quantify the difference between the current home environment and the user habits, and positioning environment factors needing to be adjusted. The multi-modal data deviation value is subjected to weighted fusion calculation according to the weight matrix driven by the current health state of the user, and the comfort degree deviation index is generated, so that the recognition accuracy of user requirements is improved, and personalized and dynamic comfort degree evaluation is realized. An intelligent regulation and control strategy is determined according to the comfort degree deviation index, precise regulation and control of the home environment in the fields of medical science and technology and home-based care for the aged are achieved, and the accuracy and adaptability of home environment parameter regulation and control are effectively improved.

The invention, which relates to the technical field of household hidden danger detection, discloses an AI-based household hidden danger intelligent detection and early warning system comprising an early warning center, a data acquisition module, a data processing module, an AI analysis module and an execution module. Operation data of each household device in a household environment is acquired through a data acquisition module, and data cleaning, numerical value normalization processing and feature interval screening are performed on the operation data of each household device through a data processing module, so that principal component feature data corresponding to each household device is obtained; the AI analysis module constructs an AI analysis model for carrying out hidden danger analysis on the household equipment, inputs principal component feature data of each household equipment to the AI analysis model to obtain hidden danger items and hidden danger coefficients of the household equipment, delimits hidden danger levels of the household equipment according to the hidden danger coefficients, and finally, determines the hidden danger levels of the household equipment according to the hidden danger coefficients. And the execution module adopts corresponding execution operation according to the hidden danger level of the household equipment.

The invention discloses an intelligent temperature control energy-saving system and method based on personnel position detection and prediction. The system monitors indoor personnel distribution and temperature and humidity in real time through the human body and environment sensing module; the behavior prediction module utilizes an LSTM deep learning model to analyze the historical moving track of the user and predict the next target room and the arrival time of the user in combination with the environment context; the environment regulation and control module starts equipment such as an air conditioner in the target room in advance to adjust to a comfortable state; and the energy efficiency optimization module is used for implementing energy-saving control on the unmanned room. According to the method, the crossing from passive reaction to active prediction is realized, and the energy utilization efficiency of the home environment is remarkably improved on the premise of ensuring the comfort.

The invention belongs to the technical field of augmented reality, and discloses an AR scenario furniture identification and dynamic removal system based on artificial intelligence, and the system comprises the steps: carrying out the multi-view image registration, furniture entity segmentation and shielding completion analysis based on the obtained hotel scene AR image sequence data, and forming a complete furniture contour feature; the style similarity of the furniture multi-dimensional feature vectors is analyzed, and a furniture style recognition result is obtained; the method comprises the following steps: acquiring AR scanning data of a home environment, performing furniture removal priority ranking through space conflict analysis and style coordination evaluation, generating a dynamic removal strategy, establishing furniture three-dimensional model data based on the dynamic removal strategy, and performing material texture mapping and shadow fusion to obtain a realistic rendering effect; an interactive optimization adjustment scheme is generated, and scene parameter real-time adjustment and optimization and visual effect improvement are realized through user feedback; the reality sense of virtual home display and the user experience effect are remarkably improved.

The invention discloses a smart home equipment cooperative control method and system based on edge computing, and relates to the technical field of smart home equipment cooperative control, and the method comprises the steps: employing multiple sensors to collect the temperature, humidity, illumination intensity and user behavior data in a home environment, and obtaining an original data set; preprocessing the original data set by adopting a data processing method to obtain a high-quality data set; constructing a multi-modal collaborative decision prediction model based on the high-quality data set in combination with an open-source large language model LLM, inputting the high-quality data set into the collaborative decision prediction model, and outputting a control strategy result; based on a control strategy result, performing instruction distribution and state synchronization on the smart home equipment by adopting a high-efficiency communication protocol between heterogeneous equipment to obtain an equipment operation instruction set; and based on the equipment operation instruction set, computing and storage resources of the edge nodes of the smart home equipment are distributed through a dynamic resource management and load balancing method, and a resource configuration scheme is obtained.

The invention belongs to the field of nursing robots, and particularly discloses a multi-robot collaborative operation method and system for home nursing of old people, and the method comprises the steps: building a virtual simulation platform which comprises a simulation robot, the old people and a home environment, a large motion planning model built based on the PaLM-E is deployed on the simulation robot; the multi-modal information comprises visual sense, touch sense, sound and temperature sensing information; multi-robot cooperative operation training is carried out based on a virtual simulation platform, so that the action planning large model is trained; multi-modal information and nursing task information about the old people are obtained and input into the trained motion planning large model, unit motion planning of all robots is obtained, and home nursing of the old people with multi-robot collaborative operation is achieved. According to the invention, personalized, efficient, comprehensive, safe and intelligent nursing services can be provided for old people.

The invention relates to the technical field of smart home control, and discloses a smart home equipment control system, which comprises a sensor unit used for collecting environment data and outputting sensor feedback data; the equipment control unit is used for controlling the operation state of the intelligent household equipment according to the feedback data of the sensor, and the equipment control unit comprises an air conditioner controller, a humidifier controller and an illumination controller; and the fuzzy control and adaptive adjustment module is used for receiving feedback data of the sensor. By adopting the technical means of game theory optimization, multi-module cooperation, predictive control, self-adaptive adjustment, fuzzy control and the like, the cooperation efficiency and the resource utilization rate between smart home devices are remarkably improved, environment changes and user requirements can be adapted in real time, the device state can be accurately adjusted, energy waste is reduced, the comfort level and energy efficiency of the home environment are improved, and the user experience is improved. The problems of fixed rules, insufficient energy efficiency optimization, conflicts among devices and the like in the prior art are solved.

The embodiment of the invention provides a smart home equipment control method and device, equipment and a medium. The method comprises the following steps: acquiring sensor data collected for a current home environment; determining environment state information of the current home environment and user state information of a user in the current home environment according to the sensor data; according to the environment state information and the user state information, determining to-be-adjusted target smart home equipment and generating a target control strategy for the target smart home equipment; and adjusting the target smart home device according to the target control strategy. According to the embodiment of the invention, the intelligent control of the intelligent home equipment is realized according to the environment state information and the user state information, and the comfort and convenience of home life are improved.

The invention provides a smart home control system of a single-chip microcomputer based on the 5G Internet of Things, and the system comprises a sensor module which collects environment data, a data processing module which integrates the data, and a deep Q network control module which is internally provided with a DQN algorithm model, learns and trains home environment data and user behavior data, generates a control strategy, and achieves the intelligent control of home equipment. According to the invention, the automation and intelligence level of the home environment can be effectively improved, and efficient, energy-saving and user behavior self-adaptive home equipment management is realized.

The invention discloses a map construction method of a body-equipped robot control system, a body-equipped robot and a medium. The method comprises the following steps: acquiring 3D point cloud data and a first environment image acquired when the body-equipped robot moves in a home environment; acquiring a second environment image acquired by a camera in the home environment; constructing a target three-dimensional home map according to the 3D point cloud data, the first environment image and the second environment image; and determining that the posture of the target object is changed according to a second posture of the target object in the target three-dimensional home map at the current moment and a third posture of the target object in the target three-dimensional home map at the previous moment. And dynamically recording the pose change of the target object from the third pose to the second pose in the target three-dimensional home map according to the time to obtain a target four-dimensional home map. According to the method, the four-dimensional home map is generated according to the pose changes of the object in the three-dimensional home map at different moments, and the intelligent control degree of the home robot is improved.

The invention discloses a smart home interconnection control method, system and device, and a medium. The method comprises the following steps: obtaining user commuting information and user preference information; calculating home interconnection time according to the user commuting information, and setting a home interconnection strategy according to the user preference information, the home interconnection time and the weather information; controlling the smart home to perform starting response according to the home interconnection strategy; according to the invention, intelligent regulation and control of a winter home environment can be realized by integrating user information, weather forecast information and intelligent home equipment; through intelligent calculation and execution, a more convenient and accurate window closing and air conditioner warm air opening scheme is provided for the user, the user experience of the intelligent home system is further improved, and the intelligence, the air conditioner heating efficiency and the control flexibility are improved.

The invention discloses a robot common sense reasoning method based on a graph neural network and a spatial knowledge graph, and the method specifically comprises the steps: S1, constructing an indoor common sense knowledge graph composed of entities and relationships through collecting and sorting common sense in an indoor home environment scene; s2, constructing an instance knowledge graph by using a visual relationship recognition method, and generating a triple from an article to a spatial relationship to an article in real time aiming at an actual article spatial relationship existing in a robot operation environment; s3, learning knowledge representation by using a propagation aggregation method in the graph neural network, representing entities and relationships in the knowledge graph into a continuous feature space, and realizing semantic representation of the entities and relationships in the spatial domain knowledge graph; and S4, reasoning indoor common sense by utilizing spatial domain knowledge graph representation, or designing related entity query, and reasoning similar entities by utilizing entity representation in the graph neural network model. By introducing a propagation and aggregation method of a graph neural network, the efficiency of common sense reasoning is improved.

The invention discloses a multi-device cooperative intelligent household electrical appliance control method, which belongs to the technical field of intelligent home furnishing, and specifically comprises the following steps: a household electrical appliance collects environment and self state data in real time, and when any device detects that the data exceeds a preset threshold value, a trigger message containing an event type code is broadcasted to a local area network; a device receiving the message calls a capability database, and a control parameter set containing operation instruction sequences of the device and associated devices is generated in combination with current environment parameters; the parameter sets are uploaded to a shared storage area, each device performs conflict detection on other parameter sets, and conflict marks and correction parameters are generated when output variables are monitored in a local simulation environment and a safety range is exceeded; two parameter sets with the least conflicts are selected according to the number of conflict marks to compare the difference, each device quantitatively scores according to a preset rule, finally the device with the highest score is selected as an execution scheme, and the device analyzes and executes a corresponding instruction; according to the invention, multi-device cooperative intelligent control is realized, and the efficiency and reliability of home environment regulation and control are improved.

The invention discloses an integrated system and method with body movement control in a home environment, and the system comprises a home task construction module which is used for constructing a simulation environment, designing home tasks, labeling task data, defining task attributes, and obtaining an original home task data set; the data enhancement module is used for performing enhancement processing on the data set by adopting a supervised fine tuning SFT method and a direct preference optimization DPO method; the evaluation index module is used for setting indexes for evaluating system performance; the HLP module is responsible for decision making and planning adaptation of a tool, and generates an output O comprising a subtask and a selected bottom layer model m based on the input instruction I; the LLE module is used for converting the subtasks output by the HLP, the selected underlying model m and the inventory inv into model calling instructions, the selected underlying model m starts to execute work, error detection is carried out in real time in the execution process, the execution result is fed back to the HLP, and the execution process is recorded. The system has excellent performance.

An air controlled off-loading device that provides the ability for a less mobile individual to adjust themselves in bed with or without the assistance of a caregiver as well as allowing a caregiver to boost this individual up in a bed or chair in the home setting. The device includes a rectangular pad having a plurality of attachment sites for removably attaching inflatable wedges. The attachment sites including a plurality of hook and loop fasteners mounted to the upperside of the pad. A plurality of inflatable wedges are removably secured to the plurality of hook and loop fasteners mounted to the upperside of the pad.

The invention discloses a sleeping posture monitoring method and device, equipment and a readable storage medium, and relates to the technical field of sleeping posture monitoring, and the method comprises the steps: obtaining the point cloud data of indoor information through a depth camera; from the point cloud data of the indoor information, separating the point cloud data of the sleeping posture of the human body through preprocessing; taking the point cloud data of the human body sleeping postures as input, and obtaining sleeping posture categories through a trained convolutional neural network classification model; and judging whether the sleeping posture state of the user accords with the setting or not through the sleeping posture category, and sending prompt information when the sleeping posture state of the user does not accord with the setting. According to the sleeping posture monitoring method, the inconvenience caused by using wearable equipment or using a bed pressure sensor in an existing sleeping posture recognition method is overcome, the privacy problem and the light interference problem caused by using an image acquisition camera are also avoided, the sleeping posture of the user can be accurately acquired by using the millimeter-level depth camera, and the user experience is improved. And the practicability of sleeping posture monitoring in a home environment is improved.

The invention belongs to the crossing field of smart home and health Internet of Things, and discloses a home Internet of Things old-age care monitoring and service system and method based on artificial intelligence, and the system comprises a sensing layer, a network layer, and an application layer. The sensing layer is used for acquiring monitoring data of the old and the home environment; the network layer is used for enhancing and transmitting the monitoring data; and the application layer is used for comprehensively scoring the old people according to the monitoring data. The system is an intelligent old-age care system integrating multi-mode sensor data, edge computing optimization, dynamic communication protocol switching and an artificial intelligence algorithm, and is used for monitoring the health condition of the old in real time, guaranteeing the home safety and providing personalized life services.

The invention relates to the technical field of home environment detection, and particularly discloses a smart home monitoring and early warning method and system based on Internet of Things sensing equipment, and the method comprises the steps: carrying out the statistics of the operation data of each piece of home equipment, and obtaining an operation matrix; determining a color value parameter of each equipment contour in real time according to the operation matrix, and updating the home map at the corresponding moment; determining an abnormal value at each position according to the home map at each moment, and determining an image acquisition frequency at each position according to the abnormal value at each position; acquiring images at each position based on the image acquisition frequency, inputting the trained risk identification model, and outputting a risk identification result; according to the invention, periodic analysis is carried out on the working parameters of various home devices, whether the home devices are abnormal or not is judged, a selective image acquisition and detection process is carried out on the whole home environment according to the judgment result, in the process, the number of images needing to be acquired is sharply reduced, and the power consumption is greatly reduced.

The invention relates to a home safety control method and system based on big data analysis, and belongs to the technical field of home safety control, and the control method comprises the steps: obtaining an original sensor data flow in a home environment; preprocessing the original sensor data stream to obtain a synchronous calibration matrix; calculating a temperature change rate, a smoke concentration accumulation amount, a current harmonic component and a temperature current correlation coefficient to obtain a characteristic matrix; performing anomaly detection on the temperature change rate, and outputting a temperature isolation score; calculating a smoke risk coefficient according to the smoke concentration accumulation amount; reconstructing the current harmonic component, and calculating a current reconstruction error; determining an environmental risk coefficient according to the door and window state; carrying out weighted fusion on the data, and calculating to obtain a dynamic risk index; and sending a corresponding safety control instruction according to the dynamic risk index. According to the invention, the potential safety risk can be efficiently and accurately identified, the control strategy is adjusted according to the real-time data, and more efficient and safer home environment guarantee is provided.

The invention discloses an intelligent robot system integrating health monitoring and cleaning functions for old people, and belongs to the technical field of intelligent old people nursing auxiliary equipment. According to the system, through cooperative work of the health monitoring module, the cleaning module, the interaction module, the control module and the communication module, health monitoring, intelligent cleaning and convenient interaction of old people in a family scene are achieved. The health monitoring module integrates the functions of blood pressure detection, medicine taking reminding and fall detection, and supports multi-dimensional health data acquisition and cloud transmission; the cleaning module realizes an efficient cleaning task through dual-mode control and intelligent path planning; the interaction module adopts a voice recognition mode and a touch control operation mode and adapts to the use habits of the old. And the control module dynamically coordinates health monitoring and cleaning functions through a multi-modal data fusion algorithm and a priority scheduling strategy, and preferentially processes emergency health requirements. The communication module supports dual-network encryption transmission, and collaborative management of local equipment and a cloud is realized. The system breaks through the bottleneck of function isolation of traditional equipment, improves the life safety and convenience of old people through an intelligent algorithm and an aging-suitable design, and has the advantages of high integration level, high adaptability and remote management capability.

The invention relates to the field of visual analysis, in particular to a visual analysis method for a domestic robot. The method comprises the following steps: acquiring a real-time following image, and determining real-time behavior information and home environment information according to the real-time following image; acquiring following information, and determining abnormal following information according to the real-time behavior information, the following information and the home environment information; and adjusting the following information according to the abnormal following information and the real-time following image, determining real-time following information, and following the family members according to the real-time following information. According to the method, the real-time following information is determined by acquiring the following image in real time and accurately identifying and analyzing the behavior information and the environment condition of the family members. By comparing the real-time behavior information with the home environment, an abnormal following condition is detected, so that the following path and behavior are optimized. The adjusted following information ensures that the robot more intelligently adapts to the activities of the family members, the home automation experience is improved, and the safety of the family members is enhanced.

The invention discloses a smart home cooperative control method and system based on multi-modal information fusion, and relates to the technical field of smart home control. Comprise but not limited to visual information acquired by an image sensor, audio information acquired by a sound sensor and physical environment information of temperature, humidity and illumination intensity acquired by various environment sensors; the collected multi-modal information is preprocessed, and data of different formats and features are converted into a unified recognizable form. Multi-modal information is collected through various image sensors, sound sensors and environment sensors, the home environment can be sensed in an omnibearing and three-dimensional mode, compared with a traditional single sensor sensing mode, richer environment details can be obtained, the indoor temperature can be sensed, the activity condition of indoor personnel can be known through visual information, and the intelligent home environment sensing system is suitable for being popularized and applied. And a more comprehensive data basis is provided for cooperative control of the smart home equipment.

1. The name of the design product: folding ground mat. 2. The use of the design product: folding ground mat used in home environment. 3. The design points of the design product: in shape. 4. The picture or photo that best shows the design points: front view.

This invention provides a smart home remote control system, relating to the fields of visual detection and intelligent control, comprising: a dynamic home feature calibration module: screening and classifying smart home devices controllable by the remote control system, and acquiring initial three-dimensional coordinate values ​​of feature points through visual detection technology; a static home environment ground state acquisition module: acquiring initial environmental feature data of static home devices in real time; a control target routing module: selecting whether to call the dynamic home response verification module or the static home response verification module; a dynamic home response verification module: calculating the dynamic home change index and outputting the dynamic home control judgment result; and a static home response verification module: calculating the static home environment change index and outputting the static home control judgment result. This invention enables the system to objectively and accurately confirm whether the control has been truly executed and produced the expected effect, even when the home devices themselves do not provide status feedback or the feedback is unreliable.

A portable method and device for monitoring sodium ions in breast milk, belonging to the field of lactation status feedback, is disclosed. The method is executed after a breast milk container is installed on the main unit and includes the following steps: breast milk container identification and batch parameter loading, posture detection and gating, dry self-calibration of the electrical channel, thermal pulse temperature response acquisition and thermodynamic virtual volume feature extraction, low-frequency / high-frequency electrical response acquisition and bubble interference feature extraction, optical scattering signal acquisition and fat / turbidity proxy feature extraction, and geometric boundary compensation, temperature compensation, milk fat shielding compensation, and sodium ion concentration inversion based on the multi-dimensional features. It can also perform nursing guidance push, result storage, and edge-cloud collaborative updates. The device includes a main unit and a breast milk container. The main unit contains a heating film, a temperature probe, an optical turbidity detection module, and an electrode detection module connected to a four-electrode structure. This solution can improve the accuracy, stability, and repeatability of breast milk sodium ion detection in a home setting.

The invention relates to the field of intelligent equipment control, and provides a smart home cooperative control method based on the Internet of Things. The method comprises the following steps: analyzing historical state data of a smart home environment through machine learning to obtain an equipment association map, and encoding collected real-time state data to obtain a global state vector; clustering by combining the global state vector and the equipment association map to obtain a life scene mode set, extracting a trigger condition to form a library, and inputting the global state vector into a neural network to predict scene occurrence probability distribution; determining standard equipment state configuration corresponding to a target scene in the trigger condition formation library according to scene occurrence probability distribution, and performing multi-target optimization on standard equipment state control to obtain a cooperative control strategy list; and executing instructions in groups on the cooperative control strategy list according to the equipment network partitions, and performing monitoring compensation in the execution process. According to the invention, the scene intelligent control accuracy of the intelligent equipment is improved.

The utility model discloses an assembly combined cabinet, which comprises three cabinet bodies and two limiting cover plates, the top of each cabinet body is provided with a concave part, the top edge of each cabinet body is provided with a baffle plate which is erected around the periphery of the concave part, and the cabinet bodies can be arranged in the same row or arranged in a mutually vertical manner that long and short sides are connected; the bottom of the limiting cover plate extends downwards to form a first inner groove plate, a second inner groove plate and an outer edge plate, the first inner groove plate, the second inner groove plate and the outer edge plate are distributed corresponding to baffles of the cabinet bodies, the limiting cover plate covers the adjacent cabinet bodies in a sealing mode, and the first inner groove plate, the second inner groove plate and the outer edge plate are combined pairwise to form mortise structures which are matched with the baffles on the adjacent cabinet bodies to be inserted into the corresponding mortise structures to be clamped. Therefore, the adjacent cabinet bodies can be conveniently fixed and limited, additional installation auxiliary tools are not needed, field installation is rapid, and a user can conveniently adjust the form of the combined cabinet body at any time according to the requirements of the home environment.