2008 results about "Roomba" patented technology

Examples assist in renovating a room, including receiving a first image of a room, being a digital image prior to a planned renovation, inputting the first image and a renovation prompt to a generative machine-learning (ML) model, being configured to generate an renovated room image from the input image and an input prompt, receiving, from the generative ML model, a second image of the room, the second image being the renovated room image, inputting the second image to a second ML model, the second ML model being configured to identify objects that appear in an input image and output a list of objects, and transmitting the second image and the list of objects to a user computing device, the list of objects being displayed as a list of items to upgrade the room to appear as shown in the second image.

The invention provides a room obstacle detection optimization method and system based on a cross-modal attention mechanism. Wherein a dynamic compensation coefficient is calculated by acquiring motion track data of the mobile equipment, and a stable visual coordinate system is constructed. Visible light and near-infrared wave band acquisition of the multispectral sensor is synchronously triggered, the visible light captures geometric deformation characteristics of a floor projection surface, and the near-infrared detects a local heat radiation abnormal area. And extracting a thermal feature connected domain conforming to periodic biological motion as a living obstacle, and marking a collision risk boundary of a static obstacle. And based on a living body motion law and a collision boundary deviation trend, synchronously optimizing the dual-band exposure parameters and updating the trajectory prediction model, and forming a closed-loop feedback link of sensing and planning. According to the technical scheme provided by the invention, the living body and the static obstacle are accurately distinguished in a dynamic environment, and the sensor parameters are adaptively adjusted to improve the real-time obstacle avoidance response capability.

A remote test apparatus is configured to simulate an environment of at least one remotely located room and configured to receive at least one air sample from the at least one remotely located room. The apparatus includes a sealed enclosure forming an interior cavity and including an inlet in connection with the at least one remotely located room and an outlet in connection with a sample collection unit. The sample collection unit is configured to communicate the at least one air sample from the remotely located room at a first flow rate. The apparatus further includes at least one sensor disposed in the interior cavity and at least one air transfer unit configured to transfer test air from the interior cavity of the sealed enclosure to the at least one sensor at a second flow rate.

The invention relates to the technical field of intelligent generation, and particularly discloses a decoration scheme generation system and method based on generative artificial intelligence, which utilize an artificial intelligence technology based on deep learning to analyze the demand of a user, extract the semantic feature of the decoration demand of the user, and meanwhile, generate the decoration scheme according to the semantic feature of the decoration demand. And feature learning is performed on a large number of indoor decoration elements, and an indoor decoration element feature library is established, so that a room decoration effect picture is intelligently generated based on the semantic association interaction features of the indoor decoration element set and the decoration demand of the user. Therefore, the room decoration effect picture can be automatically and intelligently generated for the user to refer to and select according to the personalized requirements of the user, so that the efficiency and the quality of decoration design are improved, and better decoration experience is provided for the user.

The following relates generally to light detection and ranging (LIDAR) and artificial intelligence (AI). In some embodiments, a system: receives LIDAR data generated from a LIDAR camera; measures a plurality of dimensions of a room of the home based upon processor analysis of the LIDAR data; builds a 3D model of the room based upon the measured plurality of dimensions; receives an indication of a proposed change to the room; modifies the 3D model to include the proposed change to the room; and displays a representation of the modified 3D model.

A system and method for real-time, identity-free personalization using deformable emotional trait vectors to dynamically adapt digital and voice-based experiences. Each user session is modeled as a behavioral object known as a Vectra, composed of fluidic traits—such as mass, viscosity, temperature, volatility, and texture—that evolve continuously in response to live behavioral, contextual, environmental, and voice-derived signals. These Vectras traverse a dynamically warped emotional space, the Vectraverse, influenced by ambient conditions including time of day, noise level, inventory urgency, and engagement rhythm. Gravitational pull toward predefined emotional goal attractors modulates system behavior, while a goal mutation engine reclassifies session intent when confidence decays or friction spikes. Outputs include tone modulation, content pacing, offer framing, and gamified reward logic—all executed without storing identity, login credentials, or historical profiles. The system supports modular deployment across voice, screen, signage, mobile, and in-room environments, and integrates with large language models, AI agents, and third-party personalization stacks via privacy-safe APIs and federated learning. Designed for zero-ID personalization, the platform enables emotionally intelligent, context-aware engagement across any surface or session.

The invention relates to the technical field of air conditioners, in particular to an air conditioner internet-of-things control method. An IoT (Internet of Things) module is integrated in each air conditioner, and environment data including temperature, humidity and air quality of a room are collected in real time through connection of an intelligent sensor and a cloud platform; data of all air conditioning equipment is summarized to form a centralized management system of equipment state and environment information; an intelligent cooperative control algorithm based on communication between the equipment is constructed by means of internet-of-things intercommunication between the air conditioning equipment; the air conditioning equipment detects environmental data in real time through a local sensor, accesses prediction data of an external environment including weather forecast and climate change trend, and adjusts a working mode in advance in combination with a self-learning function of the equipment; a multi-dimensional energy-saving optimization algorithm is adopted for intelligent control; meanwhile, the overall energy consumption is optimized in combination with external weather change and equipment use frequency; the optimization strategy comprises time period distribution and equipment priority control; and performing personalized user control based on big data analysis.

The invention discloses an autonomous visual semantic navigation system and method based on interactive semantic mapping, a semantic scene graph is constructed by sensing the environment through a first visual angle of a robot and combining top-down environment semantic priori, and the method comprises regional spatial distribution identification, object attribute and layout analysis and room type clustering. And in combination with priori knowledge, complete scene representation is formed, the scene graph can be dynamically adapted and updated according to real-time observation of the robot, and the accuracy and timeliness of scene representation are ensured. Besides, a high-level and low-level AI agent module cooperation mechanism is adopted, and the high-level AI agent module is responsible for understanding and decomposing navigation tasks and distributing subtasks and supervising the execution process; the low-layer AI agent module is responsible for further dynamic decomposition and execution of the subtasks and feeds back execution results to the high-layer Agent, a complete task closed-loop monitoring mechanism is formed, and the execution efficiency and robustness of the navigation tasks are improved.

The invention relates to the technical field of self-adaptive control, in particular to an operation period building energy-saving low-carbon control method and system based on artificial intelligence, and the method comprises the following steps: collecting and analyzing the room use condition and illumination intensity, and obtaining an activity type recognition result; according to the invention, based on real-time analysis of room use conditions and illumination intensity, use modes of different areas are identified, and in combination with natural light changes and indoor activity requirements, required illumination intensity and color temperature adjustment parameters are dynamically calculated, so that accurate matching of illumination environments is realized. A dynamic feedback mechanism is established by monitoring the adjustment state of the lighting equipment in real time in combination with the change of the room use mode, the lighting deviation is adaptively corrected, and energy waste is avoided. By introducing reinforcement learning, the ventilation strategy can be continuously optimized through historical data and real-time feedback, personalized air quality management is achieved, and single adjustment is not executed based on a fixed threshold value.

A conferencing system includes a plurality of microphones and an audio processing system that generates and evaluates machine-learning / artificial intelligence models to optimize acoustics of meeting rooms.

Example implementations are directed to recapturing or realigning a room or scene in an artificial reality (XR) environment as a three dimensional (3D) space. To initially capture a room, a user manually annotates, using an XR system, one or more walls around the XR system. The XR system then aligns or localizes itself relative to the room. Once a room is captured and stored, and the user in the future enters the room again, the XR system may not be able to align itself in the room due to, for example, lighting conditions. Rather than require the user to manually recapture every wall captured during the initial room capture, the XR system can select one wall for recapture and, after receiving an annotation or marking of the one wall from the user, use the selection to realign the XR system relative to the room.

The invention relates to an intelligent regulation and control method for a fan coil of a central air conditioner, relates to an internet of things technology, and aims to solve the problems that multi-source environment parameter data is large in noise, working condition modeling is inaccurate, and equipment regulation response and energy consumption optimization are not coordinated. A regulation and control system integrating multi-parameter distributed sensing, data preprocessing, feature extraction and cross-domain knowledge migration is provided. A high-quality structured data set is formed through multi-dimensional real-time acquisition of room temperature and humidity, fan current, valve opening, human traffic, external weather and building information and in combination with denoising, normalization, alignment and missing completion. And a multi-target neural network and digital twinborn simulation are utilized to realize load trend prediction, equipment abnormity early warning and virtual deduction of an adjustment strategy, an optimal adjustment time sequence window and an activation threshold are output, and dynamic adaptive control is realized in combination with reinforcement learning.

To provide a room structure in which living space is less likely to become narrow even when a bed is placed in the room.SOLUTION: A room structure comprises a pair of side walls 14, 15 provided on two sides in a room in parallel, bed support units 25 each fixed to the inner wall surface of the pair of side walls 14, 15, and a bed 26 supported by being stretched over the pair of bed support units 25. The bed 26 comprises multiple bed plates 27, 28 which are made adjacent by being arranged in the direction perpendicular to the direction where the bed 26 is stretched over the pair of bed support units 25 in plan view. By the above configuration, it is possible to reduce the size that the bed 26 occupies the room by stacking the multiple bed plates 27, 28 and removing the multiple bed plates 27, 28 from the pair of bed support units 25, and thus, living space is less likely to become narrow even when the bed is placed in the room.SELECTED DRAWING: Figure 1

Techniques and apparatuses are described that implement a smart-device-based radar system capable of performing location tagging. The radar system has sufficient spatial resolution to recognize different external environments associated with different locations (e.g., recognize different rooms or different locations within a same room). Using the radar system, the smart device can achieve spatial awareness and automatically activate user-programmed applications or settings associated with the different locations. In this way, the radar system enables the smart device to provide a location-specific shortcut for various applications or settings. With the location-specific shortcut, the smart device can improve the user's experience and reduce the need to repeatedly navigate cumbersome interfaces.

Techniques are described for using data capture devices at a building to automatically generate a building floor plan and to determine associated absolute location data for the generated floor plan, such as by associating separately captured GPS data or other absolute location data with the floor plan. In some situations, a building floor plan is automatically generated by analyzing visual data of images captured at multiple image acquisition locations by a camera device to determine room shapes of surrounding rooms, and GPS absolute location data is associated with the generated floor plan using additional data captured at other data capture locations at the building by a separate mobile device that moves independently from the camera device, such as by extending the absolute location data from the mobile device to the camera device's image acquisition location and its surrounding room shape.

The invention discloses a digital typesetting design system and method for a clean workshop enclosure structure based on a BIM technology. The digital typesetting design system comprises a room processing unit which comprises a room generating unit, a room merging unit and a room separating unit; the typesetting area division unit is used for distinguishing room practice, cutting ceilings, combining the ceilings, typesetting partitions and cancelling the partitions; the typesetting unit comprises typesetting configuration and one-key typesetting; the top plate typesetting and adjusting unit comprises ceiling typesetting, top plate adjusting, top plate dividing and top plate combining; the wallboard typesetting and adjusting unit comprises wallboard typesetting, wallboard adjustment, wallboard segmentation and wallboard combination; the optimization typesetting unit is used for optimizing non-standard boards of the wallboards; the plate coding unit comprises coding rule definition, automatic coding and non-standard combination; and the typesetting result output unit is used for generating a plate purchase list, a profile purchase list and a typesetting drawing. According to the method, rapid and refined generation, three-dimensional intelligent typesetting, non-standard plate optimization and numbering drawing of the building envelope model can be realized, the building envelope typesetting efficiency and quality are improved, and the problems of low typesetting efficiency and insufficient optimization in an existing method are solved.

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.

Methods and apparatus for spatial annotation of design plans in an AI-powered collaborative environment. It includes a controller to receive a static representation of a building's design plan and an AI engine to analyze raster images to identify design elements such as architectural aspects, walls, and rooms. An interactive user interface generates polygons and lines representing these elements, allowing users to select elements for annotation. The apparatus determines positional coordinates of selected elements, links annotations to these coordinates, and updates the interface in real-time for multiple users. Additional features include automated annotation suggestions, user interaction options like commenting and approval, and learning from user interactions to enhance future annotations. The apparatus can detect physical changes in design elements using cameras and update the interface accordingly. It supports dynamic collaboration and enhances the accuracy and efficiency of design plan annotations.

Aspects of the present disclosure involve a system comprising a computer-readable storage medium storing a program and a method for performing operations comprising: receiving a video that includes a depiction of one or more objects in a room within a home; determining a room classification for the room by processing the one or more objects depicted in the video; selecting one or more augmented reality items available for purchase based on the room classification and the one or more objects depicted in the video; and generating, for display within the video, the one or more augmented reality items that have been selected at a display position within the video corresponding to the one or more objects depicted in the video.

The invention belongs to the technical field of intelligent control, and discloses an energy optimization management system and method for hotel guest rooms, and the system comprises a central data pool unit which constructs a time sequence database cluster, and carries out the uploading and interaction of data between all units through a data bus; the existence sensing unit is used for integrating multiple sensors by adopting a sensing layer architecture to form a sensing network, capturing existence sensing data and generating a room existence state map based on the existence sensing data; the existence sensing data comprises guest room reservation information data, guest room environment data and guest information data; the partition environment control unit is used for obtaining customer preference data by analyzing a room existence state map; based on the guest preference data and the guest room environment data, selectively activating environment control of different guest room areas by adopting an intelligent optimization algorithm; and the hotel energy utilization rate and customer satisfaction are improved.

The embodiment of the invention discloses a scene map navigation method and device based on a knowledge base and a medium, and the method comprises the steps: receiving a task instruction of a current user based on a preset language large model, so as to judge whether the task instruction is associated with an existing instruction of a preset knowledge base; if not, acquiring the current location of the robot corresponding to the task instruction, and performing target search on the scene map according to the current location to determine the room to which the target object belongs; if yes, based on the current positioning of the robot corresponding to the existing instruction and the task instruction, performing target search to determine the room to which the target object belongs; and receiving the current location of the robot, the scene map and the task instruction to perform task planning to generate an action sequence corresponding to the task instruction, so as to execute navigation of each target position point in the action sequence based on a preset function packet in the scene map.

The invention discloses a building energy management method based on big data, and relates to the technical field of building energy management, and the method comprises the steps: collecting building environment, room cold and hot demands and historical energy consumption data through a long and short term memory network LSTM in combination with Bayesian optimization, constructing a short-term and long-term cold load prediction model, and dynamically adjusting a cold and hot water supply strategy; the cold and hot water supply adjusting part enables cold and hot water conveying to accurately meet different room requirements on the basis of cold supply optimization parameters in combination with variable-frequency water pump regulation and control, water supply flow optimization of all floors and cold and hot water pipe network balance adjustment; an error feedback correction mechanism is introduced, the deviation between a predicted value and an actual load is monitored in real time, if the error exceeds a threshold value, an LSTM model is automatically adjusted, cooling parameters are updated, the prediction precision is improved, cooling and heating load regulation and control errors are reduced, and the influence of temperature fluctuation on user experience is reduced; aiming at different room temperature control requirements, personalized energy supply is carried out based on real-time temperature and humidity, air velocity and user preference.

The invention discloses an electrical room ventilation opening arrangement optimization method, which comprises the steps of determining the optimal position of a ventilation opening of an existing electrical equipment room through Fluent software simulation, and counting each numerical value of the optimal position, including room volume, total equipment heat dissipation capacity, room air supply capacity, area size of an air supply outlet and the number of the air supply outlets; constructing and training a neural network model, taking each counted numerical value as the input of a neural network, and taking the optimal position of the ventilation opening as the output; calculating the air supply amount and the number of air supply outlets required by the electrical equipment room to be designed, determining the optimal position of the ventilation opening of the electrical equipment room to be designed through the trained neural network model, and finally verifying whether the result meets the requirement or not through Fluent software simulation. According to the method, the number of the ventilation openings required by the electrical equipment room can be reasonably calculated, the neural network is introduced, the positions of the ventilation openings are optimized, and the design efficiency of the electrical equipment room is improved.

The invention discloses a method and system for guiding an old person to go home through a door lock, and the method comprises the steps: calculating a lost score value through a lost score model according to a condition that a target door lock A detects that the old person fails in continuous verification for multiple times and stays overtime in front of the door, and judging that the old person is in a lost state when the score value exceeds a threshold value, and obtaining a lost judgment result; according to the door lock A, encrypting and broadcasting the elderly biological characteristics to all the door locks, receiving confirmation information returned by the successfully matched door lock B, and obtaining a target room positioning result; according to the floor topological data of the door lock A and the door lock B, generating an optimal guide path, and obtaining path data containing a passing door lock sequence; according to the path data, controlling lamp strips along the way to be lightened according to a preset mode, and cooperating with a directional sound box to play voice guidance; and sending a reset instruction to the path door lock according to the fact that the door lock B detects that the old person successfully unlocks or arrives. According to the embodiment of the invention, convenient, efficient and intelligent door lock guiding can be carried out, and precise guiding and supporting for the elderly are realized.

The embodiment of the invention relates to the technical field of air conditioner control, and discloses an optimization method for accurate control of room temperature, which comprises the following steps: acquiring tail end control information of each space area of a target building stored in a pipeline database; target temperature information set in all space areas in the target building is obtained, and operation state information of all devices in the air conditioning unit and the tail end control module is controlled according to the target control parameters; determining area state information of each space area in the target building; and the area state information is matched with the target area state, if matching is not consistent, the area state information and the target area state information are determined to determine adjusting parameters of the air conditioning unit, and the air conditioning unit of the target building is controlled, adjusted and optimized according to the dynamic adjusting parameters. According to the embodiment of the invention, accurate temperature control can be realized, and the temperature of each space region can be maintained in the target range set by the user, so that the comfort of the user is greatly improved.

The invention discloses a hotel check-in information management method and system based on a database, and belongs to the technical field of information management. Nodes and edges are defined based on the extracted data, node embedding is generated through a random walk method, a customer classification model is constructed, and classification labels of customers are generated; generating a room distribution result by constructing a linear programming model based on the classified customers in combination with the real-time room related information of the hotel; through short-time Fourier transform and BERT model extraction emotion features and text embedding, constructing an emotion analysis model and a demand recognition model, and generating an emotion score and a demand recognition result; and based on the customer classification, the room allocation result, the emotion analysis result and the demand identification result, using a logic rule to generate a personalized service recommendation list. An intelligent management mode from efficient data extraction, accurate customer classification and dynamic room allocation to real-time service response and recommendation is realized.

The invention discloses a building energy consumption management method and system based on a BIM building, and relates to the technical field of energy consumption management. In the system operation, energy consumption and environment data are continuously collected and cleaned facing the whole building partition, a building IoT, a BMS system and a BIM model are fused, cleaning, alignment and standardization processing are carried out, and the energy consumption management efficiency is improved. Building components, rooms and equipment in the BIM model are mapped to real-time data, a'building-floor-area-room-equipment 'hierarchical tree model is established, rolling prediction is performed on future energy consumption demands of each area based on dynamic factors of personnel density, equipment use and external climate, feed-forward control information is provided, and a prediction result and real-time feedback are combined to realize real-time prediction of energy consumption demands of each area. The method comprises the steps of generating a partition-level energy consumption control strategy, issuing a strategy instruction to a BMS system, providing safety protection and linkage control, monitoring energy efficiency and comfort in real time, detecting energy consumption abnormity, continuously optimizing parameters through strategy evaluation and self-learning, and forming long-term closed-loop improvement.

The invention provides an air conditioner load real-time monitoring and intelligent regulation and control system which comprises a water chilling unit located in a control room, fan coils located in all areas of the room, a temperature sensor, a people flow detector, a power detector and an illumination intensity detector and further comprises computing equipment, and a prediction model is operated in the computing equipment. The calculation module is used for calculating first correlation among the temperature, the heat production data and the valve opening in the time dimension; extracting data in the time dimension according to the first correlation, and calculating the first correlation among the temperature, the heat production data and the valve opening in the space dimension; the extraction module extracts data in a spatial dimension according to the first correlation, and is used for performing feature extraction on the extracted data to obtain feature data; and the regression module is used for predicting the feature data to obtain the valve opening at the next moment. The data is analyzed from the dimensions of time and space, prediction analysis is carried out by considering various data, and the prediction accuracy is improved.

The embodiment of the present invention relates to the field of air conditioning control technology, and discloses an optimization method for precise control of room temperature, including: obtaining terminal control information of each spatial area of ​​a target building stored in a pipeline database; obtaining target temperature information set for each spatial area in the target building, and controlling the operation status information of each device and terminal control module in the air conditioning unit according to the target control parameter; determining the regional status information of each spatial area in the target building; matching the regional status information with the target regional status, and if the match is inconsistent, determining the regional status information and the target regional status information to determine the adjustment parameters of the air conditioning unit, and controlling and adjusting the air conditioning unit of the target building according to the dynamic adjustment parameters. The embodiment of the present invention can accurately control the temperature and ensure that the temperature of each spatial area is maintained within the target range set by the user, thereby greatly improving the user's comfort.

Techniques are generally described for an artificial intelligence based interior designer system. In various examples, an image comprising a plurality of items arranged together in a room may be received. A visual representation and a positional representation of each item represented in the image may be determined. An output embedding may be generated based at least in part on the visual representation and the positional representation of each item represented in the image. At least one output item may be determined based at least in part on the output embedding. An image of the at least one output item may be displayed in association with the image comprising the plurality of items arranged together in the room.