1546 results about "Roomba" patented technology

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.

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 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.

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 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 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 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.

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.

The invention discloses a virtual hotel guide customization system based on intelligent optimization and multi-modal interaction, which relates to the technical field of virtual reality and augmented reality application and comprises a multi-source data acquisition module, a VR guide module, an AR customization module, a user interaction interface and a data storage management module. The multi-source data acquisition module acquires hotel 3D data and user behavior data, the VR guide module plans a user moving path, the AR customization module adjusts room layout according to user behaviors and selects an optimal scheme, and the user interaction interface provides touch voice interaction. Through the intelligent optimization and multi-mode interaction technology, personalized navigation and room layout customization are realized, the user experience is improved, the optimal path is planned, the layout is intelligently adjusted according to the user behavior, the touch voice interaction interface is friendly, the data security is guaranteed through the encryption storage technology, and the user experience is improved. And an innovative solution is provided for the technical field of virtual reality and augmented reality application.

The invention discloses a fire spreading prediction method, a server and a storage medium, and the method comprises the following steps: 1, collecting fire related data from a sensor layer and a block chain layer, and carrying out the preprocessing of the fire related data; and 2, inputting the preprocessed fire related data into a fire spreading prediction model for prediction to obtain a fire spreading trend. According to the method, the change of the fire along with the time is accurately grasped through the LSTM, the GCN accurately predicts the spreading path of the fire in the space, the spatial-temporal characteristics can be integrated through the fusion of the LSTM and the GCN, and the fire spreading probability of each room is given. The method is suitable for fire-fighting early warning of various buildings such as shopping malls, office buildings and residences, effectively assists fire-fighting decision making, plans rescue paths and resource allocation in advance, and reduces fire hazard and loss.

The application discloses a room semantic segmentation method, which comprises the following steps: S1, acquiring a topographic map of a house, detecting door features on the topographic map, and generating a setting area based on the detection positions corresponding to the detected door features; S2, segmenting the setting area to segment out doors from the setting area, and then verifying the segmented doors to determine the shapes and positions of the doors; and S3, based on the shapes and positions of the doors, performing semantic classification on the topographic map, and then generating a topographic map after the semantic classification. The room semantic information of a grid image is recognized and segmented in a deep learning manner, the understanding of a scene semantic by a robot is improved, and different cleaning strategies or other work can be used for different rooms.

The invention relates to the technical field of smart home, in particular to a smart home control method and system based on multi-modal fusion and deep learning. The method comprises the steps of triggering a data acquisition instruction, and performing human body data acquisition; acquiring human body data, and generating a global human body motion track sequence according to the preprocessed human body data; predicting a human body track target point and a space region; acquiring a human body track target point and spatial region data, and predicting a target electric appliance and a use probability thereof; the use probability of the target electric appliances is obtained, the target electric appliances are sorted, and electric appliance starting and standby operation is carried out; the system comprises a data acquisition module, a motion trail sequence generation module, a prediction module, a target electric appliance prediction module and an electric appliance operation module. Based on the human body track generated by sensor data, the corresponding electric appliances are pre-started by predicting the room where the user is about to arrive and the electric appliances possibly used by the user, so that multi-scene and multi-space coverage is realized, and a complex indoor environment can be met.

The invention discloses a control method of a multi-split air conditioner based on load self-adaption and an air conditioning unit, and relates to the technical field of air conditioner control. The technical problems that when the multi-split air conditioner operates at small load at night, due to the fact that the output capacity is not matched with the required load, the control mode is passive, and self-adaptive adjustment is insufficient, a unit is started and stopped frequently, room temperature fluctuates, and a user feels uncomfortable are solved. Each indoor unit is independently controlled, a load self-adaptive matching algorithm is adopted, room loads are calculated through real-time monitoring, matched output capacity loads are generated according to real-time load changes in respective rooms, and independent control logic is generated; the outdoor unit calculates the supply capacity according to the parameter change of each indoor unit, realizes load self-adaptive adjustment based on the combined control of the compressor frequency and the fan rotating speed, and automatically optimizes and iterates the room load through the real-time matching and automatic optimization of the output capacity of the outdoor unit and the room load on the premise of not increasing hardware. And real-time supply and demand matching of loads in each room is realized.

The invention discloses an equipment management method and device, electronic equipment and a storage medium. The method comprises the following steps: configuring a Bluetooth anchor point array in each room of a management area; determining position information of terminal equipment based on the Bluetooth anchor point array; and determining room information corresponding to the terminal equipment according to the position information and a house type diagram corresponding to the management area. According to the embodiment of the invention, high-precision positioning of the terminal equipment can be realized through the Bluetooth anchor point array, the room information is automatically allocated to the terminal equipment based on the determined position information, manual setting by a user is not needed, and the room allocation efficiency and accuracy are improved.

An example method includes receiving 3D data of an interior of a building that has one or more stories and one or more rooms on the one or more stories. The 3D data is classified by receiving multiple 360 degree panoramic images of the interior, applying a trained model to classify the multiple 360 degree panoramic images, and determining, based on applying the trained model to classify the multiple 360 degree panoramic images, one or more room classifications for the 3D data. One or more story identifications of the one or more stories and one or more room identifications of the one or more rooms are generated. A property layout of the building that includes the one or more story identifications and the one or more room classifications is generated. The property layout is provided for display.

The invention discloses an urban activity prediction method and system based on a Transform framework and a denoising diffusion probability model, and the method can achieve the prediction of the urban activity of any building in any future time under the condition that the urban activity of any historical time is known through the trained model based on the Transform framework and the denoising diffusion probability model. The construction of the model specifically comprises the following steps: carrying out fine-grained division on spatio-temporal data according to a building and room units in the building, executing Z-Score standardization, inputting a spatio-temporal causal convolution module, adjusting a data structure to adapt to a Transform structure, carrying out mask processing, and enhancing the time sequence prediction capability by adopting a noise diffusion probability model framework. According to the method, high prediction precision can be realized under the condition of relatively short input time, high-precision prediction of urban activities can be realized on the aspects of large scale and small fine granularity, arbitrary multi-step prediction of urban activities under any time step is realized by using artificial intelligence for the first time, and the blank of artificial intelligence in urban activity prediction is filled.

In various embodiments, a room-based design application automatically generates a design for a floor structure of a building. In operation, the room-based design application generates blocks representing portions of the floor structure that are delineated by walls based on a room plan included in a computer-aided design of the building. The room-based design application modifies the blocks based on a spanning length to generate partitions. Each partition represents a different portion of the floor structure that can be spanned by a structural element that has the spanning length in at least one direction. Based on the partitions, the room-based design application determines wall classifications for the walls. The room-based design application generates at least a portion of the design for the floor structure based on the wall classifications and the partitions.

The utility model particularly relates to an automatic air interchanger for an indoor suite door of a passive building. The automatic air interchanger solves the problem that people having a rest are lack of oxygen or dizzy and lack of strength due to the fact that the concentration of indoor CO2 and PM2.5 cannot be detected in time during night rest of an existing passive building. A lock is arranged on the suite door, an outer ventilation opening is formed in an outer side plate at the top of the door pocket line, an inner ventilation opening located on the inner side of the suite door is formed in a top plate of the door pocket line, an air duct communicated with the outer ventilation opening and the inner ventilation opening is arranged between the outer ventilation opening and the inner ventilation opening, and a power transmission mechanism and a rotary ventilation mechanism are arranged in the door pocket line. Automatic ventilation of the public area and the indoor room is achieved, the CO2 concentration and the PM2.5 concentration in the room are equivalent to those in the public area, the CO2 and PM2.5 concentration detecting instrument installed in the public area can detect the concentration of harmful gas in the closed room in time, the fresh air system is started in time to convey fresh air into the room, the air cleanliness in each independent room is improved, and the indoor environment is protected. And the comfort level of the living environment is further improved.