118 results about "Home based" patented technology

The invention provides a home abnormal state signal detection method and system based on multi-modal sensing, and relates to the technical field of detection, and the method comprises the steps: collecting human body motion, acoustics and environment parameters through a millimeter wave radar, an acoustic sensor and an environment sensor, inputting the parameters into a deep fusion network, a spatio-temporal attention mechanism and a multi-scale convolutional neural network are used to extract a spatio-temporal feature sequence, and joint probability features are formed in combination with an acoustic feature spectrum analysis result. And inputting the joint probability features into a time sequence knowledge graph, and obtaining scene adaptive features after processing by a graph attention network and a double-flow auto-encoder network. And finally, the multi-task learning network is combined with the risk propagation neural network and the recursive neural network to carry out anomaly prediction and risk level evaluation, and is combined with historical early warning information to output an early warning strategy. According to the invention, multi-modal data can be effectively fused, the accuracy and reliability of home abnormal state detection are improved, and a more accurate risk assessment and early warning strategy is provided.

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 plurality of dimensions of the home based upon processor analysis of the LIDAR data; builds a 3D model of the home based upon the measured plurality of dimensions; and displays a representation of the 3D model by visually navigating through the 3D model.

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.

This invention relates to a system and method that enhances user interaction and marketing effectiveness through advanced data integration and personalized algorithms. The system and method collects detailed user data through body scanning and questionnaires, creating comprehensive profiles using machine learning. These profiles facilitate precise matching of influencers with businesses based on physical attributes, audience demographics, and content preferences. The system generates AI-driven marketing personas tailored to specific demographics and enables live shopping integration with social platforms. A novel double-blind review mechanism ensures transparent feedback between businesses and influencers. The platform supports group profiles that aggregate multiple users' data, enabling family-based shopping with privacy controls and preference weighting. The system continuously refines its algorithms using campaign performance data and engagement metrics, optimizing future matches and marketing strategies. This innovative approach significantly improves marketing ROI, user engagement, and personalization for digital social interaction and targeted marketing.

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 discloses a scene adaptive recommendation method in smart home based on multi-modal data, and relates to the technical field of multi-modal data processing. According to the method, firstly, scene classification is carried out based on multi-mode sensing data for a smart home scene, a current life scene of a user is accurately recognized, meanwhile, an equipment linkage state is analyzed in combination with a classification result, whether equipment operation is matched with a scene requirement or not is judged, and then a scene mode is recognized according to a linkage analysis result to generate preliminary recommendation; whether the dynamic weight space relation model of the user is updated or not is judged, finally, the recommendation effect is quantified according to the weight adjustment judgment result, the recommendation strategy is optimized through two-way feedback, the adaptability to the user requirement is improved, and the user experience is improved. A full-process closed loop of multi-modal data classification, equipment linkage analysis, mode recognition recommendation, weight dynamic updating and effect quantitative feedback in a smart home scene is realized, and the problem that the intelligent degree of scene recommendation in smart home is not high in a user behavior dynamic change scene is effectively solved.

A facility for estimating the value of a distinguished home is described. The facility trains a forest of decision trees to estimate valuations for homes within the geographic area where the distinguished home is located using data including both previous home sale transaction prices and synthetic sale transaction prices based on listing prices. The facility accesses information about the distinguished home's attributes and applies each decision tree in the forest to that information, generating a number of estimated valuations. The facility determines an overall valuation for the distinguished home based on the valuations generated by the decision trees.

The invention discloses a household elderly falling monitoring system and method based on feature fusion, and relates to the technical field of falling monitoring. The technical key points are as follows: firstly, the reasonability and effectiveness of an obtained detection result are guaranteed to obtain first gait image recognition of the home elderly to estimate the posture of the home elderly, the improved OpenPose network and CoordConv are utilized to replace VGG-16 into EfficientNet, the first gait of the home elderly is accurately monitored, the balance influence proportion is calculated for different gaits, and the balance influence proportion is calculated for the different gaits. According to the method, the probability that the old people have falling behaviors is judged to generate different risk signals, falling behaviors and postures under medium and high risk signals are further analyzed in a targeted mode, through deflection analysis, changes of human body postures are monitored in real time, characteristics of different falling postures are understood, different falling postures are independently and accurately modeled, and a second falling coefficient is generated; the tumble degree is accurately identified, and a foundation is laid for optimization of a subsequent model.

To provide a pipe joint that has strong pipe withdrawal resistance, is excellent in durability, and has a home base-shape recessed groove.SOLUTION: A home base-shape recessed groove 9 formed in a compressive deformable sleeve 7 has a large straddle angle θ, where a deep part tip 9A has a round shape with a specified large radius R1.SELECTED DRAWING: Figure 5

Computer-implemented methods and computer systems are disclosed herein as implemented by one or more local or remote processors, transceivers, servers, and / or sensors. The methods and systems include the one or more processors (i) determining an electric vehicle has a state of charge (SOC) below a predetermined threshold; (ii) if the SOC is determined to be below the predetermined threshold, determining homes capable of charging electric vehicles within a vicinity of, or a predetermined distance of, the low SOC vehicle's GPS location; (iii) from among the homes within the predetermined distance of the low SOC vehicle, ranking the homes based upon various factors; and / or (iv) scheduling a rendezvous or appointment for the low SOC vehicle with the highest ranked home for recharging the low SOC vehicle, the highest ranked home being equipped to recharge the low SOC vehicle and is available to charge the low SOC vehicle.

Devices are disclosed for home based electric vehicle (EV) charging. In one embodiment, a programmatic method includes receiving a first notification indicative of a first electrical coupling of an EV to an EV charger located at a first physical address. Upon receiving the first notification, the programmatic method further includes providing to a first display a first plurality of content options. The first display is co-located with the EV charger and the first plurality of content options are indicative of a first plurality of multimedia content streams to be provided to a second display. The programmatic method further includes receiving a second notification indicative of a first selection of the first plurality of content options by a user of the EV charger and storing the first selection in a memory.

The invention discloses infrared AI smart glasses for controlling smart home based on a voice recognition technology, and belongs to the technical field of smart home control. Comprising a glasses body, and a hardware system and a software system which are arranged on the glasses body, the hardware system comprises a microphone array, an AI processing chip, a wireless communication module, a loudspeaker and a power supply module, the microphone array is used for collecting voice signals of a user, the AI processing chip processes and analyzes the voice signals in real time, the wireless communication module realizes data mutual transmission between the glasses body and the smart home equipment, and the loudspeaker is used for transmitting the voice signals to the power supply module. The loudspeaker is used for receiving and playing the voice prompt information processed by the AI processing chip, and the power supply module supplies power to the microphone array, the AI processing chip, the wireless communication module and the loudspeaker; the software system is integrated on a voice recognition algorithm, a semantic understanding module, an equipment control module and a voice prompt module on an AI processing chip, and the voice recognition algorithm carries out preprocessing, feature extraction, model training and reasoning on voice signals.

The invention provides a communication method and a communication device applied to the field of wireless communication. In the technical scheme provided by the invention, when a user deploys a home base station and the home base station is in a closed mode and there is a demand for allowing a visitor terminal to access the home base station, a management terminal of the home base station can send first information to a first functional network element, and the first information indicates that the visitor terminal which is allowed to access the home base station is allowed to access the first functional network element. Therefore, the first function network element can trigger the flow of updating the signing data of the visitor terminal based on the first information, and the closed access group information corresponding to the home base station is stored in the signing data of the visitor terminal, so that the visitor terminal can access the network through the home base station to obtain network service.

This disclosure provides systems, methods, and devices for control and management of production home builders. According to aspects of the disclosure, computerized tools described herein may enable home builders to react more quickly and consistently to new data relating to market forces and home buyer demand. Some features disclosed herein may enable and provide improved performance metric tracking, including dynamically determining a pacing metric based on data. In some aspects, the system may determine a performance pace for a first plurality of homes based on a comparison of home status data for the first plurality of homes to performance data for a second plurality of homes. Such operations may beneficially enable effective pacing of home builder performance that more accurately matches the home sales pace to the home production pace. Additionally, the system may output instructions of actionable steps to improve home production and performance in the market.

The invention relates to the technical field of smart home, in particular to a smart home collaborative decision and adaptive agent construction method based on LLM. The method comprises the steps of receiving a user instruction to generate a family situation model, decomposing an abstract instruction into a sub-task sequence, identifying conflicts and negotiating consensus, calling a database interaction sub-agent to complete data operation, and injecting a query result to support subsequent task execution and full-link redisk to optimize system performance. Through context sensing, conflict pre-judgment and safety controllable database interaction modules, the problems of fuzzy instruction understanding, dynamic environment adaptation and data safety are solved, the intelligent level and the user satisfaction degree of the system are improved, and meanwhile the sustainable evolution capacity of the system is achieved.

The invention discloses a semi-supervised non-contact neonatal jaundice home intelligent early warning method based on image calibration, and the method comprises the steps: building a camera response function database, and building a color constancy depth model and a skin region segmentation network; designing a strong and weak enhancement strategy by using a large amount of label-free home data, constructing a time and context comparison learning module, and performing self-supervised training on a feature encoder; a small amount of labeled hospital data and a large amount of unlabeled family data are combined, and semi-supervised fine tuning is realized through pseudo label generation and supervised comparative learning; image sequences continuously uploaded by a user are input into the model, multi-day prediction of the bilirubin level is achieved, prediction uncertainty is quantified in combination with a Bayesian method, the risk boundary is dynamically adjusted, and personalized early warning is provided. According to the method, a user does not need to use a physical colorimetric card, color measurement errors caused by model differences of mobile equipment and variability of household illumination are inhibited from a data source, and the accuracy and robustness of subsequent jaundice assessment are improved; through a training framework combining self-supervised pre-training and semi-supervised fine tuning, the understanding ability and generalization performance of the model for the sequential characteristics of jaundice are improved.

The invention discloses a smart home illumination intensity monitoring and automatic adjusting method based on a sensor, and relates to the technical field of smart home illumination intensity monitoring and automatic adjusting, and the method comprises the following steps: installing an illumination sensor to monitor the indoor illumination intensity in real time, and collecting environment change data; the illumination sensor and the smoke sensor are integrated, an intelligent priority mechanism is combined, the user safety is guaranteed preferentially in an emergency, the emergency lighting system is started automatically, and the brightness is adjusted to ensure safe evacuation. An environment data fusion technology is adopted, various sensor data such as illumination, smoke, temperature and humidity are comprehensively analyzed, the living comfort is optimized, and the emergency response precision is improved. Meanwhile, based on the deep learning technology, the system can perform adaptive learning, optimize the emergency recognition and response capability, and improve the safety and reliability of the smart home.

The embodiment of the invention discloses a home base station position verification method and device, a node and a storage medium. The method comprises the following steps: a second node obtains first position information of a first node; based on the first position information and first information obtained in advance, performing position verification on the first node to obtain a position verification result; the first information represents the signing position of the first node.

This disclosure provides systems, methods, and devices for control and management of production home builders. According to aspects, computerized tools described herein may leverage trained machine learning (ML) models to automatically identify similar homes across a housing market for a more representative price comparison than typical market averages. In some aspects, the system receives a first set of parameter values corresponding to a first home associated with a first entity (e.g., a home builder) to extract a feature vector. The feature vector may be provided to a trained ML model that identifies one or more related homes to the first home using clustering in a multidimensional feature space. The system may determine a target price for the first home based on prices of the identified homes, as well as provide instructions to the home builder of actionable steps to improve home production and performance.

An example mobile computing device includes: a wireless communications interface configured to connect to a network deployed by a plurality of base stations; a controller for the wireless communications interface, the controller configured to: initiate a scan for foreign base stations; when the scan is complete, return to a home base station and initiate a home channel dwell time; receive a data packet from the home base station during the home channel dwell time; receive an indicator that transmission of buffered data packets from home base station is complete; and in response to the indicator, terminate the home channel dwell time.

Methods and systems are described for controlling access to a home based on user occupancy. According to at least one embodiment, an apparatus for controlling access to a home based on user occupancy includes a processor, a memory in electronic communication with the processor, and instructions stored in the memory which are executable by a processor to determine a location of a user of a home automation system relative to a barrier of a home being monitored by the home automation system. The instructions are executable to determine whether to permit a change in a locking mechanism of the barrier based in part on the determined location of the user, and maintain a current state of the home automation system.

The invention provides a base station switching method, electronic equipment and a computer readable storage medium, and belongs to the technical field of communication. In the method, a home base station gateway firstly obtains a neighbor cell information table, a historical switching information table and a load information table, then receives a first switching request sent by a core network control plane network element, and switches the core network control plane network element on the basis of part or all of the first switching request, the neighbor cell information table, the historical switching information table and the load information table. Screening out at least one second home base station from the first home base stations; and finally, the home base station gateway sends a second switching request to the at least one second home base station, so that the terminal equipment is connected with one target home base station in the at least one second home base station. In the application, the home base station gateway only sends the second switching request to the second home base station instead of blindly respectively sending the second switching request to all the first home base stations, thereby effectively reducing resource waste, improving resource utilization rate, and reducing communication cost.

1. Name of the product in this design: Unmanned Aerial Vehicle Countermeasure Equipment (Space-based D100). 2. Purpose of this design: This design is used to cut off the communication and navigation links of drones, forcing them to return to their home base or make an emergency landing, thereby achieving effective control over drones. 3. The key design feature of this product is its shape. 4. The image or photograph that best illustrates the design's key points: 3D view 1.

The utility model discloses a household electrical stimulator, which comprises an electrical stimulator body and a switch device, and a switch control rod capable of translating relative to the switch device is arranged on the side surface of the switch device; the charging groove is formed in the side wall of the electrical stimulator body, a charging port used for being electrically connected with the circuit board is formed in the charging groove, and the charging port is located on an extension line of the moving track of the switch control rod; a control rod clamping groove matched with the switch control rod is formed in the inner side of the sliding switch key; the charging groove is formed in the side wall of the electrical stimulator body, the first end of the sliding switch key is communicated with the charging groove and is partially overlapped with the charging groove, and when the electrical stimulator body is powered on, the first end of the sliding switch key is located in the charging groove and covers the charging port, so that a user is prevented from charging while using the electrical stimulator body; the first end of the sliding on-off key is separated from the charging groove for a user to charge.

Cleaning robots, comprehensive: a communication interface; at least one sensor; at least one camera (120); a drive unit; and a processor (140) that is configured: to input an image taken by at least one camera into a trained artificial intelligence model in order to obtain information about an object contained in the captured image: to obtain information that is captured by at least one sensor; To obtain recognition information about each of several work surfaces in a home based on information about the object, wherein the recognition information about each of the several work surfaces includes type information about each of the several work surfaces; to generate a map that displays the multiple work areas, using the information obtained about the object, the captured information, and the recognition information for each of the multiple work areas; based on a user voice instructing a cleaning operation to control the drive unit to move to at least one of the multiple work surfaces; and based on moving to the at least one work surface, a cleaning operation for the at least one work surface is to be carried out, where the recognition information for each of the multiple work surfaces includes a name for each of the multiple work surfaces.

1. Name of the designed product: vest (Muse shadow series outerwear home base vest 5318). 2. Use of the designed product: for women to wear. 3. Design points of the designed product: the combination of shape and pattern. 4. Pictures or photos that best show the design points: perspective view. 5. The design points of the top view of the product have been shown in other views, so the top view is omitted; the bottom view of the product is generally not easy to see during use, so the bottom view is omitted. 6. Other circumstances that need to be explained Other explanations: the mannequin is used to support the clothes and does not belong to the protection range of this design.

The invention relates to the field of smart home control, in particular to a smart home control method and system based on voice recognition. The method comprises the following steps: collecting a user voice signal based on an indoor distributed microphone array; performing interference correction on the user voice signal to obtain a voice sequence to be analyzed; performing deep semantic analysis on the to-be-analyzed voice sequence to obtain voice intention information; performing scene semantic prediction on the voice intention information, and outputting a user control demand set; performing security constraint arbitration and abnormal demand elimination on the user control demand set to generate a standardized control demand set; and based on the standardized control demand set, a control instruction is sequentially issued to the smart home, and smart home control operation is completed. According to the invention, efficient and accurate control of the smart home is realized, the user instruction is deeply understood, and the user experience and convenience are improved.

The present invention discloses an intelligent optimization method for multi-screen interaction in a smart home based on AI services, which relates to the technical field of smart homes; it includes: device identification and classification: identifying all screen devices in the home through wireless network sensing technology and classifying them according to device characteristics; user behavior analysis: collecting operation data of users on different screens and analyzing the user's behavior pattern using machine learning algorithms; content recommendation system: recommending content suitable for different screens using a deep learning model based on user behavior analysis and device characteristics; interaction optimization algorithm: an interaction optimization algorithm based on multi-screen interaction. The present invention realizes an intelligent optimization system for multi-screen interaction in a smart home by adopting artificial intelligence technologies, including support vector machines, hidden Markov models, convolutional neural networks, reinforcement learning, etc.; this system can automatically identify various screen devices in the home and classify and manage them according to device performance and usage environment.

The invention relates to the technical field of online light arrangement of smart home, and discloses an online light arrangement method and device of smart home and electronic equipment, and the method comprises the steps: obtaining a design drawing of a to-be-recognized object, and determining the object contour of each design object in the design drawing; adding light equipment in the object contour to obtain an equipment point location map; based on the device position and the device parameter of each light device in the device point location map, rendering the light effect in the object contour to obtain a light effect map; and generating an online light arrangement scheme of the smart home based on the light effect picture and the equipment point location picture. According to the invention, the implementation and overall reliability of smart home light arrangement are improved.

This invention relates to a multi-base station dynamic networking method, system, and device for large-scale venue voting applications. The method includes: monitoring the signal strength between each voting terminal and each base station, as well as the load data of each base station; when the load of any base station reaches a warning threshold, identifying terminals to be redirected; evaluating the marginal increase in communication time consumption of each neighboring base station for the terminal to be redirected, and generating a home selection criterion based on the access adaptation attributes of neighboring base stations; selecting a target home base station from among the neighboring base stations based on the home selection criterion; controlling the load warning base station to suspend the allocation of communication time slots, and coordinating with the target home base station to reserve communication time slots; and issuing a handover command to the terminal to be redirected, instructing the terminal to upload its cache and then migrate seamlessly to the target home base station. Therefore, this invention can adapt to the dynamic distribution of personnel in the venue without manual intervention, fully meeting the stringent requirements for network stability and real-time performance in large-scale conferences.