787 results about "Community setting" patented technology

The invention relates to the technical field of intelligent education, in particular to an AI-based nursing teaching scene construction and evaluation system. According to the system, a dynamic case script is generated through historical case data, and a virtual patient physiological model is constructed; creating three teaching scenes of community follow-up visit, emergency rescue and traditional Chinese medicine nursing fusion by using a mixed reality technology; a personalized learning portrait of the student is constructed through a pre-test, and accurate matching between the ability of the student and the teaching content is formed; a double-track system skill training module is built, and AI tutor guidance and teacher guidance are integrated; and an ability evaluation system based on operation data is established, and intelligent pushing of adaptive training content is realized. The problems that in traditional nursing teaching, scene authenticity is insufficient, personalized training is insufficient, and clinical thinking is difficult to cultivate are solved, and the clinical operation skill and decision judgment ability of students are improved.

A method and system for automated routing of pictures taken on mobile electronic devices to a digital picture frame including a camera, microphone, and speaker integrated with the frame, and a network connection module allowing the frame for direct contact and upload of photos from electronic devices or from photo collections of community members. Clustering photos by content is used to improve display and to respond to photo viewer desires. Trends or patterns can be detected from the photo collections and that information is used for various purposes beyond photo display. The frame includes a conversational intelligence that provides a verbal communication with a viewer, such as for determining an identity or preferences of the frame viewer, determining photos to display for the viewer, discussing displayed photos with the viewer, or telling stories and life histories to the viewer based upon photo content.

The invention relates to the technical field of community planning, and discloses a community life circle planning evaluation method and system, and the method comprises the steps: carrying out the real-time analysis of data based on a data collection end, extracting the core attribute of a community service facility, generating a unified semantic representation, and carrying out the distributed synchronization of the unified semantic representation to a central evaluation database through federal learning; based on standardized data and resident behavior portrait features, dynamically generating facility coverage conflict solving strategies, and performing classified execution by an edge node local preprocessing module; after the conflict is solved, selecting a target edge node in combination with a population age structure and dynamically configuring a cache evaluation index set in a collaborative architecture of the edge node and the central server; and obtaining an evaluation demand of a planner, analyzing a planning intention, generating a comprehensive evaluation feature in combination with the cache index, determining an evaluation level, outputting a planning optimization suggestion, and updating an evaluation index weight system and a planning strategy based on the feedback of the planner. The application can dynamically adapt to the change of the relationship between the resident demand and the facility supply and demand.

The application discloses a smart community management service system, and particularly relates to the field of service management, comprising a perception layer module, a communication layer module, a data processing layer module and an application layer module; the application realizes global intelligent management through the collaborative architecture of the perception layer module, the communication layer module, the data processing layer module and the application layer module; the perception layer is deployed with multi-source heterogeneous sensors, and data preprocessing is conducted in combination with edge computing; the communication layer adopts multi-protocol fusion transmission, supports 5G+NB-IoT dual-channel redundancy and end-to-end encryption; the data processing layer is based on a cloud-edge collaborative architecture, uses Kalman filtering denoising, D-S evidence theory fusion conflict information, LSTM-Attention prediction device failure, and constructs a digital twin simulation optimization energy consumption; the application layer provides a three-dimensional visual management and control platform, integrates security linkage, air conditioner group control strategy driven by reinforcement learning and convenient service scheduling, and supports cross-platform access and RBAC permission management.

The invention discloses a quantum bit mapping optimization method for hardware guidance and fidelity perception and a related device, and belongs to the field of quantum computing, and the method comprises the steps: defining each node in a hardware coupling graph of a target quantum processor as an initial community; evaluating all adjacent community pairs according to a reward function defined based on modularity and fidelity of candidate communities, selecting an optimal community pair for fusion, and taking the community with the largest current scale as an optimal candidate area; iteratively executing a community fusion step until a converged single community is obtained; and selecting an optimal candidate region with the physical quantum bit number greater than or equal to the logic quantum bit number of the quantum circuit to be mapped and the minimum scale, and outputting a mapping sub-graph. According to the method, through a recursive community fusion strategy, the operation range of the solver is restrained in a subspace with the scale greatly reduced and the quality better, the problem of combinatorial explosion caused by global search is fundamentally avoided, and the calculation overhead is greatly reduced.

The invention relates to the technical field of attribute graph collection and release, in particular to an attribute graph collection and release method, system and device based on local differential privacy and a medium. Receiving disturbed data from each client; based on all disturbed data, estimating community division of the original graph structure and triangular counting of each node; obtaining a target graph structure based on community division and triangular counting; and on the basis of the target graph structure and the disturbed data, node attributes are optimized, so that node attribute distribution and community division are kept consistent, and a final publishable target attribute graph is obtained. The method has the advantages that strict requirements of local differential privacy are met on the privacy protection level, and multi-dimensional features such as a community structure, triangular counting and node attribute homogeneity are reserved in the published attribute graph at the same time; and the practical value of the synthetic data in applications such as downstream graph analysis, community discovery and personalized service is greatly improved.

According to the privacy enhancement type (k, d)-truss community search method for the social network, a novel KTG tree structure is constructed by fusing k-truss and G-tree indexes. According to the index structure, hierarchical community decomposition of a social graph and social distance information are fused, a refined boundary vector coding scheme is designed to support efficient distance calculation, and a double-cloud-server non-collusion architecture integrating improved homomorphic encryption and matrix encryption technologies is constructed. Through a two-stage security query process of first structure filtering and then distance verification, on the premise of protecting full-process privacy of a graph structure, a query intention, a distance matrix and an intermediate calculation result, efficient and accurate search of a close community in a large-scale social network is realized. The method is suitable for various scenes such as social recommendation, risk control, public opinion analysis and anti-fraud, and the problems of privacy disclosure and calculation efficiency in social network analysis are effectively solved.

The invention relates to the technical field of community management, in particular to a dynamic monitoring analysis method and system for vehicles in an intelligent community, and the method comprises the steps: collecting multi-source data through a sensor, and generating structured sensing data through a lightweight OCR algorithm; calculating the real-time weight of each sensor by using a self-adaptive dynamic weight algorithm according to the structured sensing data in combination with environmental parameters and equipment states, calculating fusion confidence through a feature confidence fusion formula, rejecting unqualified data, and generating high-precision sensing data; constructing a community digital twinning scene, performing anomaly judgment through a dynamic threshold algorithm, positioning a fault through a three-level mechanism, generating a configuration updating instruction, and generating system state data; and inputting the high-precision sensing data, the system state data and the historical vehicle violation records into the game theory model to calculate the vehicle violation probability, and generating a differentiated management strategy according to the vehicle violation probability. According to the scheme, precise management of community vehicles is realized through multi-source fusion and hierarchical association.

The invention relates to the technical field of infectious disease monitoring and early warning, and discloses an intelligent influenza early warning system based on community multi-modal data fusion. The community-level multi-modal data fusion architecture is constructed, medical health data, environmental data, crowd activity data and network behavior data are integrated, spatial-temporal features are dynamically extracted and fused in combination with a deep learning model, and the problem of community monitoring blind areas caused by a single data source of an existing early warning system is solved; a long short-term memory network and convolutional neural network cascade architecture is utilized to capture a localized propagation rule, and the defect that a region-level prediction model cannot adapt to community heterogeneity is overcome; the risk score is generated in real time, the grading response instruction is triggered, a'monitoring-early warning-intervention 'closed loop is established, the early warning timeliness is remarkably improved, a basic-level response chain scission gap is filled, early prevention and control of flu outbreak are finally achieved, and public health resource consumption is reduced.

The invention belongs to the technical field of medical treatment, and discloses a wearable intelligent method and device for monitoring the mental health of community old people, and the method comprises the steps: collecting the physiological indexes of the community old people in real time through an intelligent chest card, and achieving the dynamic collection of multi-dimensional data; data are transmitted to the cloud platform through Bluetooth or Wi-Fi, the equipment supports a data caching mechanism, and key data are temporarily stored when connection is abnormal; a dynamic evaluation model is constructed based on AI learning, and a multi-factor decision tree model and a natural language processing NLP algorithm are combined; a group psychological health trend and an environment risk thermodynamic diagram are presented in real time through a chest card APP, main factors influencing psychological health of the old are analyzed, and community managers are assisted in making an intervention plan. By making and applying the community old people mental health monitoring and early warning model, a unified mental health assessment system is provided for old people in different states, the applicability, universality and compliance of mental assessment are improved, home rehabilitation is achieved, and the overall medical cost is reduced.

The invention belongs to the technical field of community intelligent inspection, and discloses an intelligent decision-making and interaction method and system for a community inspection robot, and the method comprises the steps: collecting community image, sound and gas concentration data through multiple sensors, extracting visual, audio and gas multi-mode features, and carrying out the multi-mode feature extraction; constructing a cross-media knowledge graph to associate an abnormal event entity and a multi-modal feature entity; then aggregating features of entity nodes and neighbor nodes thereof in the knowledge graph based on a graph convolutional network, generating a graph structure enhanced feature representation, and transforming and outputting a hidden danger probability score; and finally, if the score exceeds a preset threshold value, triggering grading early warning. The problems that traditional inspection data are isolated and complex scene semantic understanding is insufficient are solved, hidden danger recognition accuracy and early warning reliability are improved, the intelligent and efficient requirements of intelligent community inspection are effectively met, and the method is suitable for community safety management scenes.

The invention discloses an overlapping community detection method, system and device and a medium, and particularly relates to the technical field of community detection, and the technical key points are as follows: extracting node information data from a pre-constructed adjacent matrix of an overlapping community, and inputting the node information data into a point mutual information function to calculate and obtain point mutual information; obtaining a superpoint mutual information matrix by combining the point mutual information with the hypergraph structure; constructing a target function by using the super-point mutual information matrix and a pre-constructed three-factor illegal matrix decomposition optimization model based on graph regularization; decomposing the super-point mutual information matrix in the objective function to obtain an indication matrix, and solving the indication matrix by using an alternating iteration method to obtain an optimal solution of the indication matrix; and detecting the overlapping community based on the optimal solution of the indication matrix to obtain an overlapping community detection result.

The invention relates to the technical field of community management, in particular to an intelligent community service management method and system based on cloud computing, and the method comprises the following steps: S1, collecting community multi-dimensional data in real time through a heterogeneous data collection terminal; s2, constructing an edge-cloud cooperative processing framework; s3, implementing intelligent video analysis; s4, realizing data-driven resource scheduling; and S5, establishing an intelligent storage system. According to the invention, omnibearing perception of a community environment is realized through a multispectral camera and a distributed sensor network, data processing efficiency is improved by adopting an optimized lightweight algorithm and an edge-cloud collaborative architecture, and a visual decision platform is constructed in combination with adaptive resource scheduling and an intelligent analysis technology. A closed-loop management system integrating real-time monitoring, intelligent early warning and accurate operation and maintenance is formed, the community management efficiency is improved, the operation cost is reduced, stable operation of the system is guaranteed through multiple safety mechanisms, and an intelligent solution is provided for modern community services.

The invention relates to a community low altitude-oriented aircraft path planning and traffic capacity evaluation system. The system comprises an airspace facility modeling module, a facility relation judgment module, a hierarchical airspace segmentation module, a noise-speed-safe distance constraint calculation module, a dynamic obstacle marking module, a multi-target path planning module and a bottleneck identification and traffic capacity evaluation module. The method comprises the following steps: modeling airspace facilities, and judging a facility relationship based on spatial geometric attributes and function use requirements of the facilities; performing hierarchical grid division on the low altitude of the community, calculating a safety distance along the movement direction and a safety distance perpendicular to the flight direction, and performing obstacle marking on grids around the building based on the safety distances and the flight direction; and performing path search based on an improved A * algorithm, identifying a bottleneck region, extracting parameters, and calculating the maximum allowable speed of the bottleneck region and the total traffic capacity of the bottleneck region. The system can relieve environmental troubles such as safety compliance dispute and noise pollution caused by operation of the low-altitude aircraft.

The invention relates to the technical field of community management, and discloses an intelligent community management system based on cloud service. The system comprises a community basic data management module, a building structure information module, a public equipment monitoring module, a cloud data interaction module and a user authority management module. The community basic data management module maintains community static information and dynamic records; the building structure information module stores building physical attribute data and resident association information; the public equipment monitoring module collects real-time operation state data and historical performance indexes of public equipment; the cloud data interaction module realizes local and cloud data transmission synchronization; and the user permission management module allocates operation permissions according to preset role types. The system realizes data integration, equipment monitoring, authority specification and cloud interaction in a community management process through multi-module cooperation, and is suitable for efficient operation of a community management background.

The invention relates to a post personnel recommendation interpretation method and device based on gradient features and a community structure. The method comprises the steps of obtaining a pre-trained and converged graph neural network and original embedded features, carrying out subsequent operation according to a knowledge graph in which entities such as personnel, skills, posts and services are stored, and recommending a network for on-duty personnel by using the graph neural network, and combining the original embedded features with gradient vectors obtained by the graph neural network through a back propagation algorithm to form gradient features. And performing community division on the knowledge graph nodes, and generating node community tags by maximizing modularity. Finally, the gradient features, the node community labels and the graph neural network model are input into an interpretation framework together, the graph masks and the feature masks are optimized to maximize information quantitative indexes, and post personnel recommendation results containing the key sub-graphs and the feature masks are generated. By adopting the method, the on-duty personnel recommendation interpretability in different scenes can be continuously improved.

The invention relates to a UTE-LSTM-SA-based community user charging load prediction method, an electronic device and a medium, and the method comprises the steps: obtaining multi-source data, the multi-source data comprises community user behavior data, environment data and power data, the community user behavior data comprises commuting distance, travel time and user type labels, and the environment data comprises the environment data and the power data; the environment data comprises temperature data and weather data, and the power data comprises historical charging load and time-of-use electricity price; constructing multi-dimensional features based on the multi-source data, wherein the multi-dimensional features comprise commuting association features, time scene features, external influence features and abnormal value correction features; constructing a community user charging load prediction model based on a UTE-LSTM-SA prediction framework and the multi-dimensional features; and solving the community user charging load prediction model based on constraint conditions to obtain a community user charging load prediction result. According to the method, the commuting distance, the environment temperature and the time-of-use electricity price characteristics are fused, the charging load in the next 24 hours is predicted through the customized deep learning model, and the prediction precision is improved.

The invention relates to the technical field of data processing, in particular to an intelligent community data processing system based on situation awareness, which comprises an information acquisition module used for acquiring external accident information and generating an external accident report; the video module is used for acquiring video data in the community and generating a scene report; the analysis module is used for calling the external accident report and the scene report for comparison and generating a risk report; the preset scheme module is used for creating and storing a processing scheme; the automatic auditing module is used for matching the risk report with a processing scheme in the preset scheme module, generating a risk processing scheme if matching succeeds, and directly sending the risk report to the manual auditing module if matching fails; and the manual auditing module is used for auditing the risk processing scheme, analyzing the risk report, creating a corresponding processing scheme in the preset scheme module, and generating the risk processing scheme. The system can recognize some potential risks in the community in advance, and reduces the accident rate.

The invention relates to a community household rehabilitation resource matching and scheduling method and device based on multiple agents. The method comprises the following steps: dynamically acquiring rehabilitation service demand data and rehabilitation resource data in a community through a data acquisition and preprocessing agent; evaluating the rehabilitation service demand data and the rehabilitation resource data of the patient through a demand evaluation agent, and generating a rehabilitation demand priority of the patient and a professional field preference list of a rehabilitator; generating a rehabilitation resource portrait of the rehabilitation demand priority and the rehabilitator professional field preference list through a resource portrait agent; and performing reinforcement learning on the rehabilitation resource portrait through a matching scheduling agent, and decomposing a matching problem into two sub-tasks of coarse-grained matching and fine scheduling. According to the invention, a solution with adaptive capability is provided for community household rehabilitation resource matching and scheduling, so that the overall level of community household rehabilitation service is improved.

The invention discloses a community division-based power distribution network two-stage voltage out-of-limit control method and related equipment. Firstly, community division is carried out on nodes containing a photovoltaic power distribution network based on an improved particle competitive learning algorithm to obtain a plurality of communities so as to enhance the rationality and stability of community division. And secondly, establishing a voltage out-of-limit control model based on a linearized power flow equation in the community, and when node voltage is out of limit, realizing rapid autonomous control and eliminating local voltage out-of-limit by adjusting SVG reactive power and photovoltaic active and reactive power in the community. And thirdly, after autonomous control in the community is completed, power and voltage information of boundary nodes of the community is collected, a distributed optimization method is adopted to carry out coordinated regulation on SVG and photovoltaic across the community, and a power flow equation is utilized to correct the voltage of the boundary nodes, so that global optimization of the voltage of the whole network is realized.

An electronic gaming device for providing a community-based electronic game including a community matrix for providing community gameplay of the community-based electronic game. The community-based electronic game includes a base game including a first set of reels and the community matrix displayed within a display interface of the community-based electronic game. One or more social trigger symbols associated with play of the base game by a plurality of players are randomly determined and presented on one or more reel columns of the first set of reels. For each of the one or more social trigger symbols, one or more community social trigger symbols are presented on one or more columns of the community matrix, each of the one or more community social trigger symbols being attributed to respective one or more players of the plurality of players of the base game associated with at least one social trigger symbol.

The invention relates to the technical field of abnormal behavior recognition, in particular to an abnormal behavior multi-mode recognition method and system for a smart community. Comprising the following steps: multi-modal data acquisition and preprocessing: synchronously acquiring spatio-temporal dynamic data of a target area through a millimeter wave radar, an infrared sensor, a microphone array and a panoramic camera deployed in a community, wherein the spatio-temporal dynamic data comprises a human body motion track, temperature field distribution, environment voiceprint characteristics and a visual image sequence; wherein the millimeter-wave radar adopts a frequency modulation continuous wave system to sample micro-Doppler characteristics of a human body, the infrared sensor realizes temperature field reconstruction through the pyroelectric array, the microphone array collects voiceprint signals through the array structure, and the panoramic camera collects a high-frame-rate image sequence; and environment interference coupling correction: aiming at acoustic reflection characteristics of different materials in the community, and combining an illumination abrupt change rate, an object reflectivity and an air humidity parameter, the method can improve the recognition accuracy and robustness in a complex community environment.

The invention discloses a federal learning model poisoning attack defense method and system, and the method comprises the following steps: updating a model uploaded by a client, and carrying out the clustering voting through K-means; constructing a consensus graph according to voting records, and detecting communities through a Louvain algorithm to divide model updating; a cosine similarity filtering model is used for updating in each community; aggregating each community to generate representative updates; community updating is evaluated based on key parameters in the initial stage of training, historical information prediction is used after stabilization, and a new global model is aggregated by taking the highest evaluation as the benign updating in the current round. Compared with a traditional method, the method has the advantages that model poisoning attacks can be effectively resisted under the complex scenes that data are highly non-independent identically distributed and high-proportion malicious clients exist, and the safety and robustness of the federal learning model are remarkably improved.

The utility model discloses an intelligent community double-door half-height shielding door which comprises a protection shell, a sliding door assembly is arranged in the protection shell and comprises a nut block, a slot is in sliding connection with the interior of the side wall of the top of the protection shell, the top of the protection shell is fixedly connected with an outer protection box, and the outer protection box is fixedly connected with an inner protection box. The top of the protective shell is further fixedly connected with a sliding rail, the outer wall of the sliding rail is slidably connected with a blocking sliding door, the two sides of the blocking sliding door are fixedly connected with L-shaped connecting rods, the L-shaped connecting rods are inserted into the inserting grooves, the sliding door assembly further comprises a top cover, and the top cover is fixed to the top of the outer protective box through bolts. The utility model relates to the technical field of shielding doors. According to the double-door half-height shielding door for the intelligent community, when the blocking sliding door needs to be disassembled, the top cover is separated from the top of the outer protection box, then the blocking sliding door can be directly taken up to vertically move upwards, and the disassembly can be quickly completed by enabling the L-shaped connecting rod to be separated from the inserting groove.

The invention relates to the technical field of intelligent community data governance and main identity normalization management, and discloses a future community member architecture intelligent building method and system, and the method comprises the steps: carrying out the field semantic standardization of structured resident data; fusing the unstructured data; generating a ciphertext identifier; executing cross-system identity matching in combination with a field similarity function; and generating a unique main identity file. Compared with the prior art, the technical problems that data of multiple departments are independently managed, field structures are heterogeneous, a unified identity primary key is lacked, and particularly, high-precision identity fusion and normalization management cannot be realized under the complex data conditions of name duplication, different address expressions, field missing or untrusted sources and the like of residents are solved. According to the method, cross-system multi-source data fusion and identity uniqueness determination are realized through semantic hash slot construction, image-text joint recognition, multi-source fuzzy matching and a credible main file generation mechanism, and the uniqueness and credibility of future community resident identity data are improved.

We provide the system. [Solution] A method that uses generative models to predict future natural disasters by analyzing environmental data collected from diverse sources, A means for providing an appropriate evacuation route to a user terminal based on the predictions of the generation model, A means of sharing community information among users in real time and promoting its use in disaster prevention, A method for using unmanned aerial vehicles to acquire information on the situation in disaster-stricken areas and then re-proposing the optimal evacuation route based on that information, A system that includes this.

The invention relates to the technical field of public space design, in particular to a community old and young shared public space design method and system. Exercise facility safety analysis is performed on the basis of exercise habit conditions of children and old people in the community and corresponding exercise facility position specification conditions, exercise facility selection analysis is performed on the basis of an exercise facility matching analysis result and an exercise facility safety analysis result, and the matching conditions of various exercise facilities and the old and the young in the community are accurately analyzed. And the rationality and safety of exercise facility installation are improved.

The invention relates to a community power dispatching optimization method, system and device and a medium, and the method comprises the steps: monitoring and collecting the power utilization data in a designated region in real time, and obtaining the external environment data of the designated region; storing the collected data according to a time sequence form; capturing a long dependency relationship in the stored time sequence data by adopting a long-short term memory (LSTM) network, and generating a prediction model by learning historical power consumption data and combining external environment data to predict a power consumption demand at a specified time in the future; acquiring real-time electricity price, actual electricity demand of a user and power grid load information, and calculating and generating an optimal scheduling strategy by using a multi-target optimization algorithm on the basis of the predicted electricity demand; and monitoring the operation state of user power equipment in real time, and adjusting load distribution and equipment start and stop based on the generated optimal scheduling strategy. According to the invention, the intelligence and flexibility of power dispatching can be improved.

The invention discloses an urban waterlogging resident emergency evacuation path guiding method for a smart community, and relates to the technical field of smart cities and emergency management. The method comprises the following steps: firstly, constructing a community digital twinborn base fusing geographic information, building information, Internet of Things sensing data and a hydrodynamic model; dynamic inversion and prediction of the waterlogging situation are realized by assimilating a multi-source observation data driving model; calculating the space-time dynamic risk of the evacuation road network based on the prediction result, and generating a risk map; calculating a space-time evacuation scheme including optimal departure time and a specific path sequence for residents or families by combining resident personalized constraints and adopting a double-layer optimization model combining macroscopic flow distribution and microscopic path planning; finally, instructions are issued through multiple channels such as an intelligent terminal and broadcast, and dynamic adjustment is performed based on real-time monitoring, so that accurate perception, prospective prediction, personalized planning and collaborative guidance of waterlogging evacuation are realized, and the overall efficiency of community emergency evacuation is effectively improved.

The invention provides a family-centered child development platform designed to support and enhance a child's academic, emotional, social, and cultural growth. By utilizing an AI-driven system for personalized learning, immersive VR / AR technologies for engaging educational experiences, and a community-building module for peer interaction, it offers an integrated solution for holistic child development. The system incorporates emotion detection, biometric feedback, and emotion-driven content adaptation, which dynamically adjusts the child's learning experience based on real-time emotional and physiological data. Additionally, the platform features culturally relevant content, promotes intergenerational collaboration, and includes a gamified learning environment to foster motivation and engagement. A secure interaction system ensures safe online communication, while the adaptive challenge system maintains an optimal level of difficulty tailored to the child's evolving needs. By combining these technologies, the platform provides a personalized, interactive, and supportive learning journey for children, supported by parents and educators.