1388 results about "Community setting" patented technology

The invention discloses a community intelligent monitoring and emergency linkage method and system fusing BIM spatial semantics, and the method comprises the steps: constructing a BIM scene map, and obtaining the attributes and mutual relationships of components and spatial regions in a BIM model; mapping a dynamic target detected in video monitoring into the BIM model, and obtaining spatial semantic information of the dynamic target; based on BIM spatial semantic information of a dynamic target, a target-environment interaction graph is constructed, a graph neural network model is used for training and reasoning, and specific complex events related to spatial contexts are recognized; taking the BIM model as a space-time reference, fusing multi-source heterogeneous data, and reconstructing by adopting a graph-based event association algorithm to form a complete event chain containing an atomic event sequence and an association relationship; and when an emergency event or an event chain is detected to indicate an emergency state, combining BIM preset information and real-time sensor data, dynamically generating an optimal emergency plan, and performing visual commanding and dispatching through a BIM three-dimensional scene and augmented reality.

The invention, which relates to the technical field of community safety supervision, discloses an artificial intelligence-based community safety environment supervision system comprising a data acquisition module, a data processing and analysis module, an intelligent decision module, an early warning response module and a system management module. The data acquisition module is used as a sensing layer of the system; the data processing and analysis module specifically comprises a feature extraction unit and a behavior recognition unit; the intelligent decision module is used for receiving the risk assessment result output by the data processing and analysis module; and the early warning response module generates the scheme according to the intelligent decision module. According to the community safety environment supervision system based on artificial intelligence, intelligent supervision of a community safety environment is realized through a complete closed loop of data acquisition, data processing, intelligent decision making, early warning response and system management; all the modules are in close cooperation, full-process automation from data collection to emergency response is ensured, and the efficiency and accuracy of community safety management are greatly improved.

The invention discloses a smart community security management method and system based on the Internet of Things. The method comprises the following steps: acquiring environmental data in real time through Internet of Things sensing equipment deployed in a community; generating a dynamic risk thermodynamic diagram through a risk assessment model based on historical security event data and environment data collected in real time; generating an optimal patrol path by using a reinforcement learning algorithm according to the dynamic risk thermodynamic diagram and a preset patrol constraint condition; issuing the optimal patrol path to a patrol terminal for execution, and dynamically adjusting the path in the execution process according to the environment data updated in real time; when a high-risk event is detected, an emergency response mechanism is triggered, and the unmanned aerial vehicle, the patrol robot and the mobile terminal are automatically dispatched for cooperative disposal. Through the method, the intelligent degree of community safety monitoring can be enhanced.

A disclosed data platform may be configured to access a custom policy developed by a particular client entity that uses the data platform. The custom policy may invoke a query that targets a target dataset ingested from a cloud environment and stored in a data store. The data platform may determine that the custom policy is likely to be of value to one or more other client entities, besides the particular client entity, that also use the data platform. In response to the determining that the custom policy is likely to be of value to the one or more other client entities, the data platform may generate a community policy based on the custom policy. The community policy may be available for use by the one or more other client entities. Corresponding methods, systems, and products are also disclosed.

The invention relates to the technical field of environment intelligent management, and discloses a multi-community-oriented AI intelligent household garbage control processing system which comprises a multi-mode sensing module, a data processing and edge calculation module, a garbage quantity prediction and scheduling optimization module, an intelligent decision and multi-source data fusion module and a self-adaptive adjustment and feedback mechanism module. The multi-community-oriented AI intelligent household garbage control processing method comprises the following steps that S1, a multi-modal sensing module collects garbage data; s2, an edge calculation module performs preprocessing, classification and encrypted transmission; s3, optimizing transportation and scheduling; s4, generating an optimal processing decision; and S5, adaptively adjusting the strategy. Through the technical scheme of combining multi-modal perception and edge calculation, accurate garbage data acquisition and efficient processing in a multi-community environment are realized, the technical effects of reducing data transmission burden and improving garbage classification data quality are achieved, and garbage classification is more accurate and reliable.

The invention relates to the technical field of smart community data management, in particular to a smart community metadata interaction method and system based on an edge computing framework, and the method comprises the steps: carrying out the dynamic storage of multi-dimensional data through a hierarchical rolling cache; generating a uniform resource vector through sequential progressive mapping; community semantic tags are added for the uniform resource vectors through extensible tag slots, connection is established according to association rules, and a resource semantic graph oriented to community services is constructed; receiving a resident task request, constructing a multi-factor weighted scoring engine based on the resource semantic graph, and generating a task data packet with a priority label; a two-channel hybrid scheduling network is constructed, a first channel outputs resource availability and node association degree, and a second channel outputs time sequence characteristics and load prediction parameters; and fusing dual-channel output to obtain task-node correlation and generate an optimal matching strategy. According to the method, task collaboration and resource adaptive management are realized through semantic resource modeling and hybrid scheduling.

The invention relates to the technical field of community video monitoring, and discloses a community personnel abnormal behavior video monitoring method based on human factor engineering, and the method comprises the steps: dividing community monitoring video data based on a preset activity region, and obtaining the monitoring data of each sub-region, including a personnel track, environment interaction and the like; determining the abnormal level of each sub-region according to the movement frequency of the personnel trajectory data and the interaction strength of the environment interaction data; key monitoring nodes are calculated in combination with abnormal levels and the like, and the scanning sequence and the scanning duration are adjusted and determined according to a dynamic path; then generating observation anchor points and redundant anchor points at the boundaries of the sub-regions; and finally, associating and integrating to generate a monitoring path. According to the method, through multi-dimensional data processing and dynamic optimization, the accuracy, flexibility and environmental adaptability of community abnormal behavior monitoring are improved, and the method is suitable for community safety management.

The invention belongs to the technical field of information technology and intelligent health service, and discloses a community old-age care service resource optimal configuration method based on edge computing, which comprises the following steps: collecting physiological data, environmental data and activity data of old people to form original heterogeneous data, uploading the original heterogeneous data to a data warehouse through an urban and rural community network adaptation mechanism, generating a space-time tagging multi-modal data set; constructing a dynamic digital twinborn model, generating a space thermodynamic diagram, identifying different level priority requirements, and generating a time period allocation scheme through a conflict priority scoring mechanism; an MILP model is constructed to dynamically optimize edge node computing power and functional area space resources, and a resource optimization report and a block chain transaction list are generated; desensitizing the original data of the old people, creating a digital identity card, generating an encrypted service log, and synchronously recording migration behaviors of the old people; and triggering network strategy switching and priority threshold self-adaption, and carrying out resource scheduling and strategy closed-loop optimization.

A system for assessing the ecological sensitivity and development potential of areas within ecologically sensitive mountain towns, consisting of: a data acquisition module configured to extract various data types, including multi-source geospatial data, environmental data, built environment data, socio-economic data and community participation data, with the extracted data being validated and stored in a database; a central processing unit comprising one or more processors connected to a memory, the processor communicatively connected to the database in which the extracted data is stored, the memory storing instructions that, when executed, configure the processor to implement the following: a data input module configured to receive data corresponding to multiple indicators from different assessment dimensions, including ecology and environment, built environment, economy, heritage and culture, mobility, location, community participation, visual aspects and safety from hazards; an indicator evaluation module configured to evaluate each indicator according to predefined sensitivity categories and assign corresponding sensitivity index values in the range of 0.1 to 1; a dimension weighting module configured to apply dimension-specific weights to calculate weighted scores for each indicator; a development potential calculation module that aggregates the weighted assessments to determine an overall sensitivity assessment and assigns this overall sensitivity assessment to a development potential rating scale; and a visualization module configured to generate visual representations and reports of the assessment results; and an output module having a user interface operatively connected to the visualization module of the central processing unit, the output module configuring the user interface to display the visualized results and the final index value obtained from the central processing unit.

The invention provides a method and a system for issuing tasks in a collaborative community and computing equipment, users of the collaborative community have user label information, and the method comprises the following steps: determining a first collaborative template for completing a first task; determining task setting information according to the first cooperation template; according to the task setting information, task planning information of the first task is generated, the first task corresponds to the first cooperation template, and the first task comprises at least one subtask; issuing the first task according to the task planning information, including: determining a task scheduling scheme for the first task according to the task planning information and the user tag information, the task scheduling scheme being used for setting a user executing the subtask; according to the task scheduling scheme, the corresponding subtasks are sent to corresponding users set by the task scheduling scheme in a pushing mode and / or a dispatching mode. By means of the method, a more friendly interaction mode can be provided.

The invention belongs to the technical field of urban low-carbon planning, and relates to a low-carbon community evaluation index library dynamic construction method and system. The method comprises the steps of knowledge graph mode layer construction, knowledge extraction, semantic relation enhancement and fusion and graph database storage. Defining the types of the entities and the semantic relationship between the entities to obtain a mode layer with a hierarchical topological structure; knowledge extraction: mapping the entity relationship in the mode layer into a knowledge extraction template; after an extraction result is subjected to subgraph structured organization, vector space mapping is carried out, semantic association strength among indexes is calculated, and entity alignment is carried out by adopting a knowledge fusion mechanism driven by a large language model; and importing the knowledge graph subjected to semantic relationship enhancement into a graph database through a query language. According to the method, efficient construction and expansion of the cross-domain index library can be realized; the adaptability of the index system is enhanced; and in combination with a knowledge fusion feedback mechanism, the mode layer is dynamically adjusted, so that the data processing efficiency and accuracy are improved.

The invention discloses a large language model question and answer method based on a retrieval enhancement generation scheme. The method comprises the following steps: segmenting a source document into a plurality of text blocks; extracting element instances from the text blocks; converting the element instance into a readable element abstract; constructing the element abstract into a graph community based on a graph theory scheme; generating a community-level abstract for the graph community; generating community answers according to the digests of the community levels and reducing the community answers to obtain global answers, and completing large language model questions and answers based on the retrieval enhancement generation scheme. The invention further discloses a system for realizing the retrieval enhancement generation scheme-based large language model question and answer method. According to the large language model question and answer method and system based on the retrieval enhancement generation scheme, entity knowledge graph and community abstract generation technologies are combined, question and answer of the large language model are achieved based on the retrieval enhancement generation scheme, reliability is higher, and accuracy is better.

The invention relates to the technical field of urban geography, in particular to a crowd movement flow-based multi-scale community structure importance identification method, which comprises the following steps of: constructing a crowd movement space-time network according to a preset geographic space unit and a time interval on the basis of crowd movement starting place and destination data; identifying a dynamic community structure based on a crowd mobile space-time network; performing multi-scale community structure object role and importance identification; and performing pattern classification by using the time sequence importance of the multi-scale community structure object. According to the method, the problems of inaccurate dynamic community structure recognition and lack of multi-scale object contribution decoupling mechanisms are solved.

The invention discloses a big data energy management method for intelligent monitoring of a community, and relates to the technical field of energy management, and the method is characterized in that through the hierarchical processing of community energy consumption data, the comprehensive analysis of a time dimension and a periodic rule is combined, and the energy use characteristics can be deeply mined. According to the processing mode, data of residential areas, public areas and commercial areas are layered, and detailed statistics is carried out according to categories of electric power, water resources, natural gas and the like, so that extraction of energy consumption characteristics is more targeted and systematic. Through time interval segmentation and clustering analysis, the behavior pattern of energy consumption is identified, and abnormal fluctuation characteristics are found in combination with entropy calculation, so that an abnormal source lower than a threshold value can be accurately positioned, and the efficiency and accuracy of troubleshooting are remarkably improved. Meanwhile, based on the dynamic prediction of the future energy consumption trend, in combination with the correlation analysis of the fluctuation region and the risk equipment, the potential problems in the energy consumption can be effectively pre-judged.

The invention relates to the field of community old-age care, and discloses a community old-age care-oriented medical-care-and-care-combined data intercommunication and service coordination system, which comprises a sensing module used for acquiring physiological data of old people, old-age care service data, environment data and service demand information to form multi-modal information; the network module is used for carrying out multi-modal information transmission, protocol conversion and edge calculation preprocessing to obtain processed data; and the data module is used for constructing a standardized data lake according to the processed data by adopting a unified data standard and a main data management technology, and carrying out fusion storage, treatment and safety protection to obtain multi-source information. Multi-modal information is collected to provide a data basis for cross-mechanism cooperation, data transmission and preprocessing are performed, and a standardized data lake is constructed through a unified data standard and main data management, so that medical institutions, pension institutions and community grids can share global data such as health states, service records and the like of old people in real time.

The invention relates to the field of data management, in particular to a community data management system for an intelligent old-age care community, and the system comprises a video monitoring unit which comprises a plurality of community monitoring devices and is used for collecting monitoring videos of all monitoring areas; the video analysis unit is used for periodically determining the video frame category of each basic video frame according to the personnel change reference value and the personnel influence reference value of the basic video frame corresponding to the community monitoring equipment; the video optimization unit is used for determining the state of the monitoring equipment according to the first-class video frame proportion and the first-class video frame density corresponding to the community monitoring equipment, and determining a corresponding video frame optimization mode as compensation optimization or activity feature optimization according to the state of the monitoring equipment; the key frame optimization unit is used for determining a processing mode to supplement or generate image description for the associated frame according to the effective state; and the monitoring data processing efficiency is improved.

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.

The invention discloses a community old-age service management system and method based on risk analysis, and belongs to the technical field of old-age service management. The method comprises the following steps: positioning risk positions in a community by using a YOLO algorithm to form a community risk position set; a community three-dimensional map is constructed, the community risk position set forms a risk area in the community three-dimensional map, and risk information is marked; exploratory data analysis is carried out, a statistical model is constructed, and a risk area expansion factor is obtained; based on the risk area expansion factor and the current weather data, adjusting the risk area of the community three-dimensional map and corresponding risk information; obtaining health data of the user, setting a scoring standard, and calculating a health score; evaluating whether the user is suitable for going downstairs to exercise or not based on the total health score by combining the individual condition of the user to obtain a health evaluation result; and when the health assessment result of the user is that the user is suitable for exercise or careful exercise, adjusting the exercise route planned by the user, and carrying out risk information prompt.

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.

A method and system for attribute community search based on a relation tree are provided. In the method, a data relation of a target domain is obtained, and an attribute information network of the target domain is constructed in the form of a graph. The attribute information network is loaded over a unified access interface, and data processing, subgraph construction, and algorithm operation and maintenance search are performed on the attribute information network. A community structure parameter k value and a search node q are received through an interface for attribute community search provided for a user, and a community that contains the search node q and satisfies structural cohesion and optimal attribute cohesion is returned. Rendering and interaction are performed on a user interface, which renders the community search result returned into a dynamic community network diagram and presents the dynamic community network diagram to the user.

The invention discloses an online social network harmful node identification and community division method and system. The method comprises the following steps: acquiring a social platform user speaking and interactive information data set; on the basis of the data set, a social network directed graph structure is constructed with users as nodes and interaction relations as edges; based on the social network directed graph structure, introducing evaluation indexes of edges for calculation, and determining weights of the edges; based on the directed graph structure of the social network, introducing degree centrality, betweenness centrality and a Kshell value to carry out total graph node calculation, and determining key nodes in social network propagation; and based on the weight of the edge and the key node, using a Louvain algorithm to realize community division of the optimal modularity. According to the method, the potential manipulation behaviors are identified by analyzing the graph structure of the dynamic social network, so that the identification capability of the manipulation behaviors of the social network can be improved.

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 an urban community public space residence vitality measurement method based on spatiotemporal behaviors, and the method is characterized in that the method comprises the following steps: S1, determining a sample; s2, defining a space range; s3, acquiring resident resident activity data; s4, determining community public space information; s5, calculating a residence vitality index; S6, constructing a residence vitality measurement model; and S7, introducing the data and calculating the residence vitality of the public space of each community. According to the method, data acquisition, statistics and analysis are carried out based on actual daily travel behaviors of community residents, and the resident activity distribution condition of the community public space obtained through representation can more truly describe the use condition of the residents on the community public space, so that the actual demands of the residents are mined, and the resident experience is improved. Therefore, the rationality and effectiveness of urban community public space planning are evaluated more accurately, and targeted technical guidance and theoretical support are provided for updating and optimization of the mountain community public space.

The invention discloses a community layout planning method and electronic equipment, and the method comprises the steps: sequentially carrying out the iteration updating of a community layout scheme, inputting a community layout design model, obtaining a first evaluation result corresponding to a first evaluation index, and carrying out the iteration of a target number of iterations; taking a community layout scheme corresponding to the first evaluation result meeting the first target condition as a first target community layout scheme, and determining a plurality of community spatial form simulation results corresponding to the first target community layout scheme; obtaining a second evaluation result corresponding to each second evaluation index according to the plurality of community spatial form simulation results and the plurality of second evaluation indexes; and determining a second target community layout scheme according to the plurality of obtained second evaluation results and the corresponding community spatial form simulation results. Therefore, a community layout scheme with more reasonable functional area layout can be obtained, so that the traffic efficiency is effectively improved, the carbon emission is reduced, and the life convenience of users is improved.

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 provides a community structure detection method and system for spatial concurrent extreme climate events, and the method comprises the steps: collecting lattice point temperature and rainfall data of a research region, extracting a binary time sequence of heat waves and extreme rainfall events, and carrying out the synchronous judgment calculation and significance test of the events; according to the interlayer adjacent matrix, a double-layer coupling heat wave-extreme precipitation network is constructed; based on the double-layer coupling network, a community detection method combining a Leiden algorithm and consensus clustering is adopted, and a stable community classification result is obtained; and carrying out lead-lag correlation analysis on all community pairs, identifying key community pairs with strong correlation and lag time thereof, and further discussing time-space propagation characteristics of climate events. According to the method, the advantages of double-layer coupling climate network analysis are fully utilized, the Leiden algorithm and the consensus clustering method are combined, the accuracy and stability of community detection are improved, and the spatial concurrency characteristics and the space-time propagation law of global extreme climate events can be effectively revealed.

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.

The invention discloses a community work order intelligent management method and device, and relates to the technical field of community service management.The community work order intelligent management method comprises the steps that user work order data containing texts, voices and images are received through a multi-mode interface, and the user work order data are cached to a preprocessing queue; based on a semantic segmentation model, performing multi-dimensional analysis on the user work order data in the preprocessing queue, generating a structured work order comprising an equipment identifier, a fault feature and a geographic position, and associating a problem type label for the structured work order; according to the equipment identifier, the fault feature, the geographic position, the problem type label and an order division decision model, obtaining an assignment instruction of the structured order; and allocating the structured chemical worksheet to a corresponding processing terminal according to the allocation instruction, and updating the processing state of the structured chemical worksheet. According to the invention, the efficiency and response speed of community work order management are 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.