368 results about "Smart community" patented technology

The invention relates to the technical field of smart communities, and discloses a smart community resident health management method based on machine learning, and the method comprises the steps: continuously collecting the health feedback data of residents, such as the physical condition change after outdoor activities, carrying out the correlation analysis of the health feedback data with the previous health data and environment data, dynamically updating and optimizing a correlation model, and obtaining the health feedback data of the residents; the prediction precision of the model and the effectiveness of suggestions are improved, the relationship between the use condition of the community public space and the resident health indexes is analyzed, key public facilities and areas influencing resident health are identified, data support and decision basis are provided for community planning and facility reconstruction, and the method is suitable for popularization and application. Community resident health and environment condition analysis reports are generated regularly, and resident health index change trends are visually displayed for reference of community managers and residents. According to the invention, intelligent analysis and application of environment and health data are realized, and technical support is provided for building a healthy community.

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.

The invention relates to the technical field of smart communities, and discloses a smart community target identification tracking method based on big data, which comprises the following steps: constructing an omnibearing monitoring network in a community, collecting real-time video and sensor data in the community, obtaining feature data of a target through an edge computing technology, and carrying out target identification tracking on the feature data; transmitting the target feature data to a cloud server through a network, identifying and classifying the target feature data, judging the type and identity of the target, analyzing the current behavior of the target according to a preset target historical behavior pattern library, and determining whether the behavior is abnormal or not; and if the behavior of the target is not matched with the normal mode in the historical behavior mode library, judging that the behavior is an abnormal behavior, and triggering an early warning mechanism. According to the invention, intelligent identification, dynamic tracking and timely early warning of the abnormal behavior of the smart community are realized, and the intelligent level and response efficiency of community safety management are improved.

A new multi-edge smart community system consisting of communication, computing, and energy harvesting models, where the task execution delay and energy consumption are formalized as the optimization objectives under multiple constraints. For single-edge scenarios, we propose an improved twin-delayed DRL-based algorithm. For multi-edge scenarios, we develop a novel personalized FL-based training framework for DRL. Using the real-world settings and testbed, extensive experiments are conducted to validate the effectiveness of the proposed PFR-OA. The results show that the PFR-OA achieves better trade-offs between delay and energy consumption and exhibits higher task execution success rates than benchmark methods under different scenarios. Notably, the PFR-OA reaches a faster convergence speed compared to advanced DRL-based and FRL-based methods. Moreover, we further verify the practicality and superiority of the PFR-OA via real-world testbed experiments.

The invention relates to the technical field of smart communities, and discloses a building low-carbon operation management method based on data analysis, which comprises the following steps: acquiring building data, preprocessing the data to obtain a multi-dimensional data set, performing feature extraction by adopting a principal component analysis method aiming at the multi-dimensional data set, and calculating a feature value and a feature vector of a covariance matrix to obtain a building low-carbon operation management result. Selecting the first k principal components with relatively large feature values as new feature spaces to obtain a feature data set after dimension reduction, taking the feature data set after dimension reduction as input, constructing a credit rating prediction model by using a random forest algorithm, calculating importance scores of all features to rating results, and sorting the results according to the importance scores of the features to obtain a credit rating result. And selecting the first n features with higher scores as key feature factors, and constructing a credit evaluation feature vector. According to the method, a more accurate and comprehensive evaluation result is provided for building credit rating, and green building development and realization of energy conservation and emission reduction targets are effectively supported.

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 smart communities, and discloses a smart community intelligent security scheduling management method based on deep learning, which comprises the following steps: acquiring video monitoring data and access control record data of a plurality of communities, cleaning the data, unifying the format and content of the data by adopting a data standardization technology, and storing the unified data into a database; the method comprises the steps of obtaining standardized community security and protection data, mining a personnel flow mode and a vehicle track mode among different communities by adopting a graph algorithm analysis technology on the basis of a community relation network to obtain a cross-community personnel flow mode and a vehicle track mode, and obtaining a cross-community security and protection result according to analysis results of the cross-community personnel flow mode and the vehicle track mode. And an anomaly detection algorithm is adopted to identify potential safety hazards, and if an abnormal condition is detected, early warning information is generated. According to the invention, deep correlation analysis of cross-community security data is realized, and the intelligent level of community security management is effectively improved.

The invention discloses a smart community comprehensive service method, system, device and product, and relates to the field of smart community services, and the method comprises the steps: obtaining sensor data in a current community; the sensor data in the current community comprises behavior data, equipment data and environment data of residents; performing data mining and predictive analysis on the sensor data in the current community by using a user behavior analysis model to obtain a future behavior trend; the user behavior analysis model is a deep learning network or a machine learning algorithm; analyzing the future behavior trend by using a machine learning model to obtain a resident demand; the machine learning model is a model which is obtained by training a cloud database and is deployed in an edge computing node. According to the invention, efficient operation of the system and quick response of services can be ensured, intelligent and personalized service recommendation is provided, all-around demands of residents are met, and user experience is improved.

The invention relates to the technical field of smart communities, and discloses a smart community intelligent security monitoring management method based on data interconnection, which comprises the following steps: acquiring real-time monitoring data, reading a preprocessed monitoring data set from a database, extracting feature parameters related to community security patrol, and determining the real-time monitoring data; the characteristic parameters comprise road length, road width, building height and building density, and constructing a community security patrol environment model based on the characteristic parameters; and aiming at the community security patrol route optimization model, solving by adopting an ant colony algorithm to obtain a plurality of candidate optimal patrol routes, evaluating the candidate optimal patrol routes according to historical patrol data, and selecting the patrol route with the optimal comprehensive evaluation index as the optimal patrol route. According to the invention, intelligent and fine management of community security patrol is realized, the patrol efficiency and the safety prevention and control level are improved, and powerful decision support is provided for community security management.

The invention provides a smart community Internet of Things access control operation system, and relates to the technical field of data processing, the system comprises: a data acquisition module, used for obtaining a standard identity data set; the preliminary verification module is used for matching the standard identity data set with a preset resident database to generate preliminary verification result data; the distributed computing node module is used for performing deep verification on the preliminary verification result data through computing nodes to obtain final verification result data; the task distribution module is used for generating node distribution data; the load balancing module is used for adjusting node distribution data; the fault-tolerant processing module is used for redistributing the verification task of the fault node to other computing nodes; the dynamic authority management module is used for generating access control authority information for the user according to the final verification result data; the access control module is used for controlling target access control equipment to execute door opening operation; according to the invention, the data processing efficiency of the system is improved.

The invention relates to the technical field of parking lot operation, and discloses an optimal scheduling method for an intelligent parking lot of an intelligent community, the core of the method is to construct an intelligent parking decision model, the model models the scheduling process of the parking lot into a Markov decision process, and intelligent scheduling is realized by defining a state space, an action space, rewards and strategies. The reward function design comprehensively considers the parking space utilization rate, the vehicle access speed, the user satisfaction degree and the operation cost, and supports dynamic adjustment to meet actual requirements and user feedback. And carrying out model training by adopting a deep Q network algorithm, and evaluating a model effect through an A / B test. In the real-time scheduling stage, the method can collect the state information of the parking lot in real time, selects the optimal action according to the current state and strategy, and achieves efficient and intelligent parking management. The implementation of the invention is helpful for improving the overall intelligent level of the smart community, enhancing the attraction and competitiveness of the community, and providing powerful support for the construction and development of the smart community.

The invention discloses a smart community new energy grid management and analysis system, and belongs to the technical field of smart power grid and energy management, and the system comprises a data collection module which is used for collecting photovoltaic power generation, energy storage equipment and user power utilization data in real time; the dynamic modeling module is used for dynamically generating a multi-level energy grid division scheme according to the collected data; the optimization decision module is used for outputting energy regulation and control parameters according to the grid division scheme; and the iterative feedback module is used for monitoring the regulation and control effect and triggering online updating of the model parameters. According to the method, a dynamic grid topology adaptive division mechanism, a multi-source adaptive collaborative optimization algorithm and a pre-verification type network splitting simulation technology are adopted, so that real-time dynamic reconstruction, multi-target joint optimization and millisecond-level security risk prevention and control of a community energy network can be realized; the problems of high transmission loss, response delay, equipment service life reduction and the like caused by traditional static division are effectively solved.

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 relates to the technical field of data processing, in particular to a multi-modal sensor data real-time fusion processing method for a smart community. According to the method, a sensor network topological graph is constructed, a connection weight is optimized, distributed clock synchronization is realized by using a graph Laplacian matrix, and clock drift prediction and compensation are performed in combination with a fractional Brownian motion model; performing wavelet transform decomposition on the sensor data after time sequence alignment, calculating each scale Hurst index, predicting a load trend through a fractal prediction model, and outputting an optimal resource allocation scheme through hybrid evolution calculation; the method comprises the following steps: constructing multi-modal sensor data into a graph structure, extracting node features by using a graph convolutional neural network, obtaining global feature representation by using a self-attention mechanism, and performing anomaly detection classification in combination with a resource utilization rate and a prediction error; an anomaly detection feedback mechanism is established, and Laplacian matrix eigenvalues and weight parameters are dynamically adjusted; the real-time performance, the accuracy and the robustness of data fusion processing are improved.

The invention discloses a smart community dynamic combination access control verification method and system, and the method comprises the following steps: obtaining corresponding user data through an access control system when a user carries out access control verification in any verification mode; according to the user data and the system data of the access control system, the historical recognition success rate of the user, the safety coefficient of the current time period, the safety level of the user and the recent suspicious activity index are calculated; calculating a user score according to the historical recognition success rate of the user, the safety coefficient of the current time period, the safety level of the user, the recent suspicious activity index and a preset weight; and determining a verification mode needing to be executed by the current user according to the calculated user score and a preset judgment rule. On the premise of not influencing the daily access control access experience of the user, the access control access safety coefficient is effectively improved, and the convenience and safety of different types of personnel are balanced.

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 discloses a method and a device for generating a smart community digital twin interaction system. The method comprises the following steps: acquiring information data of each physical entity of a community; constructing a smart community three-dimensional model according to the information data; associating the physical entity with a virtual object corresponding to the physical entity in the three-dimensional model to enable the physical entity and the virtual object to form a mapping relation; designing an interaction logic and an interaction interface of the user and the three-dimensional model according to the mapping relation; according to the interaction logic and the interaction interface, generating an initial smart community digital twin interaction system; collecting feedback of the user in the initial intelligent community digital twin interaction system; and iteratively optimizing the interaction logic and the interaction interface according to the feedback, and generating the intelligent community digital twin interaction system. According to the intelligent community digital twin interaction system generated by the method, the community management efficiency can be remarkably improved, the life experience of residents is improved, and the sustainable development of the community is promoted.

The invention discloses a smart community private data sharing method supporting access strategy updating, and relates to the technical field of information security. The method relates to four entities of a community management center, community cloud, a data owner and a data requester, and comprises nine algorithms of system initialization, community cloud key generation, community member key generation, data encryption, update key generation, strategy update, trap door generation, ciphertext retrieval and decryption. According to the invention, access control of the data requester in the smart community can be realized; an access strategy can be updated, and different access control conditions of data owners in the smart community can be responded; non-interactive private data sharing between a data owner and a data requester can be realized; sensitive information in the data can be protected under the condition that a ciphertext retrieval result is leaked; and the unforgeability of the updated key can be ensured.

The invention relates to the technical field of smart communities, in particular to a future community construction method and system based on government big data, and the method comprises the following steps: collecting power use data, water resource consumption data and public transport utilization rate data in a community, synchronizing the data, and carrying out the standardization processing, and generating a community resource use data set. According to the method, through a time sequence analysis method, the resource demand of a community in a future week can be effectively predicted, a resource flow simulation model is established, prediction data is input in real time, model parameters are adjusted, influences of policies are continuously simulated and evaluated, optimal allocation of community resources is achieved, and the community resource allocation efficiency is improved by constructing a resource allocation diagram and determining an optimal path. The method achieves the high efficiency and fairness of resource distribution, continuously tracks the distribution effect and resident feedback, further guarantees the adaptability and continuity of resource distribution, not only optimizes the community resource management, but also improves the welfare of residents, and enhances the sustainable development of communities.

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 discloses a multivariate data access and fusion resident community energy metering device, and the device comprises a data collection module which is used for collecting multi-energy data in a resident community through a plurality of communication interfaces, the energy comprises electricity, water, gas and heat, and the communication interfaces support RS485, NB-IoT, LoRa, Zigbee and Wi-Fi; an edge calculation module connected with the data acquisition module and used for preprocessing the acquired multi-energy data, including data format standardization, time sequence reconstruction and preliminary anomaly detection; the data fusion module is connected with the edge calculation module and is used for performing multi-dimensional modeling and data fusion on the multi-energy data based on a deep learning algorithm; compatible access of multi-energy equipment such as electricity, water, gas and heat is realized through modular design, real-time processing, intelligent analysis and user-friendly interaction of energy data are realized by adopting edge computing and deep learning technologies, and technical support is provided for development of smart communities and green buildings.

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 discloses a digital community governance management system and method based on artificial intelligence, and relates to the technical field of big data analysis. A BIM modeling method is combined with a community building drawing to construct a community virtual model, residence units are divided in the virtual model, a database is established, mapping of the model and data is achieved through a Revit plug-in, and the system and the method have the advantages that the system and the method are simple and convenient, and the system and the method are easy to implement. The method comprises the steps of collecting resident behavior data through Internet of Things equipment, converting the resident behavior data into a third-order tensor, extracting spatial and temporal features by using a convolutional neural network and an LSTM network, optimizing a training model in combination with a cross entropy loss function, constructing a behavior feature library system and an activity label system, and realizing accurate pushing of information through matching degree calculation and dynamic pushing threshold setting. And finally, the data is updated according to the feedback information of the residents, a service closed loop is formed, the pertinence of activity pushing is improved, the community interaction experience is enhanced, and a data-driven intelligent solution is provided for intelligent community construction.

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 relates to an intelligent community charging pile management method and device, equipment and a medium, and the method comprises the steps: obtaining the real-time power utilization state data of a community, determining a corresponding effective charging power interval based on the power utilization state data, building a multi-level charging strategy according to the effective charging power interval, and carrying out the management of the charging pile of the intelligent community. A corresponding charging strategy is matched and issued to the target charging pile, operation data of the target charging pile are dynamically monitored, and the charging power of the target charging pile is adjusted in real time to not exceed a safety load limiting threshold value contained in a preset power grid bearing threshold value; generating and pushing a corresponding exclusive charging mode according to pre-acquired historical use behavior data of the user; based on an intelligent regulation and control mechanism of a cell-level load state and user multi-dimensional information, dynamic perception and hierarchical control of a charging process are realized, the load prediction capability is enhanced, and efficient scheduling and ordered management of charging behaviors in an intelligent cell are realized.

The invention relates to the technical field of data processing, in particular to a smart community management and control method based on multi-dimensional data monitoring, which comprises the following steps: collecting multi-dimensional data in a smart community, and sequentially caching, cleaning, integrating and compressing the multi-dimensional data to output optimized data, training an early warning model by using the optimization data to output an active safety model; monitoring and controlling the smart community through the active security model, giving an alarm when an abnormal condition occurs, and displaying alarm information on a visual interface; determining the management and control stability of the smart community based on the variance of the packet loss rate of the multi-dimensional data; if the management and control stability does not meet the requirement, adjusting the cache size of the multi-dimensional data, or determining the management and control reliability of the smart community based on the early warning missing report rate of the abnormal condition; and if the control reliability does not meet the requirement, adjusting the batch training size of the optimized data. The management and control stability of the smart community is 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 discloses a wireless talkback and smart home integrated system for a smart cell and a control method thereof, an ad hoc network wireless local area network is constructed through an ESP-WIFI-MESH protocol, and the wireless talkback and smart home integrated system comprises an outdoor host, a wireless repeater and an indoor extension. The system adopts mesh topology to realize multi-hop redundant transmission, automatically selects an optimal path and ensures communication reliability; dynamic priority scheduling of alarm, voice, video and smart home control data is supported, wherein the alarm signal is the highest priority. The indoor extension set is integrated with a multi-protocol gateway and is compatible with Wi-Fi / Bluetooth / ZigBee equipment, so that wireless access of smart home such as water, electricity and meters is realized. The community integrated management platform monitors the state of equipment in a centralized manner, and supports remote management, anomaly detection and emergency linkage. The system has the advantages of being low in cost, easy to expand, short in construction period and the like, the problems of complex wiring, signal shielding and the like in old community reconstruction are effectively solved, and community security and protection intelligence is improved.

The invention discloses a digital human interaction system and method based on a smart community, and the method comprises the steps: collecting the questioning voice of a user through a recording device, carrying out the voice recognition of the questioning voice of the user, and obtaining a text recognition result of the questioning voice of the user; a data processing and text semantic understanding algorithm based on artificial intelligence and a natural language processing technology is introduced at a rear end to perform semantic analysis on a user question voice text recognition result, so that user question semantics in the user question voice text recognition result are carefully and fully captured, and an answer text meeting user requirements is generated; and displaying the answer text in an answer window of the digital human object. In this way, the user problem can be understood and optimized, so that the generated interaction content has higher matching degree and user satisfaction.

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.