136 results about "Park management" patented technology

The invention discloses an AI-based smart park multi-source data fusion method and system, and the method comprises the steps: generating a time-space aligned standardized data flow according to environment parameters, energy consumption waveforms, security signals and personnel trajectory data collected by a heterogeneous sensor network; generating a multi-modal fusion feature matrix based on the standardized data stream; according to the multi-modal fusion feature matrix, generating a three-dimensional twinborn body including the equipment state, the people flow density and the energy consumption hot spot in real time; inputting the three-dimensional twin into a multi-target constrained reinforcement learning algorithm, and fusing real-time data and prediction data to generate a Pareto optimal solution set; and based on the Pareto optimal solution set, generating a final instruction set for driving park equipment regulation and control, and triggering collaborative response of a security and protection system and an energy consumption system at the same time. According to the embodiment of the invention, intelligent upgrading of park management can be realized through cross-modal feature extraction, dynamic digital twin modeling and reinforcement learning optimization.

The invention discloses a smart park safety protection system and method based on smart video analysis and multi-mode integration, and relates to the technical field of smart park management. The system comprises a camera, an environment microphone and an access control terminal which are deployed in a park, an edge computing node is used for extracting structured video, audio and access control features, a central server realizes multi-modal space-time alignment through a self-calibration module, a multi-modal fusion module constructs a joint representation vector based on a low-rank tensor algorithm, and the joint representation vector is used for realizing multi-modal space-time alignment. And the security decision module identifies an abnormal event and triggers a response strategy in combination with a classification and anomaly detection model. According to the invention, multi-mode cooperative identification, high-robustness behavior analysis and intelligent response linkage are realized, and the real-time performance, accuracy and intelligent level of a park security system are improved.

The invention discloses an intelligent park management system based on cloud computing and Internet of Things, and relates to the technical field of park management systems, and the system comprises a dynamic digital twinborn body module which comprises a heterogeneous data fusion layer which integrates a BIM model, LiDAR point cloud, an unmanned aerial vehicle inspection image and distributed loT sensor data, and eliminating timestamp deviation of multi-source data by adopting a space-time alignment algorithm, and generating a millimeter-level precision three-dimensional park twin model. Through the construction of the high-precision digital twinborn model, the panorama and equipment operation state of the park can be accurately presented in real time, the timestamp deviation and spatial registration error of multi-source data are eliminated, the real-time performance and accuracy of the data are improved, a solid data basis is provided for subsequent intelligent simulation and early warning decision, and the response and monitoring capabilities of the system are improved.

The invention discloses a park management method based on digital twinning, particularly relates to the field of park operation, and is used for solving the problem that a multi-source event is difficult to stably chain under the conditions of compensation delay and evidence gap and causes misalignment of disposal triggering. Comprising the following steps of: registering an event in a pool to generate an event number and writing the event number into a platform arrival moment; screening and mapping an anchor point event to a park object identifier and a process stage identifier to generate a management token; checking a stage sequence and an evidence item requirement set according to an event chain rule table in event chain construction and generating a conflict point list; the delay portrait library generates a credible mark when a source is generated and forms a reverse sequence violation spectrum; the digital twin object relation graph forms an influence domain span mark; the closed table is returned to obtain a disposal convergence guarantee level; the cost-sensitive decision tree outputs a disposal template identifier, and the disposal template table generates a management action instruction and a trigger voucher and records an instruction acceptance identifier; and returning, comparing and freezing the exception management token, and updating the event chain rule table and the delay portrait library.

The invention provides a smart park operation and maintenance management method and system based on CIM and a medium, and belongs to the technical field of smart park management. The method comprises the following steps: constructing a CIM digital twinborn model based on a park building group, a geographic position, Internet of Things equipment and business data, and synchronously extracting equipment state and energy consumption information; analyzing the state data by using the equipment fault prediction model and generating a repair work order to realize predictive maintenance; performing gridding processing on the energy consumption data, generating a thermodynamic diagram and identifying an abnormal energy consumption area; and positioning a high-energy-consumption grid by combining an energy consumption analysis model, and generating a comprehensive operation and maintenance scheme of equipment regulation and control, energy scheduling and system optimization through matching of an energy management strategy library. According to the invention, the digital twinning technology and the CIM platform are fused, so that full-life-cycle management and dynamic energy consumption optimization of the equipment are realized, the operation and maintenance efficiency is remarkably improved, the failure rate and energy waste are reduced, and both economy and environmental protection are achieved.

The invention relates to the technical field of resource scheduling, in particular to a smart park resource scheduling method and system, and the method comprises the steps: constructing a heterogeneous information network representing the current state of a park; performing feature extraction on the heterogeneous information network by adopting a graph attention convolutional network, and generating a state embedding vector fused with high-order neighborhood information; inputting the state embedding vector into a scheduling strategy model, and predicting the expected variation of the candidate scheduling action to future park energy consumption, security index and traffic efficiency; according to the state embedding vector and an external management instruction, determining an optimization target of a current scheduling period from a preset operation normal form, and allocating a dynamic weight; and calculating a comprehensive utility score of each candidate scheduling action, and issuing and executing the candidate scheduling action with the highest score as a final scheduling instruction. According to the invention, the refinement level and the overall operation benefit of park management are improved.

The invention relates to the technical field of smart park integrated management, and discloses a smart park comprehensive management and control system and method based on multi-modal data analysis, and the method comprises the steps: obtaining a park multi-dimensional real-time data flow, and extracting a current situation feature vector and a personnel distribution thermodynamic diagram; analyzing the historical emergency event data sequence by using a space-time convolutional neural network, and outputting an event type identification vector; and generating a dynamic evacuation path planning and resource scheduling scheme based on a graph optimization algorithm, constructing a minimum cost flow optimization problem taking the weighted sum of time cost and waiting time as a target function, and solving to obtain an optimal people flow allocation scheme. The problem that emergency response cannot adapt to dynamic environment changes is solved. Experiential knowledge cannot be effectively inherited and utilized. And the emergency response system is slow in response and improper in resource allocation.

The invention discloses an artificial intelligence and Internet of Things smart park integrated management method and system, and belongs to the technical field of smart park management, and the method comprises the following steps: S1, collecting multi-source operation data of Internet of Things smart park equipment in real time, and generating a multi-source data stream; s2, generating a multi-dimensional feature set based on the multi-source data stream; s3, analyzing a behavior mode of an administrator of the Internet of Things smart park based on the historical operation record, and generating an administrator behavior portrait and an event priority evaluation result; s4, dynamically constructing a visual management interface according to an event priority evaluation result, and generating a one-key operation instruction set; and S5, collecting operation response data of the administrator on the visual management interface, and updating the administrator behavior portrait. The system comprises a data acquisition module, a feature analysis module, a priority evaluation module, a generation module and a feedback module. According to the method, the complex state of the park is comprehensively captured through the steps S1 to S5, and the problem of information fragmentation is solved.

The invention relates to the technical field of smart park data monitoring, and discloses an artificial intelligence smart park multi-source data monitoring and analysis method. The method comprises the following steps: constructing a park operation state basic model; when the model is identified to be abnormal, data dynamic change characteristics are extracted by utilizing a spatio-temporal data fusion technology, and an abnormal event mode in a specific region is identified by combining deep belief network deep analysis; calculating data complexity by using permutation entropy, optimizing and analyzing an abnormal propagation path in combination with an A star algorithm, and evaluating a diffusion range and an influence path; recognizing a comprehensive risk area, analyzing the environment and equipment state characteristics of the area through a multispectral imaging technology, and evaluating the operation abnormity in combination with real-time multi-source data; and performing accurate intervention on the comprehensive risk area based on the abnormal condition. According to the method, effective integration and analysis of multi-source data of the smart park are realized, abnormity is accurately identified, risks are mastered, a scientific means is provided for park management, and stable and efficient operation of the park is guaranteed.

The invention discloses a cloud-edge collaborative multi-modal reasoning method and system for park governance, and relates to the related field of multi-modal intelligent reasoning, and the method comprises the steps: collecting and processing local multi-modal sensing data through a plurality of edge nodes, carrying out the single-modal reasoning based on a lightweight AI model, and generating a plurality of pieces of edge event description information; based on a dynamic triggering mechanism, evaluating the multiple pieces of edge event description information to determine whether an event processing strategy judges whether to trigger a collaborative reasoning request; for the marked edge node triggering the request, based on an attention mechanism, performing fusion reasoning on the multi-modal feature information uploaded from the marked edge node to generate a joint reasoning result; and the cloud generates a governance instruction according to the joint reasoning result and issues the governance instruction to the marked edge node to drive and execute a park governance action. The technical problem that the real-time performance and the reliability of existing multi-mode reasoning oriented to park management are insufficient is solved, and the technical effect of improving the real-time performance and the reliability of park management is achieved.

The invention relates to a park green land service level optimization evaluation method and device, a terminal and a medium, and the method comprises the steps: coding environment monitoring data and tourist positioning data into a unified space-time grid through a multi-source data fusion technology, and constructing a dynamic supply and demand prediction model; based on collaborative analysis of vegetation irrigation capability and tourist gathering intensity, quantifying a time-space conflict degree between a resource strategy and peak activities; a dynamic weight distribution mechanism is adopted to optimize collaborative parameters of an irrigation period and a diversion path, and an adjustment scheme considering both resource efficiency and tourist experience is generated; and finally, realizing closed-loop optimization of the park service level through multi-dimensional index fusion evaluation. According to the method, the problems of resource supply and tourist demand separation, response lag, experience decision deviation and the like in a traditional management mode are effectively solved, the irrigation conflict rate is remarkably reduced, the tourist satisfaction degree is improved, and a decision basis is provided for intelligent park management.

The invention belongs to the technical field of smart park management, and discloses an Internet of Things data fusion method for comprehensive management of a city-level smart park. The method comprises the following steps: constructing an odor spatial distribution model corresponding to each park, and carrying out chemical component analysis to obtain park odor characteristics of each park; comparing the park odor characteristics with a predefined normal odor baseline, and dynamically identifying abnormal odor characteristics corresponding to each park; determining a potential risk event corresponding to each park based on the abnormal odor characteristics; based on the odor spatial distribution model and the abnormal odor characteristics, reversely positioning the position of an abnormal source, and generating an odor source positioning map corresponding to each park; according to the potential risk event and the smell source positioning map, a targeted emergency response strategy is automatically generated and executed; according to the invention, a closed-loop management system from monitoring and early warning to emergency response can be formed, and the environmental risk prevention and control capability and the emergency response speed of the park are improved.

The application discloses a data management platform for smart park construction and belongs to the technical field of smart park management, and specifically comprises the following steps: collecting resource demand data and resource supply data of each enterprise in the park, performing demand feature extraction operation on the collected resource demand data to generate a structured demand description, performing supply feature extraction operation on the resource supply data to generate a structured supply description, calculating the matching degree between demand and supply based on the structured demand description and the structured supply description and generating an initial matching scheme, performing constraint condition checking operation on the initial matching scheme according to the park operation strategy to identify matching pairs that violate the constraint conditions, performing scheme adjustment operation on the matching pairs that violate the constraint conditions to generate an optimized matching scheme, and finally scheduling the park resources to complete resource data sharing between enterprises; and the application realizes intelligent management and efficient sharing of resource data in the park, and improves the overall resource utilization efficiency of the park.

The invention relates to the technical field of intelligent Internet of Things platforms, in particular to a smart park management platform for the Internet of Things and an intelligent algorithm, and the system comprises a terminal state sensing module, a response path combination module, a control path sorting module, a communication window adjustment module and a distribution execution regulation and control module. According to the method, equipment response records with associated numbers are extracted, a control set with a parallel relationship in a scheduling period is constructed, a control chain structure with a sequential triggering relationship is formed through connection in combination with the consistency of signal emission and a target response sequence in an instruction track, and paths are divided according to control sources, a number sequence and target types; and the initial time sequence and the response interval characteristics are matched to carry out channel grouping, so that the coordination relationship among multiple chains is enhanced, the hierarchical structure of path organization is enhanced, and the coherent operation capability of a control process in a multi-device scheduling scene, the instruction passing efficiency and the distributed regulation and control capability of communication execution are improved.

The invention relates to the technical field of park facility management, and provides a smart park management system based on big data and the Internet of Things technology, and the system comprises a digital twinborn modeling unit which is used for collecting park space data and constructing a dynamically updated park digital twinborn model; the environment monitoring units are distributed at preset position points of the park, monitor environment parameters in real time and upload the environment parameters to the cloud; the intelligent patrol unit moves according to a preset route and collects environment data and image information of the patrol route; and the data analysis unit is used for predicting environmental parameters of the patrol path based on the digital twinborn model and the environmental monitoring data. Through an innovative segmented prediction-deviation coupling algorithm, the system realizes the breakthrough progress of reducing the calibration deviation rate of the sensor. A risk coefficient Ri model of multi-parameter collaborative analysis is introduced, so that the false alarm rate of environment anomaly recognition is greatly reduced, and the common invalid overhaul problem in a traditional monitoring system is effectively avoided.

The invention provides a safety management and control method and system applied to an emergency material storage park, and relates to the technical field of emergency material storage management.The safety management and control method comprises the steps that firstly, a safety state link which is based on multi-source monitoring information, comprises material storage nodes, environment nodes and active nodes and forms a net-shaped structure through associated edges is constructed; tracking the evolutionary process, and recording the state information of each node and the associated edge along with time change to generate link evolutionary data; then, a management and control action set of a corresponding relation is formed based on link evolution data adaptation and node states; the management and control action set is sent to the park management and control system to drive an execution device to execute, and feedback data after execution is collected; and finally, calibrating the evolution trend of the safety state link according to the feedback data. Therefore, the safety management and control level of the emergency material storage park can be comprehensively improved.

The invention discloses a smart park management platform based on park informatization construction, which belongs to the field of park management and comprises a data management module, a simulation modeling module, a scheduling evaluation module, an access control module, a block evidence storage module, an intelligent service module, a user interaction module, a closed-loop optimization module and a system management module. According to the method, accurate prediction of park resource requirements and dynamic calibration of the digital twinborn model can be realized, the park operation efficiency and the resource utilization rate are improved, and compared with traditional static authority management, internal threat risks are remarkably reduced, and a transparent basis is provided for security audit and responsibility definition.

The application discloses a full life cycle management system and method for a smart park based on digital twinning and the Internet of Things, relates to the technical field of smart park management, and comprises a sensing edge module, a data management module, an intelligent analysis module, a life cycle module and a twinning modeling module.The application supports multi-protocol access and edge computing capability, greatly improves data transmission efficiency and stability, the intelligent analysis module outputs accurate analysis results by constructing a multi-class feature matrix and a deep multi-task joint modeling mechanism, and provides data support and model guidance for park dynamic management and intelligent decision-making, the life cycle module fuses Kepler optimization algorithm, multi-agent reinforcement learning and simulated annealing algorithm, establishes a collaborative optimization mechanism, realizes the combination of global search and local fine-tuning of resource scheduling, and effectively optimizes energy consumption, response time, space utilization and safety risks, and the twinning modeling module constructs a three-dimensional model of the park, improves system interactivity and operability.

The invention provides a multi-park-oriented equipment operation and maintenance work order assignment method and a path planning system, and belongs to the technical field of multi-park management. The method comprises the following steps: constructing a digital twinborn model of a'park-building-space-equipment-accessory-operation and maintenance personnel 'six-level topology, splitting an operation and maintenance work order into feature vectors of skill requirements, accessory requirements and energy consumption sensitivity, and generating an initial order dispatching scheme and path planning based on a topological relation and the feature vectors; and the order dispatching scheme and the path planning are dynamically adjusted according to the real-time feedback of the equipment monitoring system in the execution process. According to the method, integrated intelligent decision and dynamic optimization of accessories, personnel, paths and energy consumption are realized, the problems of difficult resource coordination and response delay in multi-park operation and maintenance are effectively solved, and the operation and maintenance efficiency and the resource utilization rate are remarkably improved.

The invention relates to the technical field of smart park management and cloud computing, in particular to a smart park safety management method based on cloud edge cooperative computing. According to the method, the multi-source data is acquired through the terminal device which is calibrated periodically, and the lightweight AI model of the edge node performs preliminary analysis according to the screening threshold and uploads the suspected hidden danger data. And the cloud platform performs deep analysis by using the prediction model, evaluates the security situation level and triggers early warning and emergency response. Meanwhile, the cloud model recognition accuracy, the edge model false alarm rate and the actual hidden danger proportion in the uploaded data are comprehensively calculated, the safety management characterization value is generated, the system state is judged based on the safety management characterization value, then the edge screening threshold value and the data uploading strategy are adaptively and dynamically adjusted, and a continuously-optimized management closed loop is formed. The safety management efficiency of the smart park is improved.

The invention provides a smart park IBMS integration method and a smart park IBMS integration system, which are applied to the technical field of smart park management, and are used for dynamically sensing the personnel state and activity property of a functional area by integrating and analyzing multi-source personnel activity data so as to intelligently match a refined environment control strategy. And self-adaptive adjustment of environmental parameters is realized through the building automatic control system, so that the problem that an existing IBMS system is difficult to carry out refined environmental control based on personnel activity data is solved, the comfort level, the energy efficiency and the intelligent level are improved, the environmental parameters can be dynamically adjusted according to the real-time activity conditions of personnel in a functional area, and the environmental control efficiency is improved. The comfort level is improved; and meanwhile, the energy utilization efficiency is optimized.

The invention discloses a smart park risk early warning system based on big data, relates to the technical field of smart park management and safety early warning, and provides the following scheme that the system comprises a data acquisition unit, a data transmission unit, a data storage and processing unit, a behavior analysis unit, a risk analysis unit and a user interaction unit; and the data acquisition unit is used for acquiring multi-dimensional data in the park. According to the method, various conditions in the park can be comprehensively perceived, the limitation of traditional single data acquisition is broken through, a rich and comprehensive data basis is provided for subsequent risk analysis and early warning, meanwhile, accurate identification and prediction can be carried out for different types of risks, the accuracy of risk judgment is improved, the situations of false early warning and missing early warning are reduced, and the safety of the park is improved. Meanwhile, emergency linkage equipment can be automatically triggered, the risk response time is shortened, and precious time is won for taking response measures in time and reducing risk loss.

The invention belongs to the technical field of park management, and particularly relates to a smart park management system based on Internet of Things, which comprises the steps of acquiring multi-source monitoring data in a smart park, including infrared thermal imaging video streams, equipment current waveform data and microenvironment meteorological parameters; super-resolution reconstruction based on an attention mechanism is carried out on the multiple paths of video streams, and a 4K enhanced video marked with dynamic metadata is generated; the system can perform real-time monitoring on the enterprise park, can perform cloud storage, avoids the situation that video data cannot be found after being covered, can perform remote monitoring at the same time, can obtain changes of emergency conditions in real time when personnel need to enter the park, brings certain danger, improves safety, and is more intelligent.

The invention discloses a time prediction method, computer equipment and a computer readable storage medium. The method comprises the following steps: determining data information of at least one park node and at least one inter-park route node; based on the data information, determining an initial time prediction value when the vehicle arrives at the at least one park node; and correcting the initial time prediction value through a Kalman filtering method, and determining a target time prediction value when the vehicle arrives at the at least one park node. Therefore, the time when the vehicle arrives at the at least one park node can be accurately predicted, the overall efficiency of vehicle transportation and park management can be improved, and the user experience is improved.

The invention discloses a smart park comprehensive security and protection management system, which belongs to the technical field of smart park management, and comprises a data acquisition module for deploying edge computing nodes in each key area of a park in a distributed manner, the edge computing nodes acquiring park videos and sensor data, a data fusion module for establishing a fusion algorithm model in an area server, the multi-source heterogeneous data collected by the edge computing nodes are analyzed, processed, associated and fused, the risk identification module carries out risk identification and risk type determination on the fused multi-source heterogeneous data, and the risk positioning module constructs a park three-dimensional model and positions the determined risk, so that key data can be preferentially processed, the system response efficiency is improved, and the risk identification and risk type determination accuracy is improved. Deep hidden danger excavation and accurate judgment of risk types are achieved, managers are helped to quickly master the risk diffusion trend, scientific and effective countermeasures are generated, and the emergency disposal efficiency is improved.

This application relates to the field of smart park management technology, and discloses a method for automatic triggering and closed-loop management of park tasks based on key semantic mining. It collects, cleans, and sorts park meeting audio and business text in real time to form a key data stream. Key semantics are extracted through lexical and syntactic analysis and converted into business feature tags through feature mapping. These tags are input into a pre-set task model for rule collision and constraint calculation to generate execution tasks. After trigger addressing and packetization, task distribution instructions are generated and delivered to vertical domain digital human agents via a collaborative distribution network to complete multi-agent collaborative execution and produce execution data. This solves the technical problem of lagging business perception and disconnected task execution in traditional park management.

The application discloses an integrated management and control system and method for a smart industrial park based on the Internet of Things, and relates to the technical field of park management and control, which comprises the following steps: collecting park event data, equipment operation data and management and control resource state data, generating event trigger states and management and control resource available states; generating an event influence window according to the event trigger states and the equipment operation data; generating an event resource matching result and an event disposal path based on the event influence window and the management and control resource available states; generating an event disposal instruction according to the event disposal path, collecting corresponding event disposal feedback of the event disposal instruction, rewriting the event influence window and the management and control resource available states according to the event disposal feedback, and generating an integrated management and control result for the park; and the application improves the adaptation degree among event disposal, resource linkage and feedback rewriting under the condition that multiple types of events in the park continuously and concurrently trigger and management and control resources are scattered and occupied.

The application provides a safety management and control method and system applied to an emergency material storage park, relates to the technical field of emergency material storage management, and first constructs a safety state link based on multi-source monitoring information, containing material storage nodes, environment nodes and activity nodes and forming a net structure through associated edges; then traces the evolution process, records the state information of each node and associated edge changing with time to generate link evolution data; then adapts the control action set corresponding to the node state based on the link evolution data; then sends the control action set to the park management and control system driving execution device for execution, and collects feedback data after execution; finally, the evolution trend of the safety state link is calibrated according to the feedback data, so that the safety management and control level of the emergency material storage park can be comprehensively improved.

1. The name of the design product: inspection robot. 2. The use of the design product: as a modern intelligent park management inspection management tool in security, environmental monitoring, equipment maintenance and other aspects. 3. The design points of the design product: in shape. 4. The picture or photo that best indicates the design points: perspective view.

This invention relates to the field of park management technology, specifically to a park intelligent management system and method based on optoelectronic 3D imaging digital twins. The system includes: a generation module that uses optoelectronic 3D sensing technology to generate a complete 3D point cloud model of the park, the 3D point cloud model including a digital twin; a real-time sensing module that senses real-time park information, the real-time park information including multimodal data; and a control module that controls the actions of the digital twin based on the real-time park information. Based on optoelectronic information technology, high-precision 3D sensing of the park at the centimeter or even sub-millimeter level can be achieved, providing solid data support for refined management. Through continuous point cloud data acquisition and automatic reconstruction mechanisms, the system ensures real-time synchronization between the digital twin model and the physical world. Managers can directly query 3D spatial information, understand scene status, and issue spatial operation commands through natural language, without requiring specialized 3D software operation skills.