14results about How to "Eliminate silos" patented technology

The invention relates to the technical field of building engineering, in particular to a BIM (Building Information Modeling)-based ship lock engineering virtual construction system, which comprises a project information management module, a process management module, an engineering decomposition structure management module, a mobile terminal module, a plan management module, a progress tracking module, an order management module and a progress 4D simulation module, the project information management module provides project information for the process procedure management module and the project decomposition structure management module; the process and process management module defines a construction process and a process according to project information, and is bound with components of the project decomposition structure management module; the engineering decomposition structure management module is responsible for generating decomposition structures and codes of the components; the plan management module formulates a project progress plan based on the generation information of the project decomposition structure management module; the progress tracking module monitors the progress of a construction site in real time, if the progress accords with a plan, a material order is generated through the order management module, and if the progress is abnormal, the material order is fed back to the plan management module for adjustment; the mobile terminal module provides progress update to the plan management module, and submits a production order to the order management module at the same time; and the order management module ensures synchronization of material supply and construction according to the order, and shares progress data with the progress 4D simulation module to generate dynamic visual display of the construction progress.

The invention belongs to the technical field of e-commerce logistics management, and particularly relates to an e-commerce product storage full-process monitoring management method, which comprises the steps of synchronously acquiring multi-source heterogeneous monitoring data in real time through a sensing equipment network; performing space-time alignment preprocessing on the original data, and converting heterogeneous data into a uniform data format; semantic fusion is carried out on the standardized data, and a job behavior knowledge graph with a complete spatio-temporal context is constructed; inputting the atlas into a pre-training hybrid model, and detecting an inventory abnormal event; and generating a strategy instruction in combination with the real-time order and resource data, carrying out joint analysis on an operator, and outputting a compliance score and a specific violation operation type. Through adoption of the technical scheme, complete reconstruction of the context of the operation behavior can be realized, the anomaly detection accuracy is remarkably improved, the abnormal event response delay is shortened, and the inventory loss rate caused by human errors is reduced.

The invention relates to an intelligent monitoring and decision-making system for a soil pollution remediation process, and the system comprises a data collection layer which is used for collecting and uploading the data of a pollution remediation site; the data processing layer is used for receiving, cleaning, storing and managing data of a pollution remediation site; the analysis and decision-making layer is used for carrying out intelligent analysis such as pollution diffusion prediction, equipment state monitoring and restoration progress optimization on the data; and the user interface layer is used for remote monitoring, dynamic operation and information feedback of pollution remediation data and equipment states. According to the system, through cooperative work of the data acquisition layer, the data processing layer, the analysis and decision-making layer and the user interface layer, intelligent management and scientific decision-making of the soil pollution remediation process are achieved. The system collects on-site key data in real time through the Internet of Things, provides real-time monitoring, automatic control and decision support for pollution remediation projects by combining big data analysis and machine learning technologies, and ensures that the remediation process is efficient, low-carbon and safe.

The invention relates to the technical field of industrial safety management, in particular to a cross-platform safety production data integration and sharing system which integrates an Internet of Things sensor, a high-definition monitoring camera, a data flow platform, a real-time data processing module, a rule engine, a data storage module, an API gateway, a data sharing platform, a user interface and a notification system. And a comprehensive, efficient and safe safety production management platform is constructed. The system comprises a plurality of Internet of Things sensors which are used for monitoring temperature, humidity and harmful gas in real time and transmitting data to an Apache Kafka cluster through an MQTT protocol. And the monitoring camera transmits a real-time video stream through an RTSP protocol. And performing data stream processing by using Apache Flink to realize window operation and aggregation analysis. And the rule engine Drools can dynamically adjust the alarm rule to ensure the alarm accuracy. And a unified API interface is provided through the KongAPI Gateway, so that the data access security is ensured. According to the invention, the efficiency and effect of safety production management are obviously improved, and the accident risk is reduced.

This invention discloses a trusted carbon footprint storage and intelligent traceability system for gold recycling based on blockchain and AI technologies, belonging to the intersection of green finance technology and environmental protection technology. The system adopts a four-layer architecture: the data acquisition layer binds batch IDs through GS1 encoding and integrates multi-source data through IoT sensors, a mobile app, and edge preprocessing; the AI ​​processing layer accurately calculates the carbon footprint based on a dynamic LCA model, optimizes process parameters through deep reinforcement learning, and simulates emission reduction potential; the blockchain storage layer uses a consortium blockchain (PBFT consensus) + IPFS storage, deploying smart contracts for storage and verification to automatically generate CDCEER carbon credits; the application layer provides traceability queries, ESG dashboards, regulatory audits, and green finance interfaces. This invention solves the problems of data fragmentation, inefficient calculation, and difficulty in value conversion, achieving trusted management and value conversion of the entire carbon footprint process, helping enterprises reduce costs and increase efficiency, comply with emission reduction regulations, and promote the green upgrading of the recycled precious metals industry.

The invention discloses an emergency broadcast system scheduling control scheme generation method, which relates to the technical field of emergency broadcast intelligent scheduling, and comprises the following steps: collecting a multi-source emergency event information data stream, and generating a unified event description record containing a global unique identifier, a quantitative influence level and an accurate geographical range through space-time correlation analysis and data fusion. The resource demand is calculated based on the record, and a scheduling conflict detection and optimization algorithm is utilized to generate a plurality of alternative schemes consisting of a terminal activation sequence, channel allocation mapping and broadcast time window arrangement in combination with a real-time resource state. And screening out an optimal scheduling scheme through the evaluation model and converting the optimal scheduling scheme into an executable instruction sequence. According to the method, the accurate integration of the emergency event information from heterogeneous to unified is realized, and the conflict problem in resource scheduling is solved through multi-scheme optimization decision, so that the automation level and the resource allocation efficiency of the emergency broadcast system in response to complex events are improved.

This invention proposes an intelligent remote emergency rescue management system capable of rapidly matching resources, relating to the field of remote emergency medical technology. The alarm receiving module triggers the case analysis module to generate priorities, the resource scheduling module allocates instructions to the drone control module, and after the drone completes deployment, the information matching module generates navigation information. Data from the person scanning the code is fed back to the system via the data association unit, forming a complete closed loop of resource scheduling-deployment-feedback. Through real-time data interaction between modules, the traditional emergency resource matching time is shortened from 10-20 minutes to within 2 minutes, while simultaneously improving the accuracy and utilization rate of drone AED deployment, achieving a qualitative leap in emergency response efficiency.

This invention discloses a method and system for integrated collaborative management and control of multiple public warehouses. The method includes steps S1: unified modeling of multiple warehouses and standardization of data across the entire domain; step S2: dynamic permission isolation control for multiple tenants and multiple warehouses; step S3: a differentiated rule engine driving business flow across multiple warehouses; step S4: cross-warehouse collaborative scheduling and real-time synchronization of status across the entire domain; and step S5: adaptation to the domestic IT innovation environment and end-to-end data security assurance. The purpose of this invention is to solve the problems of data fragmentation, inefficient collaboration, insufficient supervision, and incompatibility with domestic IT innovation in existing multi-warehouse systems. It provides a method and system for integrated collaborative management and control of multiple public warehouses, achieving integrated management and control with multi-warehouse parallelism, business isolation, data interoperability, process collaboration, security controllability, and full-stack domestic IT innovation compatibility.

The application provides a kind of production safety accident scene's survey information collection system, belong to information collection technical field, including: scene preliminary survey module and survey query module;Scene preliminary survey module is used to receive preliminary survey instruction, according to the preliminary survey instruction display scene preliminary survey page when receiving preliminary survey instruction;Also be used for receiving the basic information and scene survey data input by user according to the scene preliminary survey page, and obtain the survey data and plan sketch related to current accident;Also be used for generating survey record according to the basic information, the scene survey data, the survey data and the plan sketch;Improve the sharing and reuse of data, eliminate the phenomenon of enterprise information island, need to introduce the whole process of survey production management into information management, can improve the real-time nature of the survey information, information coverage, objectivity, automation degree.

The present application provides a method, system and medium for automatic specification range matching based on MES. The method includes: obtaining specification range rule matching parameter information, generating a first specification range rule matching list, then obtaining software parameter configuration list information, extracting test item name information, obtaining the corresponding matching rule number through the first specification range rule matching list according to the test item name information, matching the specification parameters of the test item according to the matching rule number, and recording the matching results, and determining whether the production line test software meets the requirements according to the matching results; the present application realizes automatic matching detection of software parameters and test item specification ranges by matching test rules according to the test item name, and further determining the rule description in combination with the verification mark, thereby improving detection accuracy and detection efficiency, and at the same time realizing data intercommunication and utilization between systems, eliminating information islands.

The invention provides a multi-refinery-plant-oriented crude oil centralized purchase, storage and pipeline transportation integrated scheduling method, which comprises the following steps: S1, demand collection and analysis: obtaining crude oil types, total demand, time windows and demand priority parameters; s2, constructing a multi-dimensional resource model based on the demand parameters and the full-link resources obtained in S1, wherein the full-link resources comprise purchase resources, transportation resources, port resources, storage resources, pipeline transportation resources and emergency resources; and S3, constructing a multi-objective optimization function, and realizing multi-constraint collaborative optimization. Due to the fact that full-link collaborative modeling is adopted, the limitation of segmented scheduling in the prior art is broken through, information sharing and plan linkage of all links are achieved, information islands can be effectively eliminated, the problems of unshipping congestion, pipe transportation idling and the like caused by link disjunction can be effectively solved, and the supply chain collaborative efficiency is improved.

The invention relates to a business collaboration model system based on cross-application linkage, and belongs to the field of enterprise informatization and intelligent office. The system comprises a user interaction layer, an application interface layer, a linkage engine layer, a data service layer and a system support and security layer. According to the method, through a unified event triggering mechanism and a data mapping model, bidirectional data circulation can be realized among different applications; according to the invention, through a cross-application automatic linkage mechanism, automatic information transmission and service connection among multiple systems are realized. A user does not need to manually copy and paste or repeatedly input information, and the system automatically identifies context semantics and triggers corresponding business processes. According to the invention, an event-driven business collaboration model is constructed, so that communication, planning, execution and feedback form a complete closed loop. Based on the modular architecture design and the configurable rule engine, each service application can flexibly define a trigger condition and a linkage rule, so that a novel office module can be conveniently expanded subsequently.

The present invention discloses a system for monitoring the physical changes of marine structures in the field of marine engineering monitoring, a data acquisition subsystem, a data processing subsystem, a data transmission and storage subsystem, a neural network learning subsystem, and a monitoring and alarm subsystem. After the neural network learning subsystem predicts the physical change trend of the marine structure, the data collected by the data acquisition subsystem is divided into key impact data and non-core data according to the prediction result. The data acquisition subsystem continuously collects the key impact data, and the monitoring and alarm subsystem performs real-time monitoring according to the preset threshold and the collected key impact data. Once an abnormal situation is monitored, the alarm mechanism is immediately triggered. The present invention realizes real-time monitoring, intelligent prediction and efficient alarm functions of marine structures by integrating multiple advanced subsystems, providing a strong guarantee for the safe and stable operation of marine structures.

The application belongs to the technical field of multi-source data processing and collaborative computing, and aims at the problems of multi-source heterogeneous data in complex dynamic scenes, such as time and space asynchronization, non-uniform characteristics, high processing delay, and weak concurrent support capability, and proposes a real-time processing and collaborative computing method for multi-source heterogeneous data with unified time and space reference. The method completes device coordinate calibration and timestamp calibration with Beidou time and space reference, realizes millisecond-level time and space synchronization; through a lightweight dynamic feature coding network and a self-adaptive weight distribution mechanism, unified feature extraction and target matching of multi-modal data are completed; an edge-cloud collaborative architecture is constructed, combined with hierarchical feature compression and asynchronous federated learning, supporting concurrent access of ten thousand devices and reducing end-to-end delay; integrating a digital twin engine and an operational optimization algorithm, scene deduction, resource scheduling and accurate instruction issuing are realized, which can be widely applied to global precise management and control in complex dynamic scenes such as ports and parks.