26results about How to "Realize collaborative management" patented technology

The invention discloses a multi-device cooperative management system based on cloud edge cooperation, and relates to the technical field of Internet of Things communication, and the system comprises a device management module which is used for connecting edge devices, carrying out the centralized management of the edge devices, and carrying out the optimal scheduling based on the functions and distribution positions of different edge devices; and the data acquisition module is connected with the equipment management module. According to the multi-device collaborative management system based on cloud edge collaboration, a comprehensive and accurate data basis is provided for multi-device collaborative management, and information exchange and collaborative work between devices are promoted; the optimization decision-making unit can formulate an equipment optimization management strategy according to the operation scheme generated by the big data analysis unit and the prediction result obtained by the prediction analysis unit, and continuously performs optimization adjustment according to the real-time operation condition of each piece of edge equipment; therefore, the system can adapt to continuously changing equipment operation environments and task requirements, and more efficient multi-equipment collaborative management is realized.

The invention provides a parallel water pump intelligent algorithm optimization combination and control method, which comprises the following steps of: configuring a sensor and a calculation module on an edge node of each water pump, acquiring and preprocessing operation data of each water pump in real time, and generating a unified real-time feature vector and a time sequence feature; dynamically calculating the service life state of the water pump according to the real-time feature vector, and quantifying the residual service life; designing a dynamic start-stop scheme based on a fuzzy logic algorithm according to the service life state, and balancing load requirements and water pump service life distribution; and based on federal learning, the residual life of the water pump is optimized in a global perspective, and an operation strategy based on a start-stop scheme is dynamically optimized and adjusted. A complete solution is formed, and a brand new technical path is provided for efficient and reliable operation of the parallel water pumps.

The invention discloses an intelligent equipment control system and method based on cloud computing, and relates to the technical field of equipment control. The system comprises a data acquisition and processing module, a user behavior analysis and preference modeling module, a standby energy consumption identification module and a real-time monitoring and adjusting module. The data acquisition and processing module collects historical power consumption data and external environment data of the smart home equipment, obtains a power consumption mode by analyzing the historical power consumption data, and performs historical energy efficiency evaluation in combination with the environment data to form an energy consumption portrait; the user behavior analysis and preference modeling module obtains user historical behavior data and constructs a user preference model; the standby energy consumption identification module identifies equipment with standby energy consumption and generates an energy-saving control scheme in combination with the use time period of the equipment; and the real-time monitoring and adjusting module implements the energy-saving control scheme, acquires the power consumption data and the environment data in real time, performs energy efficiency evaluation, and adjusts the energy-saving scheme according to the evaluation result.

The invention relates to the technical field of carbon emission management, in particular to edge calculation carbon emission equipment with a display screen. The technical problems are that a traditional carbon emission monitoring method is difficult to realize real-time monitoring and quick response, during large-scale data processing, calculation bottleneck is often faced, analysis efficiency and precision are influenced, intelligent analysis means are lacked, and valuable carbon emission modes and trends are difficult to mine from mass data; according to the technical scheme, the edge calculation carbon emission equipment with the display screen comprises a data acquisition module, an edge calculation module, a cloud calculation module, an intelligent decision early warning module and an API interface, the carbon emission management device integrating real-time monitoring, intelligent analysis and early warning decision is developed, and the intelligence and the high efficiency of carbon emission management are remarkably improved by integrating multiple modules of data acquisition, edge calculation, cloud calculation, intelligent decision early warning and an API interface.

The invention discloses a digital shipyard supply chain platform construction method. The method comprises a first stage of internal informatization foundation construction and standardization management: (1) material information carding and code standardization; (2) precise material full-life-cycle management; (3) internal collaboration and information system integration; (4) constructing a supplier management module; (5) constructing an internal cooperation and early warning mechanism; in the second stage, external collaboration module development and close cooperation: (1) external collaboration module development; (2) functional module improvement and supplier promotion; (3) strengthening close cooperation of suppliers and pre-planning of goods locations; and a third stage: zero inventory management is realized: (1) precise purchasing based on historical data analysis. According to the invention, accurate full-life-cycle management of the materials can be realized, tidy distribution and timely distribution of the tray-set materials are realized, and meanwhile, management decision support based on supply chain whole-process management business data is provided for each management layer of the supply chain.

The invention discloses a chronic disease patient diet management system, and the system comprises a data collection and integration module which is used for obtaining and fusing multi-source data, and forming a patient exclusive data set; the personalized diet scheme generation module is used for calculating and generating an initial diet scheme based on a medical rule base and the exclusive data set, and a final scheme is formed after the initial diet scheme is audited by the medical terminal; the diet scheme execution support module is used for assisting the user to adjust the diet scheme through a visual tool, a recipe library and an intelligent recording mode; and the monitoring and dynamic adjustment module is used for collecting diet execution data and physiological index data of the user, analyzing the relevance through a machine learning algorithm, generating an adjustment suggestion, and updating the scheme after confirmation of the medical end. According to the invention, multi-source data can be automatically integrated, a personalized diet scheme is intelligently generated and dynamically adjusted, and convenient execution support and continuous health management are provided for patients.

This application provides a third-party monitoring method for road transport safety management, including: a monitoring platform determining the status of a vehicle entering or exiting an assigned electronic fence based on vehicle satellite positioning data, and generating a regional alarm when a vehicle crosses the boundary or violates speed limits; executing a verification and processing procedure for various alarms generated by the monitoring platform, including platform alarms and proactive safety alarms, supporting enterprise users to appeal the verification results and subsequent review; marking the status of vehicles in special states such as being out of service, under maintenance, scrapped, or suspended from monitoring, and providing abnormal movement records and offline duration statistics queries; pushing announcement documents to subordinate enterprises or initiating safety inspection tasks, and requiring enterprises to submit reading receipts or inspection responses; generating statistical reports on daily, weekly, monthly, and yearly cycles, and supporting scheduled automatic or instant push to designated email addresses.

The application provides a PTC self-limiting temperature knee pad and a multi-source sensing combined control method, which comprises the following steps: collecting real-time pressure values of each pressure sensor in a pressure sensor array and a real-time inclination angle value of an inclination sensor; calculating a pressure difference value and judging whether the resistance measurement value is in a low resistance state defined by a positive temperature coefficient effect; limiting the heating temperature below the resistance mutation temperature by using the positive temperature coefficient effect; continuously monitoring the change of the real-time inclination angle value; when the real-time inclination angle value changes continuously below a preset activity angle threshold value for a time and exceeds a preset static time threshold value, outputting a stiffening prevention reminding instruction by a controller, and issuing a vibration reminder based on the stiffening prevention reminding instruction. The application realizes reliable judgment of heating start through a double-condition combined verification mechanism of a pressure difference value threshold and a low resistance state of PTC material.

The invention relates to high-temperature solid anaerobic fermentation equipment matched with gas pulse stirring, which comprises a closed box body, the interior of the closed box body is vertically divided into a fermentation space and a heating space by a transmission device, and the top of the fermentation space is provided with a feed pipe and an exhaust port which are provided with valves; the top of the feeding pipe is located outside, the bottom of the feeding pipe is located above the material level of the fermentation space, a plurality of gas pulse devices used for stirring materials in an air-blowing mode are communicated with the position, above the transmission device, in the fermentation space, and a discharging device for discharging solid materials is further arranged on one side of the bottom of the fermentation space; the heating space is used for receiving biogas slurry discharged from the fermentation space, a heating device is arranged in the heating space, and the heating space is communicated with the fermentation space through a pump set. According to the equipment, a high-temperature environment of solid anaerobic fermentation can be maintained on the basis of greatly reducing energy consumption, meanwhile, slag and liquid are convenient to separate, the loss of microbial colonies is small, dynamic and stable operation of anaerobic fermentation is ensured, and the proportion of methane in obtained biogas is increased.

The invention belongs to the field of visual inspection, and relates to a high-definition visual inspection and identification system based on an image processing industrial personal computer, which comprises a historical data acquisition module for acquiring image data of historical records of the same product; the feature point extraction module is used for constructing a convolutional neural network in deep learning and extracting key feature points and other feature points of the image data; the three-dimensional model construction module is used for calculating space coordinate points of other feature points in the three-dimensional prediction model; the error threshold setting module is used for setting a first error threshold and a second error threshold; the sorting scheme selection module is used for selecting a proper sorting scheme; the qualified threshold setting module is used for setting a first qualified threshold and a second qualified threshold; and the production scheme optimization module is used for selecting a proper optimization scheme. The problem that the accuracy and the consistency of detection results are difficult to guarantee due to the fact that a visual detection method is influenced by human factors is solved.

The utility model discloses a kind of storage device of potassium hydroxide, including storage container, KOH input port, inert gas input port, circulating pump system, observation port, sealing unit, cooling unit and control module are equipped on storage container;The control module is connected with metal ion concentration sensor, temperature sensor, flow sensor and pH monitor;The control module is used to collect the above sensor data, controls circulating pump system and cooling unit operating state, adjusts soft water supply flow, and triggers early warning when parameter is abnormal, simultaneously, operating data is uploaded to remote platform.

The invention discloses a network slicing management method based on a large language model and a related device, and relates to the technical field of network slicing, and the method comprises the steps: calling a global agent to receive a network slicing demand in a natural language format, and obtaining a demand intention; calling a global agent to interact with the large language model based on the demand intention to obtain a slicing request; calling a global agent to obtain a resource state in a current network; calling a large language model to determine a global resource allocation strategy based on the slicing request and a resource state in a current network, obtaining a resource allocation strategy of each sub-region, and obtaining a region slicing request of each sub-region; calling a local agent to interact with the large language model based on the region slicing request of each sub-region to obtain an operation instruction of network slicing operation performed by each sub-region; and executing the operation instruction to perform network slicing operation on each sub-region. The purpose of improving the management efficiency of the network slices is achieved based on the large language model.

The present application provides an intelligent management system for medical information data based on blockchain, which relates to the field of medical information management technology. The system includes: a medical information download module for downloading medical information; a tracking track introduction module for introducing multiple medical resource tracking tracks; a digital certificate addition module for adding non-homogeneous digital certificates; an access authorization opening module for creating an access permission list reserved for the user terminal corresponding to the target user; a model building module for establishing a medical over-analysis model; and a data collaborative management module for collaborative data management of medical information. This application can solve the technical problems of increased bacterial resistance and waste of medical resources due to the abuse and insufficient monitoring of key drugs such as antibiotics in medical resource management, and achieve the technical effect of improving the rationality of medical resource allocation and reducing the risk of drug resistance by establishing a data-driven medical over-analysis model.

The invention relates to a double-electric-drive-axle temperature control system and method and a vehicle. The system comprises a temperature collecting unit, a heat management loop, a heat pump unit and a main control unit. The temperature acquisition unit is at least arranged in the double-electric-drive bridge; the heat management loop comprises a cooling liquid storage unit, a water pump unit, a three-way valve unit and a heat exchange unit, the heat exchange unit is at least partially arranged on the double-electric-drive bridge, and the water pump unit is arranged between the cooling liquid storage unit and the three-way valve unit; the heat pump unit is in thermal communication with the heat exchange unit and is used for transferring heat of the double-electric-drive axle to an in-vehicle air conditioning system or a power battery under a preset condition; the main control unit is electrically connected with the above units and used for controlling the flow of the water pump unit and the opening degree of the three-way valve unit according to the oil temperature so as to adjust the flow of cooling liquid entering the heat exchange unit and / or controlling the output torque distribution ratio of the double-electric-drive bridge and / or controlling the working state of the heat pump unit. And the oil temperature of the double-electric-drive axle is maintained within the preset temperature range.

The invention relates to the technical field of ecological restoration, in particular to a photovoltaic power generation area ecological restoration dynamic optimization system and method and a computer readable storage medium, and the system comprises an ecological monitoring module which is used for collecting environment data in real time through a sensor network and monitoring equipment deployed in a photovoltaic area; the data analysis module is used for analyzing the collected data based on a big data processing technology and a machine learning algorithm, and establishing an ecological degradation evaluation model to quantify the ecological condition; the restoration scheme generation module is used for generating a restoration scheme including vegetation restoration, soil improvement and water resource management by combining the evaluation model result, the regional ecological environment characteristics and the restoration target and utilizing GIS analysis and remote sensing image processing technologies; the engineering measure management module is used for managing the implementation process of the ecological restoration engineering; and the biological measure management module is used for managing the implementation of biological remediation measures. According to the invention, collaborative management of engineering and biological measures is realized, and the ecological restoration efficiency is improved.

The embodiment of the invention discloses a method, device and equipment for determining the power generation efficiency of an offshore power plant and a medium, and relates to the technical field of power generation. The method comprises the following steps: acquiring a current environment parameter at a current moment, and determining an influence metric value corresponding to the current environment parameter; inputting the current environment parameter and the influence metric value into a pre-trained power generation grade classification model to obtain a power generation grade at the current moment; inputting the current environment parameter and the influence metric value into a pre-trained power generation efficiency prediction model to obtain a power generation efficiency actual value at the current moment; and fusing the power generation level and the power generation efficiency actual value to obtain a power generation efficiency fusion value of the power generation field at the current moment. In the technical scheme of the embodiment of the invention, the total power generation efficiency of wind power generation and photovoltaic power generation can be more accurately determined, so that the offshore power plant can more effectively dispatch and distribute power resources, energy waste is reduced, and the efficiency and reliability of energy supply are improved.

The present application relates to a kind of future and present fusion customer intelligent credit and credit risk management system and method, system includes multi-dimensional customer data acquisition and fusion module;AI dynamic credit scoring model: construct basic credit score, and introduce dynamic adjustment factor to the real-time correction of customer credit score, the comprehensive rating of the customer credit score after correction, early warning according to rating;Future and present comprehensive credit limit real-time management module;Intelligent overdue early warning and collection management module;Customer credit file and blacklist management module: for each customer signal file whole life cycle management, when customer appears set condition, execute blacklist linkage mechanism.The present application is by LightGBM dynamic risk adjustment layer, commodity price fluctuation rate, customer account change trend, associated enterprise risk and so on dynamic factor are included in credit score, risk customer is identified in advance about 30-45 days, and key time window is won for enterprise to take measures in advance.

The invention provides a coal industry engineering project safety management system and method. The system comprises a risk management and control module, a hidden danger checking module and a hidden danger treatment module. The risk management and control module is used for recording and displaying risk information of each risk item, receiving and recording a newly-added risk item input by a user when a first operation instruction input by the user is received as a risk item adding instruction, determining a risk level corresponding to the newly-added risk item, and obtaining risk information of the newly-added risk item; the hidden danger checking module is used for acquiring the risk information of all the risk items stored in the risk management and control module, and making and displaying a coal mine hidden danger checking plan based on the risk information of all the risk items; and the hidden danger treatment module is used for recording and displaying safety hidden danger information found in the execution process of the coal mine hidden danger investigation plan. According to the invention, accident potential in the coal mine production process can be effectively reduced, and the potential safety hazard checking efficiency is improved.

The embodiment of the invention provides a collaborative management method of an access network and a base station, and relates to the technical field of satellite communication, the collaborative management method is applied to a first base station in the access network, the first base station comprises a first DMC unit, a first CU and a first DU, the first DMC unit is connected with the first CU and the first DU, and the first DMC unit is connected with the first CU and the first DU. The method comprises: a first DMC unit obtaining a first signaling according to a working state of the first DMC unit in an access network, the first signaling being used for deciding resource configuration information of a first base station; and the first DMC unit sends the first signaling to the first CU and / or the first DU, so that the first CU and / or the first DU modify the resource configuration information according to the first signaling. By applying the technical scheme provided by the embodiment of the invention, the collaborative management requirements of the access network with the characteristics of high dynamic change of network topology, high transmission delay and the like can be met.

The invention discloses a data center user information dynamic management system based on a distributed architecture. The system comprises a distributed architecture layer, a core function module layer and a data interaction layer, the distributed architecture layer provides distributed computing, storage and communication support for the system. According to the method, tasks are processed in parallel through the distributed computing node cluster, and requests are dynamically distributed in a load balancing manner, so that the problems of low processing efficiency and response lag under the condition of sharp increase of equipment and data volume are solved; based on distributed storage fragmentation storage and redundant backup, the single-point fault risk of concentrated data storage is avoided, and stable operation of the system is guaranteed; cross-regional data real-time synchronization is realized by means of a distributed message queue, and unified management and control of multi-regional data centers are supported; and meanwhile, asset full life cycle traceability is realized through a block chain, the fault early warning accuracy is improved through an LSTM model, energy consumption is optimized through multi-dimensional accounting and an algorithm, and the efficient, safe and energy-saving management requirements of a modern data center are comprehensively met.

The invention relates to the technical field of heat pump systems, in particular to a whole vehicle heat management method based on an injection type air supply enthalpy increasing heat pump. A traditional air-supplementing enthalpy-increasing heat pump system is complex in structure and cannot carry out effective and controllable heat exchange with various vehicle-mounted functional parts in a whole vehicle heat management system. In order to solve the problem, the invention provides the whole vehicle thermal management method based on the injection type air supply and enthalpy increase heat pump, and a stable air supply and enthalpy increase loop is constructed in a heat pump system. And the medium-pressure gaseous refrigerant in the gas-liquid separator continuously performs enthalpy increasing and gas supplementing on the compressor. Meanwhile, a heat pump system is deeply coupled with a whole vehicle heat management system, the temperature states of vehicle-mounted functional components such as an electric drive module, a battery module and a cabin module can be collected in real time through a central integration module formed by a heat management controller and a temperature sensor, and heat is dynamically distributed according to actual requirements.

The invention discloses an electric vehicle modularized disc type permanent magnet synchronous motor cooperative control method and system, and the method comprises the steps: obtaining the total demand torque of a system, obtaining the efficiency in different operation modes according to a given rotating speed and the total demand torque of the system, obtaining the highest operation efficiency mode, and obtaining the highest operation efficiency mode; and a corresponding total demand torque instruction value of each group in the mode; based on the given rotating speed and the total demand torque instruction value of each group, solving a torque distribution coefficient of the two motors in the corresponding single group through a particle swarm optimization algorithm so as to obtain respective torque instruction values of the two motors in the single group; calculating a given stator current torque component corresponding to the torque instruction value, and determining a given stator current excitation component with the minimum total loss based on the minimum power loss of a loss model; and enabling the actual stator current of the motor to follow the given value through current closed-loop control. Cooperative management of multiple motors can be achieved through double-layer cooperative management, stability and efficiency are improved, and meanwhile cost is reduced.

An offshore wind power energy storage configuration method belongs to the technical field of offshore wind power energy storage, and comprises the following steps: firstly building a wind power plant and an energy storage station and sharing hydrogen resources, calculating the energy storage capacity according to factors such as electric hydrogen production power, determining the capacity of energy storage equipment according to a power ratio, and obtaining an energy storage configuration ratio according to predicted power generation power; and finally, when the predicted power is not matched with the actual power, peak regulation and frequency modulation are carried out by an energy storage station, and hydrogen resource management energy is shared. According to the method, multiple factors are comprehensively considered, the energy storage demand is accurately calculated, and the energy storage and the wind power plant are optimized and coordinated through accurate prediction and effective control. The energy utilization efficiency is improved through hydrogen resource sharing, multiple energy storage and power generation modes are complementary, the capacity of the system for coping with complex working conditions is enhanced, and the stability, reliability and economical efficiency of the offshore wind power system are remarkably improved.

This invention relates to the field of electrical automation technology and discloses an electrical automation control system and method with artificial intelligence, including a control center, a data acquisition module, a data analysis module, a control execution module, and a user interface. By combining artificial intelligence technology with the electrical automation control system, this invention solves problems such as insufficient real-time adaptive capability, inadequate data utilization, poor fault prediction capability, and insufficient energy efficiency management in traditional systems. It significantly improves the intelligence level, fault prevention capability, and energy management effectiveness of the electrical automation control system, providing more efficient and intelligent solutions for equipment maintenance, production scheduling, and energy optimization.

The invention provides a demand response management method and device. The demand response management method comprises the steps of S1, receiving demand response data, wherein the demand response data comprises power consumption data, power supply data and user behavior data; s2, analyzing the demand response data, wherein the analysis comprises predicting the power demand, optimizing the power supply and evaluating the user behavior; the demand response management method and device provided by the invention are convenient to use, the demand response data are received and analyzed in real time, the power supply is optimized, and the efficiency and the stability of a power system are improved; effective management of the demand response data is realized, including data updating, data deletion and data backup; interconnection and intercommunication with a power dispatching system, a user terminal and other systems are realized, and the intelligent level of a power system is improved; and the security of the demand response data is protected, data leakage, tampering or loss is prevented, and safe and stable operation of the power system is ensured.

The invention relates to a rail transit material circulation system and method, a medium and electronic equipment. The system comprises a unified identification tagging and management module, an intelligent perception and data acquisition module, a material data center and intelligent analysis platform, and a traceability and collaboration and decision support application portal. The unified identification tagging and management module generates a unique identification code for each material in a material entry storage link; associating the static attributes with the static attributes of the materials; the intelligent sensing and data acquisition module is used for acquiring the static attribute of the material by scanning the unique identification code in each operation link of the material, and updating the state change data of the material in the material data center and the intelligent analysis platform; the material data center and the intelligent analysis platform are in communication connection with the intelligent sensing and data acquisition module; and the traceability, collaboration and decision support application portal is in communication connection with the material data center and the intelligent analysis platform. According to the invention, dynamic traceability and collaborative management of materials can be realized, and the advantages are obvious.