50results about How to "Guaranteed reasonable use" patented technology

The invention provides an integrated metadata management method and system based on data source expandability, and relates to the technical field of data sources, and the method comprises the steps: executing real-time detection on a plurality of heterogeneous data sources through a PF4J plug-in framework, collecting connection information, and establishing a dynamic connection pool; obtaining a table structure, a field attribute and an association relationship list, and assembling the table structure, the field attribute and the association relationship list into JSON format data; performing analysis and standardization processing on the data, and constructing an association degree calculation matrix; generating a standardized data structure description file; establishing a three-layer index directory, and detecting structure change and updating; and calculating a data table reference dependency relationship, and generating a DAG data flow path. According to the method, efficient integration and management of heterogeneous data sources are realized, and the metadata processing efficiency is improved.

The invention relates to the technical field of smart power grids, and discloses a distributed renewable energy source and energy storage cooperative scheduling system of Internet of Things data, comprising a data acquisition and monitoring module used for acquiring the running states of distributed energy sources and energy storage units through the Internet of Things technology; the energy supply and demand prediction module is used for predicting energy supply and load demand according to historical data, real-time data and meteorological information and generating basic data of a scheduling strategy; the collaborative scheduling strategy module formulates a collaborative scheduling scheme of the renewable energy and the energy storage unit based on energy supply and demand prediction, and adjusts the charging and discharging time of the energy storage unit; the double-layer optimization decision module is responsible for long-period energy storage planning and short-period real-time scheduling optimization; and the real-time monitoring and feedback module dynamically adjusts a scheduling strategy based on feedback data. According to the invention, through real-time monitoring, supply and demand prediction and cooperative scheduling of renewable energy sources and energy storage equipment, the system can optimize distribution and use of energy to the greatest extent, and energy waste is reduced.

The invention relates to the technical field of building engineering, and discloses a building robot space positioning method based on a BIM model, which comprises the following steps: S1, establishing the BIM model of a building, and in the construction process, integrating real-time sensor data of a building site, and dynamically updating the BIM model to reflect the real-time state of a construction environment; and S2, setting multiple reference points at the construction site, performing coordinate calibration on the reference points by using a total station or a GPS system, aligning a coordinate system of the BIM model with a coordinate system of an actual construction site, and matching a building structure in the BIM model with a building structure in an actual environment through the reference points. Through the fusion of detailed building geometric information and real-time sensor data in the BIM model, the system can realize high-precision space positioning, the pose of the robot is corrected in real time by using an extended Kalman filtering algorithm and a multi-source data fusion technology, and the operation efficiency and the construction precision are effectively improved.

The invention relates to a pollutant concentration diffusion simulation method based on grid optimization and self-regulation. The method comprises the following steps: carrying out basic grid division on a simulation area to obtain a basic grid; calculating a pollutant concentration field of the simulation area according to the spatial position and the pollutant concentration value of the monitoring station; generating a concentration distribution matrix according to the pollutant concentration field of the simulation area, and then dynamically adjusting the grid density of the basic grid; calculating the calculation complexity of each grid region by using the grid density of the adjusted basic grid, carrying out pollutant concentration calculation task allocation according to a cloud platform and a weighted polling algorithm, and forming a pollutant concentration distribution prediction result of the simulation region by a pollutant concentration prediction result of each grid; and dynamically adjusting a pollutant concentration distribution prediction result according to the Kalman filtering and the obtained real-time environment data to obtain a final pollutant concentration prediction value. By adopting the method, the precision and the real-time performance of pollution diffusion simulation can be improved.

The invention relates to the technical field of freight scheduling, in particular to a freight scheduling information management method and system and a storage medium. The method comprises the following steps that uncompleted order collection is carried out on a freight platform to obtain an uncompleted order set, and the uncompleted order set comprises a plurality of uncompleted orders; each uncompleted order at least comprises an order ID, order release time, target cargo attribute data, publisher identity data, a departure place, a destination, an order state identifier, an order transportation task schedule, cargo stacking attributes, predicted delivery time and cargo expected arrival time; and performing order state classification and marking on the uncompleted order set to obtain a classified order set. By optimizing the loading space utilization rate of the vehicle, the unloaded and half-loaded conditions of the vehicle can be reduced, so that the fuel consumption and the transportation cost are reduced.

The invention discloses an industrial Internet of Things edge computing unloading method and system based on a distributed deep neural network, and the method comprises the following steps: firstly, introducing a feature matrix of an attention mechanism optimization task, transmitting the optimized task features to a multi-layer deep neural network DNN, and generating an unloading decision set in parallel; allocating resources for each task; after the to-be-unloaded task is preliminarily selected, computing resources of the high-priority task are preferentially guaranteed in the resource allocation stage according to the priority and deadline of the task. For tasks with relatively large calculation amount or relatively high priorities, decision storage is performed by using a cache strategy to optimize unloading and resource allocation processes of subsequent similar tasks, so that efficient and low-delay task unloading in a large-scale and multi-task environment is realized. Meanwhile, a distributed cache updating mechanism is utilized in each unloading time slot, the unloading decision precision is continuously optimized, and the unloading efficiency and the overall stability of the system are improved.

The invention relates to the technical field of intelligent agriculture, in particular to an irrigation area measurement and control integrated gate intelligent scheduling system and method, and the system comprises a data collection module, a gate control module, a data processing and analysis module, an intelligent scheduling module and a monitoring and early warning module. By integrating a water level sensor, a flow meter, a weather station data interface, a soil humidity sensor and an agricultural satellite data interface, various agricultural data and hydrological data in an irrigation area are collected in real time, and the crop growth condition, the water demand, the rainfall capacity, the evaporation capacity and the like are analyzed by utilizing historical data and models; therefore, an accurate irrigation scheduling strategy is formulated and executed in the intelligent scheduling module, water supply needed by crop growth is ensured, meanwhile, the system monitors agricultural data and hydrological data in an irrigation area in real time through the monitoring and early warning module, a reasonable threshold range is set, early warning can be triggered in time once an abnormal condition occurs, and the system is safe and reliable. And a reliable decision basis is provided for irrigation area management.

The invention discloses an intelligent operation and maintenance management system and method for a data center. The method comprises the following steps: acquiring a network topology structure, performance data, power supply data and equipment state data from the data center; dividing the network into a plurality of sub-regions according to the network topology structure, and performing network resource configuration according to the performance data and the power supply data of the plurality of sub-regions; performing fault prediction on the plurality of sub-regions by using a fault prediction model constructed based on a deep learning algorithm to obtain predicted fault sub-regions and predicted fault types; and according to the predicted fault sub-region and the predicted fault type, locating a predicted fault node, and carrying out early warning operation on the predicted fault node. The invention relates to the technical field of network operation and maintenance management, and solves the technical problems of insufficient fault pre-judgment capability and insufficient intelligence and automation degree in an existing network operation and maintenance management system.

The invention relates to an Internet of Things equipment deployment and control management method, in particular to a building Internet of Things equipment deployment and control management method. Comprising the following steps: deploying various sensors including an infrared sensor, a camera and an air quality sensor in a building, and collecting personnel flow and environment change data in real time; through data analysis and scene classification, the data are converted into scenes including office peaks, night modes and emergency evacuation of the building; training a scene recognition model by using a random forest classifier; a time sequence prediction model is adopted to predict scene change in a future short period, and a corresponding equipment control instruction is generated; the method comprises the following steps: establishing an incidence matrix of use frequency, spatial position and function interaction between devices by using sensor data, and identifying a device cooperation mode; dynamically generating an equipment deployment scheme through a graph theory algorithm based on the incidence matrix; issuing the generated deployment scheme to each equipment control node; and performing fine adjustment according to real-time data feedback.

The invention relates to the field of sweet potato planting, and particularly discloses a sweet potato three-dimensional planting device and a planting method.The sweet potato three-dimensional planting device comprises a planting bag which is 60 cm in depth, 40 cm in length and 40 cm in width and used for containing soil and sweet potato plants; the inner space of the planting bag is divided into an upper layer and a lower layer, four sweet potato seedlings can be cut in each layer, and three-dimensional planting is achieved. Water eliminating holes are formed in the bottoms of the planting bags and used for draining water to prevent water from accumulating at the roots of the sweet potatoes; the drip irrigation device comprises a drip irrigation tape cloth tape; by means of the unique planting bag design, efficient space utilization and three-dimensional planting are achieved, more sweet potato seedlings can be planted in the limited space, the planting efficiency of the unit area is improved accordingly, the drip irrigation device conducts precise irrigation, fertilization and pesticide application through the drip irrigation belt cloth belt, reasonable utilization of water and fertilizer resources is ensured, and the economic benefit is increased. And the waste of resources is reduced.

The invention discloses an AI project management optimization system based on artificial intelligence, and relates to the technical field of project management, and the system comprises a project optimization module, a quality evaluation module, a character analysis module, a project characteristic analysis module and a personality matching module, and also comprises a completion degree division module and a reward adjustment module. The system has the advantages that the scheme can be modified through the project characteristic analysis module in combination with project directions skilled by different character traits, reasonable distribution of project tasks is realized according to the character traits of employees, the working efficiency is improved, the character traits lacked in the traits distribution scheme can be better analyzed by utilizing the project characteristic analysis module, and the project distribution efficiency is improved. According to the scheme, the most suitable employees are distributed for the project, the personality advantages of the employees are fully exerted, the personality matching module analyzes the execution time of different sub-project schemes and marks the matched employees, the employees are prevented from being repeatedly marked, and reasonable utilization of human resources is ensured.

The invention relates to the technical field of information management, in particular to a material digital management system and method based on a cloud platform. The method comprises the following steps: acquiring material data; distributing a material storage space by using the material data; receiving an operation message of the storage space, and pushing the operation message to an inventory database; creating a circulation record table and an inventory state table; using the operation message in the inventory database to update a circulation record table, and recording circulation data; automatically updating an inventory state table according to the circulation data so as to determine the material inventory capacity; when the material inventory capacity is lower than or equal to a preset safety inventory threshold value, management early warning information is generated; and when the material inventory capacity is higher than a preset safety inventory threshold value, updating the management safety field of the inventory state table. The material inventory is monitored in real time based on the information management technology, the replenishment information is intelligently generated, inventory dynamic management is achieved, and the material management efficiency is improved.

The present invention relates to the field of vacuum monitoring technology, and in particular to a vacuum preloading soil vacuum degree monitoring system and method, the monitoring system comprising: a plurality of acquisition modules, a plurality of vacuum degree sensors, a first comparison module generation module, a second comparison module, a marking module, a division module, a third comparison module and an adjustment module; obtaining the preloading data of each monitoring point in the target area, and determining whether the preloading conditions of each monitoring point meet the preset standards; analyzing the preloading data of each monitoring point, and classifying and marking each monitoring point according to the analysis results; dividing the target area into regions according to the classification and marking results, and determining the actual operation mode of each vacuum pump according to the regional division results. The present invention can effectively identify problems existing in the preloading process, timely adjust the operation mode of the vacuum pump, ensure the optimization of the preloading effect, improve the utilization rate of equipment such as vacuum pumps, and reduce resource waste.

The invention discloses a data acquisition and processing method of an intelligent measurement master station, which relates to the technical field of intelligent measurement, and comprises the following steps: dividing a data acquisition channel, and constructing a distributed architecture of the intelligent measurement master station; cluster processing and multilink load balancing master station deployment are carried out on a distributed architecture, dynamic channel resources deployed by the master station are allocated based on an asynchronous time division multiplexing technology, and master station deployment operation based on cluster processing and multilink load balancing is carried out. According to the invention, the intelligent measurement master station system can better adapt to a complex and changeable electric power environment, the data acquisition and processing efficiency is improved, and advantages are brought to the development and application of an intelligent electric power system.

This invention relates to the field of classifying rotating equipment in refining and chemical enterprises, and provides a method and apparatus for classifying rotating equipment in refining and chemical enterprises. The method includes: determining the severity score and single-point failure / non-single-point failure score of various failure consequence indicators for each rotating equipment in the refining and chemical enterprise; calculating the risk priority number of each rotating equipment based on the severity score, single-point failure / non-single-point failure score, and weight of each failure consequence indicator; and determining the risk level of each rotating equipment based on its risk priority number. This invention can improve the accuracy of rotating equipment risk levels and provide a scientific and reasonable basis for the classified management of rotating equipment in enterprises. It can also provide a reference for rotating equipment maintenance measures and the allocation of maintenance resources.

The invention relates to the technical field of drainage engineering, and discloses a water-drop well-drop structure of a canal branch convergence area, which comprises a well chamber, a partition plate is fixedly connected in the well chamber, a mounting plate is fixedly connected to the upper side of the exterior of the partition plate, a filter screen is detachably connected to the inner side of the mounting plate, and a plurality of buffer plates are mounted on the outer surface of the well chamber. A plurality of buffer blocks are fixedly connected to the outer surface of the buffer plate, two movable columns are rotatably connected to the top of the buffer plate, a fixed column is slidably connected to the outer surface of each movable column, a mounting cavity is formed in each fixed column, a tension spring is fixedly connected to the interior of each mounting cavity, and an anti-blocking assembly is mounted on the outer surface of the filter screen. By additionally arranging the buffer assembly, the speed and impact force of water flow can be effectively reduced, so that damage to river banks and water ecology is reduced, vegetation and biological habitats around a water area are protected, and the ecological balance of the water area is maintained.

The invention discloses a closed ship traveling wave energy power generation device and a using method thereof. The device comprises a buoy, a primary transmission rod system, a shell, a spring and pushing joint system, a secondary transmission gear shaft system, a power generation and electric energy storage system and a drying box. The shell is of a closed structure, the buoy is used for making contact with the water surface, and the top end of the buoy is provided with a spherical hinge to be connected with the primary transmission rod system. The primary transmission rod system penetrates through the shell wall of the shell through a middle spherical hinge, and the tail end of the primary transmission rod system is rigidly connected with a spherical gear; the secondary transmission gear shaft system is arranged in the shell in a sliding manner and is pushed by the spring and the pushing joint system to be meshed with the ball gear at the tail end of the primary transmission rod system; and the transmission gear shaft system is connected with a generator of the power generation and electric energy storage system to generate power. According to the device, the ship waves generated by coming ships in the channel are converted into stored green clean energy, meanwhile, the device generates a negative feedback effect on the coming ship waves, scouring of the ship waves to the channel quay wall is effectively reduced, and the channel quay wall is effectively protected.

The application discloses a Bcache dirty key based on cache optimization method and system, and belongs to the technical field of computer storage. The application establishes a dirty key cache linked list, synchronously inserts reference information into the linked list when the dirty key is inserted into a B-tree, and maintains according to an LRU strategy; according to the proportion of the total number of dirty keys and the capacity of the cache linked list, a full cache mode or a partial cache mode is dynamically switched; when the dirty key is searched, the cache linked list is preferentially traversed, and when a miss occurs or the partial cache mode is used, the B-tree full tree scanning is used. The application also contains adaptive memory management, graceful degradation and write-back batch optimization. By using the application, invalid traversal of the B-tree can be greatly reduced, write-back operation can be avoided to block business IO, the efficiency of dirty key searching and write-back can be significantly improved, and backward compatibility is maintained.

The present invention provides a method, device and network side equipment for processing video data, the method comprising: decoding and copying a low-resolution video stream to obtain a first low-resolution video stream and a second low-resolution video stream; performing resolution enhancement processing on the second low-resolution video stream to obtain a high-resolution video stream; performing tile division processing on the high-resolution video stream to obtain a plurality of high-resolution video tiles; using the first low-resolution video stream as the background layer of a panoramic video, using the high-resolution video tile as the enhancement layer of the panoramic video, and splicing to generate a panoramic video stream; in an embodiment of the present invention, a panoramic video acquisition terminal uploads the low-resolution video stream to a network side equipment, and the network side equipment uses a video resolution enhancement technology to perform video resolution enhancement processing on the network side equipment, and cooperates with the tile division transmission technology, so as to obtain a relatively high-resolution panoramic video, thereby ensuring the reasonable use of uplink bandwidth and downlink bandwidth.

The present invention belongs to the field of medical technology, and discloses a sample processing method, device, sample analyzer and storage medium. The method includes: determining the sample monitoring information of the test sample rack on the current sample introduction basket; determining the injection status of each test sample on the test sample rack according to the sample monitoring information of the test sample rack; when the injection status of each test sample on the test sample rack is a preset completion status, the test sample rack is de-racked according to the retreat area. Through the above method, the overall monitoring of the test process is realized, the user can understand the change process of the sample in the sample analyzer in real time, provide a monitoring means for the user, and can timely de-rack the sample rack after the test is completed, ensuring the rational use of resources and improving work efficiency.

The embodiment of the invention provides a regulation and control method based on a port supply chain platform, and the method comprises the steps: obtaining the real-time meteorological data of a port, and predicting the influence range and duration of severe weather according to the meteorological data; based on the predicted severe weather information, adjusting the priority order of the cargos in the port; a cargo scheduling plan is dynamically updated through a port supply chain platform so as to reduce cargo retention and delay; and a port inventory management strategy is optimized, and reasonable utilization and quick response of the warehouse during severe weather are ensured. Through the scheme of the embodiment of the invention, the problem of inventory management and scheduling conflict caused by cargo retention and delay under the influence of severe weather can be solved.

The invention discloses a new energy station digital attack and defense environment simulation method and device, relates to the salinity gradient energy station technology field, introduces a digital simulation method to realize comprehensive monitoring and analysis of ocean dynamics and climate conditions, and provides abundant data support for managers. The data not only help to identify the change trend of the power generation efficiency, but also provides a scientific basis for the decision-making process. A manager can make a more reasonable decision based on a data analysis result, and an alarm mechanism can respond to the conditions of environment change and equipment performance reduction in time. Through monitoring and identification of potential risks, the system can rapidly take measures when the power generation efficiency is reduced, equipment faults or extreme climate changes occur, and managers can reasonably allocate equipment and personnel through analysis of the power generation efficiency and requirements of different areas, so that unnecessary operation cost is avoided. And effective resource configuration improves the working efficiency.

The invention relates to a hydropower station maintenance planning method based on a deep learning algorithm, and the method comprises the steps: collecting historical operation data, historical fault data, maintenance record data and environmental factor data of hydropower station equipment, and constructing a data set; establishing an equipment state evaluation model by using a deep learning algorithm; and analyzing the spatial distribution and mutual influence relationship of the maintenance equipment, optimizing the maintenance sequence and path by using a deep learning algorithm model, and dynamically adjusting the maintenance plan and formulating the maintenance layout plan of the equipment of the hydropower station through distribution and scheduling of maintenance resources in combination with the real-time state and external condition change of the equipment.

The present invention relates to the technical field of industrial robots, and in particular to a production control and adjustment method based on multi-control mode switching of industrial robots, comprising the following steps: S1, demand analysis and environmental monitoring: analyzing the demand of the production line, and monitoring the production situation data in real time through sensors; S2, mode switching based on situational awareness: applying situational awareness algorithms to analyze the current production status; S3, dynamic task scheduling optimization: automatically adjusting task allocation according to real-time data and task priority, and optimizing robot resource allocation; S4, feedback mechanism and effect evaluation: establishing a real-time feedback mechanism, monitoring the effects of mode switching and task allocation, and evaluating the effectiveness of mode switching by analyzing robot operation data. The present invention ensures the maximization of production efficiency and the rational use of resources, reduces the risk of overload and production delays, and improves the overall flexibility and responsiveness of the system.

The invention discloses a control method of an alternating current and direct current compatible low-voltage electric appliance, which relates to the technical field of control of low-voltage electric appliances and comprises the following steps of: dividing circuits of the low-voltage electric appliance and establishing a circuit set; establishing a three-dimensional image according to the circuit set, performing load resource allocation simulation on the three-dimensional image, and obtaining first data of the circuit; according to the first data of the circuit, carrying out necessity category classification on the circuit, wherein the necessity category comprises a necessary circuit and an unnecessary circuit; establishing a resource allocation priority evaluation model based on machine learning according to the first data of the circuit, and obtaining a resource allocation coefficient; and controlling a circuit of the low-voltage electric appliance according to the necessity category, the resource allocation coefficient and a preset electric appliance operation mode so as to control the low-voltage electric appliance. Therefore, reasonable utilization of electric power resources is ensured, benefits of electric appliances are maximized, and the problem that low-voltage electric appliances need more energy consumption or the functions of the electric appliances are limited is solved.

The invention provides a charging pile abnormal electricity utilization identification method and related equipment, and the method comprises the steps: carrying out the identification based on an obtained time sequence of the electricity utilization power of a charging pile, and obtaining a first charging event and a first idle state; performing clustering processing on the first charging event to obtain a clustering result; in response to the obtained second charging event, calculating a first distance between the second charging event and a clustering center in the clustering result, and identifying the second charging event according to the first distance; determining a normal distribution condition of the first idle state; and identifying the obtained second idle state according to the normal distribution condition. According to the embodiment of the invention, the charging events and the idle state are identified by adopting the difference method, the charging events of the charging piles are clustered, the electric power distribution rule of the idle state of the charging piles is statistically analyzed, and the abnormity is identified by adopting the standard score method or the box plot according to the result of whether the electric power data obeys the normal distribution or not. The false alarm rate and the missing report rate are effectively reduced, and the recognition accuracy is improved.

The application discloses a low-altitude economy cloud platform service packaging and dynamic combination charging system and method, relates to the technical field of low-altitude economy service management and charging, and comprises the following steps: a service packaging module encapsulates low-altitude core capabilities into standardized APIs and generates documents; a service arrangement module combines services through a visual interface, intelligently analyzes dependencies and provides fault-tolerant compensation; a multi-dimensional charging module collects multi-dimensional resource consumption data and generates detailed account bills; an open gateway and service market module provides unified access and service subscription management; a resource adaptation layer integrates basic capabilities and adapts to heterogeneous devices; a developer ecological support module provides whole-process development and profit sharing support; and a system operation and maintenance module guarantees stable operation and elastic scaling of the platform. The application reduces the development threshold through standardized packaging, accelerates application innovation through visual arrangement, and improves resource utilization efficiency through multi-dimensional charging; the application has high stability and adaptability, and realizes efficient operation and large-scale development of low-altitude economy services.

The present invention relates to a method and system for comprehensive management of rainwater in a sponge city, wherein the method comprises: obtaining the real-time rainfall in the current area and uploading the real-time rainfall to a cloud platform; obtaining the water level of an initial water reservoir, establishing a water level control model according to the initial water reservoir water level and the real-time rainfall, and calculating the output of a PID controller using a proportional-integral-differential (PID) controller algorithm according to the water level control model, and then adjusting the operating rate of a pump and valve in the water reservoir according to the output of the PID controller; obtaining water quality indicators and uploading the water quality indicators to a cloud platform; analyzing the water quality indicators, and generating an over-standard warning when the water quality indicators exceed a preset threshold; and upon receiving the over-standard warning, sending an instruction to close the corresponding pumps and valves in the water reservoir, the clear water tank, and the reuse pipe. The problem of low management and utilization of rainwater resources in sponge cities is solved. The present invention has the effect of realizing efficient management and utilization of rainwater resources.

This application belongs to the fields of big data and fintech, and is applied to the field of batch processing of insurance policy fees. It relates to a task batch processing method, apparatus, computer equipment, and storage medium, including receiving a batch processing request; obtaining a configuration file; identifying unused configuration text segments in the current batch processing; optimizing and adjusting the batch processing task logic; deploying the optimized and adjusted task logic and configuration file to several batch processing systems; processing fee change information in segments; parsing each piece of fee change information, and using the parsing results as method execution parameters to execute the batch processing task. This application optimizes and adjusts the task logic through configuration files and uses a modulo method to process all fee change information in segments, ensuring that each fee change information is distributed to its corresponding batch processing system. This optimizes task batch processing, improves batch processing efficiency, ensures reasonable utilization of server resources, and avoids system crashes caused by batch processing events.

The invention provides an urban street lamp bird-friendly design planning method and system, and the method comprises the steps: obtaining the bird collection data of each monitored street lamp based on a shooting device, determining to-be-screened street lamps meeting a friendly site selection condition according to the bird collection data, receiving a preset planning number inputted by a management end, and carrying out the screening of the to-be-screened street lamps. Determining a positioning planning mode according to a comparison result of the screening number of the to-be-screened street lamps and the preset planning number, obtaining a planning path corresponding to the to-be-screened street lamps according to the positioning planning mode, determining a plurality of planning points on the planning path, determining planned street lamps in the planning path according to the planning points, and screening the to-be-screened street lamps according to the planned street lamps. And obtaining inspection data of shooting the structure of the planned street lamp by a shooting device based on the monitoring route, determining a structure state corresponding to the structure according to the inspection data, and sending the structure state to a management end, so that street lamp planning of artificial nesting can be performed in combination with the actual inhabitation condition of birds.