2721results about How to "Improve transportation efficiency" patented technology

The invention discloses a logistics park vehicle path planning method and system, and the method comprises the steps: obtaining the real-time position and task state information of a vehicle in a park, dynamically constructing a vehicle path planning network model, dividing a road into nodes and edges, and forming a directed weighted graph; according to the directed weighted graph, an improved multi-lane algorithm is adopted, the path length, the congestion degree and the vehicle characteristic factors are comprehensively considered, and the optimal path of each vehicle is calculated; for the optimal path, introducing a virtual lane and a time dimension, pre-judging occupation conditions of multiple vehicles on the virtual lane for each time slice, and constructing a conflict constraint matrix; obtaining park high-precision map data, extracting road network topology, lane lines and traffic sign marking elements, performing lane-level refinement on the optimal path, and generating a driving track; and through a multi-sensor fusion positioning technology, obtaining high-precision position and attitude information of the vehicle, matching the high-precision position and attitude information with the driving track, and calculating a track tracking error.

The invention discloses an elevator control system based on artificial intelligence, which belongs to the technical field of elevator control, and comprises a plurality of layers of architectures such as data acquisition, transmission, processing, intelligent decision, execution control and the like. The data acquisition layer collects multi-source data through a car inside and outside and operation state sensor group; the data processing layer provides support for intelligent decision-making through preprocessing, analysis mining and model training optimization. An elevator dispatching module of the intelligent decision-making layer carries out peak dynamic zoning and flat peak energy-saving dispatching according to information such as passenger flow; the safety protection module monitors and processes hidden dangers in real time; the personalized service module provides customized services based on passenger behaviors and demands. And driving of the control layer, a door machine and a car environment control system are executed, and stable lifting of the car, safe operation of a door and intelligent environment adjustment are achieved correspondingly. Experiments show that the system can remarkably improve the elevator operation efficiency, safety and passenger satisfaction and reduce energy consumption, and has important application value.

The invention relates to the field of data visualization, in particular to a visualization method and system based on a vehicle service supply chain. The method comprises the following steps: acquiring whole-process information of a vehicle service supply chain; carrying out supply chain main body identification on the whole flow information of the vehicle service supply chain, carrying out spatial topology distribution analysis, and constructing a supply chain main body topology distribution map; obtaining supply chain main body interaction logic data based on the plurality of supply chain main bodies; performing topology interaction logic connection on the supply chain main body topology distribution graph by utilizing supply chain main body interaction logic data, and constructing a supply chain topology interaction network; performing intra-period path transportation frequency calculation on the whole-process information of the vehicle service supply chain to generate logistics demand trend characteristics; and performing operation behavior analysis of each link on the whole-process information of the vehicle service supply chain to obtain the capacity characteristics of each link. According to the invention, through visualizing the vehicle service supply chain, the resource scheduling efficiency and flexibility of the supply chain are improved.

The invention discloses a container tracking management system and method. The method comprises the following steps: S1, carrying out dynamic encryption binding and multi-dimensional data acquisition on an RFID chip; s2, realizing real-time position data acquisition of the container under different environmental conditions through a multi-source signal fusion and error correction algorithm; s3, various sensor modules are installed inside and outside the container, and data processing is carried out through distributed edge nodes; s4, performing on-chain storage on total data generated in the transportation process through a Hash encryption algorithm, and realizing automatic data verification, state tracking and abnormity alarm in combination with an intelligent contract; s5, carrying out real-time dynamic modeling analysis on the transportation path and resource allocation, and dynamically adjusting the transportation plan by using a distributed scheduling strategy; and S6, integrating the real-time state data, the path optimization model and the transportation scheduling decision, and providing a report for a user. The method has the advantages of high positioning precision, high data security, high transportation efficiency and good real-time performance.

The invention relates to the technical field of path planning, in particular to an intelligent transportation path planning method based on deep learning, which comprises the following steps: constructing a joint network model based on a convolutional neural network and a long short-term memory network, and training the joint network model by using historical traffic data; in the current transportation task, the real-time traffic data of the non-driving road sections in the current path are analyzed based on the joint network model, and the traffic change trend of each non-driving road section at the next moment is predicted; if the undriven road section of the current path has the sudden traffic event, or one or more undriven road sections in the current path are predicted to have traffic jam at the next moment, re-planning the path; and when the path is re-planned, dynamically optimizing the current path through the reinforcement learning model under the constraint of the multi-objective optimization function. According to the method, the accuracy of the future traffic condition can be improved, and the adaptive optimization of the transportation path can be realized.

The invention relates to the field of construction planning visualization, in particular to a construction planning visualization method and system for a refuse transfer station. The method comprises the following steps: acquiring a satellite positioning map and a refuse transfer station design drawing of a to-be-developed area; image detail reconstruction is carried out on the satellite positioning map, road space distribution fitting is carried out, and a regional road distribution network is constructed; performing surrounding building positioning calculation on the detail optimization reconstruction satellite image based on a regional road distribution network, performing an optimal site selection decision, and extracting an optimal address region image; carrying out transfer station key feature point identification on the refuse transfer station design drawing, then carrying out three-dimensional point cloud modeling, and constructing a transfer station three-dimensional structure model; and according to the optimal address area image, carrying out corresponding foundation accurate matching on the transfer station three-dimensional structure model, carrying out spatial positioning mapping, and constructing a transfer station address twinborn model. According to the method, the operation efficiency of the transfer station is improved, and the rationality of building planning is enhanced.

The invention discloses an unmanned aerial vehicle full-coverage path planning method, system and device and a storage medium, and relates to the field of unmanned aerial vehicles. The method comprises the following steps: acquiring preset map information of a first target area, and determining a second target area for delivering materials according to the preset map information; determining a relay unmanned aerial vehicle set according to the data information, a preset starting point, a second target area, preset map information, a first communication distance of the first unmanned aerial vehicle and a second communication distance of the relay unmanned aerial vehicle, and determining a second initial path of the second unmanned aerial vehicle according to the first initial path; controlling the first unmanned aerial vehicle and the second unmanned aerial vehicle to fly according to a preset initial path, and adjusting the preset initial path according to the environmental data collected by the first unmanned aerial vehicle; and when the first unmanned aerial vehicle arrives at a preset terminal point, determining flight paths of other unmanned aerial vehicles according to the actual load weights and types of the other unmanned aerial vehicles in the transportation unmanned aerial vehicle group and the environment data. By implementing the technical scheme provided by the invention, the task execution efficiency of the unmanned aerial vehicle group is improved.

The invention discloses a tea garden soil improvement method based on microbial communities. The tea garden soil improvement method aims at improving soil fertility and tea tree yield by means of precisely screening beneficial microorganisms, optimizing culture conditions and the like. Firstly, soil samples are collected from a tea garden area, gene high-throughput sequencing is carried out, soil microbial community composition information is obtained, and beneficial microorganisms are screened out. Then, the breeding speed and biomass of the beneficial microorganisms are optimized by adjusting a culture medium formula. When the bio-fertilizer is prepared, besides concentrated bacterial liquid, an organic carrier, inorganic nutrient elements and humic acid serving as a stabilizer are also added, and a proper amount of trace elements and a plant growth regulator are added. In spring or autumn, according to the physicochemical property of the soil, the bio-fertilizer is uniformly spread and ploughed into the soil layer. After fertilization, soil physicochemical properties and tea tree growth conditions are regularly detected to evaluate the soil improvement effect and adjust the fertilization strategy according to the soil improvement effect. The method is beneficial for improving the tea garden soil health condition and improving the tea yield and quality.

The H-shaped steel post-process production line comprises a temporary storage station, an assembly station, a transfer system, a welding station and a cleaning and grinding system, H-shaped steel is taken out from the temporary storage station, transported to the assembly station through the transfer system, assembled and spliced manually, and transported to the welding station through the transfer system after being spliced; the whole production line is controlled in a coordinated mode through a production line master controller, signal exchange between the transfer conveying device and all the stations is achieved, automatic feeding and discharging of the components are completed, the conveying efficiency is improved, the safety of the production line is improved, and the production line is suitable for machining large-batch open type H-shaped steel beams. The production flow of the whole process is stable, the consistency of products is improved, and the requirement of dynamic production line assembly on the professional skill level of workers is reduced; welding workers are replaced by robot welding, the requirement for station workers is low, and meanwhile the cleaning and grinding workload is greatly reduced.

The invention relates to the technical field of cold-chain logistics, in particular to an intelligent scheduling method and system for cold-chain transportation, and the method comprises the steps: achieving the precise scheduling and matching of vehicles and resources according to the information and resource integration of transportation vehicles; carrying out vehicle transportation path planning according to the determined target order; formulating an emergency response mechanism based on the real-time health state of the transport vehicle; according to the invention, through integration of transport vehicle information and resource data, optimization matching is carried out by using an intelligent calling algorithm, and accurate scheduling of vehicles and resources is realized. The resource waste and the unnecessary transportation cost are effectively avoided, and the improvement of the transportation efficiency is ensured; particle swarm optimization is adopted for path planning, and two-step operation of preliminary path generation and dynamic path optimization is combined, so that high efficiency and reliability in the cold chain transportation process are ensured; on the basis of real-time monitoring and historical data, potential faults of vehicles and equipment can be recognized in advance, and quick response can be achieved when abnormity occurs.

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 present invention provides a multimodal transport method for emergency materials based on emergency scenarios, which determines the key nodes of materials and effective transportation information according to the current emergency scenario information, constructs the current emergency material joint transport network, determines the transportation priority corresponding to the material demand point, obtains the material demand corresponding to the material demand point and the transportation capacity information of the current emergency material joint transport network, sets constraints, initializes multiple transport paths according to the constraints, and then determines the objective function, updates the transport path using a damage repair algorithm to obtain a new transport path, and re-determines the objective function, iterates and updates the preset number of times to reach the preset stop condition, and obtains the final objective function. The optimal transport path corresponding to the final objective function is a multimodal transport plan that transports emergency materials from the material supply point to the material demand point via the material transfer point. The present application can achieve the joint transportation of emergency materials in a shorter time and at a lower cost.

The invention, which relates to the technical field of coal mine transportation scheduling, discloses a coal mine intelligent transportation scheduling optimization system comprising a map construction module, a data acquisition module, a communication module, a monitoring module, an intelligent scheduling module, an emergency processing module and a man-machine interaction module. The system has the advantages that the operation states of coal mine collection equipment and transportation equipment are monitored in real time through the equipment monitoring unit and the environment monitoring unit, the environment state of a mining area is comprehensively monitored, equipment abnormity and environment risks can be found and early warned in time, safety accidents are prevented, and the system is safe and reliable. The service life prediction unit can predict the residual service life of the equipment by monitoring and analyzing the operation time and the accumulated workload of the equipment, and gives out early warning when the equipment is close to the end point of the service life, so that potential safety hazards caused by equipment aging are avoided, and the safety of coal mine transportation is improved.

The invention relates to the technical field of solid waste sorting scheduling, in particular to a real-time monitoring optimization method and device for a solid waste collection, transportation and sorting ERP system. The method comprises the following steps: obtaining a real-time solid waste sorting log based on a solid waste collection, transportation and sorting ERP system; solid waste carrying vehicle tracking is carried out on the real-time solid waste sorting log, and a carrying track distribution visual view is constructed; acquiring an omnibearing monitoring image of a real-time sorting site; equipment sorting behavior visual identification is carried out on the real-time sorting site omnibearing monitoring image, dynamic sorting evolution is carried out, and a dynamic sorting twinborn model is constructed; carrying out multi-time-point solid waste sorting simulation on the dynamic sorting twinborn model, carrying out sorting load demand prediction, and generating a sorting load demand prediction value; and carrying out vehicle load calculation on the sorting load demand prediction value one by one, and then carrying out dynamic vehicle scheduling decision making to obtain a dynamic vehicle scheduling strategy. According to the invention, efficient and real-time solid waste sorting scheduling optimization is realized.

The invention discloses an energy-saving reciprocating type telescopic mechanical arm pallet fork elevator, and relates to the technical field of elevators. The device comprises a lifting assembly, a telescopic mechanical arm pallet fork assembly is fixedly installed on the front face of the lifting assembly, the telescopic mechanical arm pallet fork assembly comprises a mounting plate, the mounting plate is fixedly installed on the lifting assembly, four sliding rails are welded to the front face of the mounting plate, and lifting sliding blocks are slidably connected to the interiors of the four sliding rails; and rotating shafts are rotationally installed between the two sets of lifting sliding blocks on the same side, first inserting rods are fixedly installed on the rotating shafts, and second inserting rods are hinged to the bottoms of the first inserting rods. Displacement of the first inserting rod in the vertical direction is converted into displacement of the second inserting rod in the horizontal direction, the pallet fork elevator has enough vertical space, but the horizontal space is limited by the size of the pallet fork elevator, under the condition that the equipment size is not increased, the pallet fork distance can be greatly increased, conveyors in butt joint with each floor are reduced, and the labor intensity of workers is reduced. The lifting cost is reduced.

The invention provides a conveying platform for internal parts of a compact fusion reactor and a using method of the conveying platform, and belongs to the field of transportation of the internal parts of the fusion reactor. Vacuum outdoor transportation parts of the conveying platform comprise a supporting steel frame assembly, a transportation track assembly, a transportation trolley assembly and a mobile crane assembly, and the supporting steel frame assembly comprises a cage-shaped steel frame; one section of the transportation track assembly is straightly installed in the building channel, the other sections of the transportation track assembly are straightly located in the cage-shaped steel frame and extend to a window in the vacuum chamber, and the movable crane assembly and the transportation trolley are sequentially located on the transportation track assembly. The cable-stayed hanger rail component comprises cable-stayed rods, a bearing steel beam and an annular hanger rail, the cable-stayed rods are installed at the upper end of the regular polygon-shaped frame in an annular array mode, one end of each cable-stayed rod is connected with the upper window collar of the vacuum chamber, and the other end of each cable-stayed rod is connected with the bearing steel beam of the frame. According to the invention, after internal parts on the equatorial plane of the vacuum chamber are quickly conveyed, the internal parts can be conveyed through simple adjustment.

The invention relates to the technical field of inter-city cargo splicing and loading, in particular to an inter-city cargo splicing and loading transportation path optimization algorithm based on large model optimization, and solves the problems that in the prior art, an optimization algorithm based on a large model generally relates to a complex calculation process and needs a large amount of calculation resources and time, and especially in a real-time path planning scene, the calculation process is complicated. And the calculation delay can influence the transportation efficiency. The invention discloses an inter-city cargo splicing transportation path optimization algorithm based on large model optimization. The algorithm comprises data collection and preprocessing, model construction and training, algorithm optimization and verification, path optimization calculation, result evaluation and feedback, and algorithm deployment and application. According to the method, various possible transportation paths are analyzed and compared through an algorithm, the optimal path is selected, unnecessary detour and waiting time is reduced, so that the transportation efficiency is improved, and the algorithm can perform intelligent scheduling and reasonable arrangement of transportation vehicles and routes according to real-time traffic conditions, cargo demands, vehicle states and other information.

The invention relates to the field of allocation, and discloses a spare part allocation method for multiple warehouses, and the method comprises the steps: obtaining spare part inventory information and historical spare part delivery data of each warehouse in a plurality of warehouses; analyzing the stock quantity corresponding to each spare part model to obtain an out-of-stock spare part model of each warehouse, and determining the warehouse corresponding to the out-of-stock spare part model as a spare part receiving warehouse; according to the historical spare part ex-warehouse data and spare part inventory information of each warehouse, a spare part allocation list is determined; sending the spare part allocation list to a plurality of auditing terminal devices; after checking of the spare part allocation list is completed, allocation delivery information corresponding to the spare part allocation list is generated, and the allocation delivery information corresponding to the spare part allocation list is sent to a delivery terminal device corresponding to a target spare part delivery warehouse; and monitoring the allocation and transportation information, and if it is monitored that the allocation and transportation information is received, generating allocation and receiving information of the spare part allocation list. Therefore, multi-warehouse spare part allocation is realized.

The invention discloses a multi-locomotive path planning method and system based on a Q-learning algorithm, and relates to the technical field of iron-steel interface locomotive path planning, and the method comprises the steps: obtaining environment data, building a transportation system environment model, and defining states and actions; performing path optimization on the vehicle path through a Q-learning algorithm to obtain an initial path plan; and the central control system receives the key information in real time, and dynamically adjusts vehicle path planning in real time through a Q-learning algorithm. According to the method, through learning and optimization of the Q-learning algorithm, the central control system can find the shortest path, the transportation time and distance are reduced, and the transportation efficiency is improved; the path planning is dynamically adjusted through the central control system, so that the congestion and conflicts of track routes are avoided, and the smoothness of the transportation process is ensured; by using the Q-learning algorithm, the method can adapt to a dynamically changing environment, and normal operation of the system can be ensured even if an accident occurs.

The invention relates to a scraper conveyor with a coal quantity monitoring function, and relates to the technical field of coal mining machinery, the scraper conveyor comprises a rack, a driving assembly, a monitoring assembly and a flattening assembly, the rack is rotatably connected with a plurality of rotating rollers, the plurality of rotating rollers are uniformly arranged in the conveying direction of the rack, and the plurality of rotating rollers are jointly sleeved with a conveying belt; the driving assembly is arranged on the rack and used for driving the conveying belt to rotate. The monitoring assembly is arranged on the rack and used for monitoring the height and gradient of a coal pile. The flattening assembly is arranged on the rack, located on the side, away from the input end of the rack, of the monitoring assembly and used for reducing the height of the coal pile. The method has the effect of improving the transportation efficiency.

The invention discloses a liquefied oil product flow management method based on the Internet of Things technology, and the method comprises the following steps: installing a high-precision flowmeter at a key node of a liquefied oil product pipeline, monitoring the flow data in real time, and collecting the historical data; local processing and analysis are carried out on real-time and historical data by using a multi-source domain antagonistic transfer learning algorithm, and the processed data are transmitted to an Internet of Things platform through a self-adaptive multi-hop wireless sensor network. And storing and processing the data through space-time self-correlation analysis, and identifying a space-time mode and abnormal change. And real-time monitoring and prediction are performed in combination with a mixed event triggering prediction control algorithm. A multivariable time sequence decomposition and reconstruction algorithm is utilized to deeply analyze flow data, and a multi-kernel learning algorithm is combined to optimize a flow prediction model, extract key features, identify abnormities and optimize transportation and storage strategies of liquefied oil products. According to the invention, real-time monitoring, automatic management, data fusion and analysis and abnormal early warning of flow data are realized.

The invention belongs to the technical field of lithium ion batteries, and discloses an amidated polyacrylic acid water-based polymer binder for a silicon-based negative electrode of a lithium ion battery and a preparation method and application of the amidated polyacrylic acid water-based polymer binder for the silicon-based negative electrode of the lithium ion battery. The preparation method comprises the following steps: under a protective atmosphere, sequentially adding 1-ethyl-(3-dimethylaminopropyl) carbodiimide hydrochloride, N-hydroxysuccinimide and levodopa, stirring to fully react, carrying out dialysis freeze-drying treatment to obtain a primary product PL, and uniformly mixing the PL with glycerol to obtain the product. According to the binder, a dynamic bond is successfully introduced, the transportation efficiency of lithium ions is improved, a three-dimensional network structure is constructed, adverse stress generated by volume expansion of a SiOx negative electrode material in the charging and discharging process of an electrode can be effectively inhibited, and the SiOx negative electrode shows good cycling stability.

The invention relates to the technical field of medicine cold chains, in particular to a medicine cold chain aging optimization method and system based on a neural network, and the method comprises the steps: collecting and recording historical temperature data of medicine in a transportation process, collecting historical data of a medicine state, a transportation route and a traffic condition, and building a cold chain data set in combination with the historical temperature data; preprocessing the data in the cold chain data set, establishing a neural network model, and training the neural network model by using the preprocessed training set data; according to the method, related data of cold-chain logistics are collected, the related data comprise historical temperature data, medicine states, transportation routes, traffic conditions and the like, a neural network model is established by using historical data, the neural network model is trained, a real-time monitoring system is established, and the cold-chain logistics process is monitored in real time. And monitoring data is fed back to the neural network model, and a transportation plan and a transportation route are adjusted in time through real-time monitoring and feedback so as to deal with emergencies and optimize logistics timeliness.

The invention relates to an acid barrel automatic transportation method, system and equipment and a medium, and belongs to the technical field of intelligent acid barrel automatic transportation. The method comprises the steps of obtaining acid barrel transportation environment information, obtaining the acid barrel transportation information through a data acquisition mechanism, and obtaining an optimal acid barrel transportation path and an acid barrel transportation task allocation strategy through an acid barrel transportation path dynamic planning model according to the acid barrel transportation environment information and workshop position information, and obtaining an unmanned acid barrel transportation device through the acid barrel transportation task collaborative scheduling model according to the acid barrel transportation task allocation strategy, and automatically transporting the acid barrels through the acid barrel automatic transportation model according to the unmanned acid barrel transportation device. The automatic collaborative transportation of the acid barrels is realized, and the transportation safety and the transportation efficiency are improved.

The invention discloses a mobile platform coal quality remote detection system and method, and solves the problem that the analysis precision and analysis efficiency of a model are affected by a spectral data acquisition error rate due to the fact that parameters of pulverized coal cannot be preprocessed when a model between a spectral line and a calorific value is established and a coefficient matrix and an error term of the model are obtained in an existing method. The method comprises the following steps: detecting stored coal in real time by adopting mobile coal quality detection equipment, pre-constructing a data processing model based on the combination of adaptive interactive multiple models and deep learning, preprocessing spectral sample data by the data processing model, and establishing a coal quality index quantitative model based on the combination of a convolutional neural network and a lightweight detection structure; according to the method, noise reduction, normalization and feature extraction preprocessing are performed on the real-time spectral data by pre-constructing the data processing model based on the combination of the adaptive interactive multiple models and deep learning, so that the spectral data acquisition error rate is reduced, and the analysis precision and analysis efficiency of the coal quality index quantitative model are ensured.

The invention provides a train cooperative operation prediction control method and system based on a dynamic interval model, and belongs to the technical field of train operation control, and the method comprises the steps: calculating a train minimum tracking interval based on the real-time estimation state information of a train according to a train relative distance braking model; the communication delay time of the train-to-train communication system is considered, an additional safety margin is added on the basis of the minimum tracking interval of the train, and the influence of communication delay on cooperative operation control of the train is compensated; a system state space model is constructed based on the safety margin, and a train optimization control problem is formed based on the control constraint and the control target; and solving a train optimization control problem, obtaining an acceleration sequence for controlling train operation, and acting a first item of the sequence on the train to realize train operation control. According to the invention, while the tracking interval between the trains is effectively reduced, the influence of communication delay on the train operation is compensated by adding the additional safety margin, so that the train operation safety is improved, and the line transportation efficiency is improved.

The invention belongs to the technical field of rail transit automatic driving, and particularly relates to a shunting locomotive ATO high-precision alignment parking control system and method. The control system comprises a fusion positioning module, a laser ranging module, a speed control module and a distance compensation module. The fusion positioning module carries out high-precision fusion positioning according to the precise longitude and latitude, the line transponder position information, the real-time speed and the wheel cycle pulse number, and provides precise position information for the speed control module in combination with an electronic map; the laser ranging module receives a laser ranging distance on a coupled and propelled molten iron tank car or a railway wagon in real time through vehicle-to-vehicle communication; the speed control module calls a speed control algorithm to perform traction and brake control on the locomotive according to the accurate position information provided by the fusion positioning module and the distance information provided by the laser ranging module; and the distance compensation module realizes distance fine adjustment after accurate parking. The invention provides a shunting locomotive ATO high-precision alignment parking control system and method.

The invention relates to the technical field of logistics management and control of cloud computing, and particularly discloses a remote logistics management method and system based on cloud big data management and control, and the method comprises the steps: obtaining multi-source data in a logistics transportation process in real time through a data collection module, including the information of road conditions, weather, warehouse states and the like; the real-time data and historical data are compared and analyzed through a data comparison and analysis module, and the optimal logistics transportation path is determined; monitoring the real-time data based on the selected path through a path risk assessment module, assessing the risk existing in the current logistics transportation, and dividing the risk into a high risk or a low risk according to the assessment result; different countermeasures are taken according to the risk levels, that is, the current transportation process continues to be executed for low-risk paths, and for high-risk paths, risk factors are analyzed, and alternative schemes are implemented; according to the invention, functions of real-time data acquisition, intelligent path planning and dynamic risk assessment are integrated, and efficient management of logistics transportation is realized.

The invention relates to the technical field of battery management, in particular to an unmanned aerial vehicle carrying platform battery management method and system, and the method comprises the steps: adjusting the charging power of a battery pack through a dynamic power adjustment type charging management algorithm; determining the charging demand and strategy of the battery according to the demand of the flight task; by implementing a quick charging technology, the charging time is shortened, and the flight efficiency of the unmanned aerial vehicle is improved; excessive charging and discharging are avoided by setting proper charging and discharging cut-off voltage. The vehicle-mounted unmanned aerial vehicle cluster system has the beneficial effects that through a vehicle-mounted unmanned aerial vehicle cluster scheme, the transportation efficiency of electric power materials in remote mountain regions is effectively improved, and meanwhile, comprehensive life guarantee and work support are provided for working field personnel. In addition, according to the technology, the energy supply process is optimized, and through a dynamic power regulation type charging management algorithm and a rapid charging technology, the charging efficiency of the battery is remarkably improved, and the service life of the battery is remarkably prolonged. And meanwhile, through advanced data acquisition and remote control capabilities, the accuracy and safety of operation are enhanced.

The invention discloses an operation method and system for distributed organic solid waste centralized treatment and quality improvement and application, and relates to the field of chemical engineering, the operation method comprises the following steps: respectively carrying out pyrolysis treatment on organic solid waste distributed in different areas to obtain combustible gas and solid combustible materials and / or pyrolysis oil, using the combustible gas as fuel for pyrolysis treatment, and using the solid combustible materials and / or pyrolysis oil for pyrolysis treatment; the solid combustible comprises carbon powder and / or pyrolysis residues; concentrating and gasifying the solid combustibles and / or pyrolytic oil obtained in different areas to obtain mixed gas, dedusting the mixed gas, and converting the dedusted mixed gas by using water vapor to obtain a hydrogen crude product; purifying the hydrogen crude product to obtain a hydrogen product; packaging, storing or conveying the hydrogen product; the method solves the problem that large-scale industrial treatment and economic benefit improvement are difficult to realize due to the fact that the organic solid waste in a distributed area or a remote area has the characteristics of multiple types, small quantity, dispersive distribution, high transportation, recovery and treatment cost and the like.