66 results about "Logistics park" patented technology

The invention relates to the technical field of logistics park management, and particularly discloses a logistics park intelligent early warning and dynamic evaluation method, and the method comprises the steps: carrying out the time-space alignment of vehicle trajectory data, cargo pressure distribution data and environment data collected by a heterogeneous sensor network, and inputting the data into a dynamic threshold adjustment module to generate a self-adaptive warning threshold; the dynamic threshold adjustment module establishes a dynamic calculation model containing the equipment utilization rate and the vehicle density based on the matching relationship between the historical operation mode and the real-time operation state; based on a multi-dimensional evaluation system constructed based on a self-adaptive warning threshold, generating a comprehensive evaluation index through collaborative analysis of three groups of indexes including transportation efficiency, safety risk and resource utilization; and when the comprehensive evaluation index deviates from the preset range, triggering a grading early warning mechanism associated with the deviation degree. According to the invention, dynamic evaluation and intelligent early warning are realized, and real-time monitoring and intelligent evaluation regulation and control of the operation state of the logistics park are realized through space-time correlation analysis and an adaptive decision-making mechanism of multi-source heterogeneous data.

The invention provides a low-altitude logistics distribution method and system based on an electromagnetic launching unmanned aerial vehicle technology, and the method comprises the steps: installing a modular electromagnetic launching system in a designated region of a first logistics park; the unmanned aerial vehicle is connected with the modular electromagnetic emission system, and cargo loading and parameter calibration are carried out; dynamically planning a flight route of the unmanned aerial vehicle from the first logistics park to the second logistics park; the electromagnetic emission system is started to accelerate the unmanned aerial vehicle, and the pulse power modulation technology is utilized to control the output of specific pulse power in different stages, so that the unmanned aerial vehicle reaches a specified take-off speed within a preset distance range; the unmanned aerial vehicle autonomously flies along the flight route and autonomously performs obstacle avoidance and path correction, and the flight route or task sequence of the unmanned aerial vehicle is dynamically adjusted; and deploying a modular catapult stopping system in the second logistics park to complete stopping of the unmanned aerial vehicle. According to the invention, the acceleration efficiency can be improved to ensure that the unmanned aerial vehicle keeps a safe distance from the obstacle while keeping the distribution efficiency.

The invention discloses an unmanned vehicle cluster cooperative distribution method and system for an intelligent logistics park, and relates to the technical field of logistics distribution cooperative control, and the method comprises the steps: carrying out the pre-judgment of an emergency prediction model based on the real-time logistics monitoring data of the intelligent logistics park, and obtaining a first prediction emergency; generating an initial collaborative delivery strategy group in combination with the target delivery order and the vehicle cluster state information; and introducing a flexible confrontation index to evaluate the initial collaborative distribution strategy group, optimizing the initial collaborative distribution strategy group through a difference value between the initial collaborative distribution strategy group and a preset flexible confrontation index, and outputting a first collaborative distribution strategy group. The technical problems that in the prior art, path planning is poor in adaptability to emergencies and unpredictable events and slow in response, so that the overall distribution efficiency of an unmanned vehicle cluster is reduced, and the operation reliability is insufficient are solved. The technical effects of dynamically enhancing the anti-interference capability and the adaptability of the unmanned vehicle cluster collaborative distribution strategy through predictive evaluation and flexible optimization, and improving the overall distribution efficiency and the operation reliability are achieved.

The invention discloses a port-adjacent logistics park planning and design method and system, and belongs to the technical field of port logistics planning and engineering informationization, and the method comprises the steps: generating a plurality of sets of port-adjacent logistics park parameterized plane models, and outputting m sets of park planning and design schemes and corresponding unit parameter data sets; calculating the annual workload and the average stockpiling day number of different types of goods, and outputting a goods quantity statistical result; calculating sub-item cost and engineering cost of each plane unit, and calculating other cost and reserve cost of engineering construction so as to obtain and output total investment of the engineering; calculating the sub-item incomes of the storage unit and the storage yard unit, and correcting the sub-item incomes according to the comprehensive influence factors to obtain the expected income of each set of planning and design scheme; and determining the planning design scheme with the minimum cost-to-benefit ratio as an optimal scheme. According to the method, layout generation, cargo volume prediction, cost calculation and income comparison and selection can be completed at the same time in the planning stage, and the problems that traditional planning design is low in efficiency and lacks economical linkage analysis are effectively solved.

The invention discloses a comprehensive logistics management method and system based on an AI algorithm and big data analysis, and relates to the technical field of intelligent logistics management.The system comprises the steps that sensing terminals are deployed at key nodes of an e-commerce logistics park, and resources, equipment and path data are collected and summarized into a multi-dimensional data set; constructing and training a multilayer neural network model, extracting task scheduling and equipment state features, and realizing scheduling analysis and strategy prediction; calculating a resource scheduling adaptation coefficient and comparing the resource scheduling adaptation coefficient with a threshold value to judge a scheduling state; aGV operation stability is monitored, and a state fluctuation coefficient is calculated; identifying an abnormal operation behavior and calculating an abnormal behavior coefficient; finally, multiple evaluation results are fed back to the AI model, model parameters are dynamically optimized, and the scheduling intelligence and stability of the system are improved.

The invention discloses an intelligent scheduling method and system for a wind-light-hydrogen storage integrated logistics park, and relates to the technical field of computers, a data collaboration system is constructed, multi-dimensional data alignment is executed, and a hydrogen production prediction function is calculated by using an inference model; calculating a dynamic hydrogenation admission threshold based on the pressure feedback and the logistics demand change; according to the predicted hydrogen production trend of the prediction function, predicting whether the generated power of the power system is in a crest period or a trough period, limiting hydrogenation in the trough period in combination with a threshold value, and guiding the vehicle to supplement energy in the crest period, so as to cope with hydrogen production demand mismatch caused by fluctuation of wind and light resources, and change post-management into prospective regulation and control to reduce potential safety hazards. Energy supply is guaranteed, and an energy storage strategy is optimized.

The overall design is compact, making it suitable for applications requiring rapid deployment and with significant space constraints, particularly in logistics parks and lithium battery fires. Users can connect and activate the device in a short time, providing a foam fire extinguishing system that enables more efficient response to fires. [Solution] The system comprises a machine box and a water pump, a peristaltic pump, a foam concentrate tank, and an air compressor located inside the machine box. The foam concentrate tank and peristaltic pump are connected to the input terminals of the water pump via piping, and the air compressor is connected to the output terminal of the water pump via piping. In addition, a water supply pipeline is installed parallel to the foam concentrate tank at the input terminal of the water pump, and the output terminal of the water pump is connected to an external fire hose. The foam concentrate tank and peristaltic pump are positioned horizontally opposite each other on the same side of the water pump, and the air compressor is positioned horizontally opposite each other on the opposite side of the water pump. This clarifies the water supply and drainage layout of the entire system and facilitates the independent removal and maintenance of each component module.

The application relates to a logistics park multi-capability complementary system management and control method and a service platform. The method comprises the following steps: using a particle swarm optimization algorithm to perform population search iteration on multiple device configuration particle individuals to generate multiple first configuration particle individuals; using a target solver to perform daily operation scheduling planning solving on all particles of the first configuration particle individuals to generate corresponding daily scheduling response data, and calculating corresponding configuration fitness based on scheduling fitness of the daily scheduling response data and a target function associated with the first configuration particle individuals; based on the configuration fitness, repeatedly performing the steps of generating corresponding first configuration particle individuals and daily scheduling response data until multiple second configuration particle individuals meeting preset fitness defined configuration fitness are obtained; using a TOPSIS method to select a target device configuration particle individual from the multiple second configuration particle individuals, and using the target solver to solve target scheduling response data to obtain a corresponding optimization result.

The invention is suitable for the technical field of logistics queuing, and provides a coal logistics park weighing vehicle queuing and calling method and system based on artificial intelligence, and the method comprises the following steps: creating a coal electronic waybill; establishing an electronic fence of the coal logistics park, and judging whether a transport vehicle enters the electronic fence based on GIS and GPS technologies; acquiring a vehicle image, identifying and analyzing the vehicle image to obtain vehicle features, matching the vehicle features with the vehicle information, and determining a corresponding coal electronic waybill; issuing the coal electronic waybill to a corresponding user terminal App, and generating a popup window to be signed in; and receiving a sign-in instruction, enabling the coal electronic waybills with successful sign-in to enter a weighing and queuing mode, and determining a queuing scheme of the coal electronic waybills according to the type of transported coal, the transportation time efficiency, the state of the weighing equipment in each weight house and the existing queuing condition of each weight house. According to the method, the optimal queuing scheme is generated by analyzing the coal type, the time efficiency, the equipment state and the queuing flow, and the queuing waiting time is shortened.

The invention relates to the technical field of automatic driving and intelligent robots, in particular to a detection and online mapping integrated sensing method in a logistics park scene, which comprises the following steps of: acquiring images and point cloud data by adopting vehicles in a logistics park, and converting the images and the point cloud data into a global coordinate system; detecting the converted image data by using a deep neural network detector, wherein information that a target is static or dynamic is recorded in a target detection result; the real-time SLAM module obtains an environment map; adding the target detection result into an environment map, and establishing an information enhancement map; updating the optimization graph of the real-time SLAM module based on the information enhancement map; updating the target detection result based on prior semantic information; path planning and automatic driving are carried out based on the information enhancement map and the target detection result; the real-time performance, the precision and the reliability of the sensing system can be improved.

The invention provides an intelligent logistics park and storage decision-making method and system, and relates to the technical field of logistics warehousing, and the method comprises the steps: monitoring the position of a transportation mechanism in real time, taking the transportation mechanism as a conflict node when detecting that a plurality of transportation mechanisms share the same goods shelf node, and determining an execution priority based on a time margin; according to the method, the time margin is calculated, the extra waiting time cost and the diversion decision time cost are calculated respectively, finally, the execution sequence and strategy are dynamically decided according to the comparison result of the time margin and the time cost, collaborative scheduling and global optimization at conflicting nodes are achieved, and the logistics efficiency and order delivery timeliness are improved.

The invention provides an underground container logistics loading and unloading system based on a deep underground passage. The underground container logistics loading and unloading system comprises an automatic container wharf, a logistics park and the deep underground passage. The automatic container wharf is connected with the logistics park through the deep underground passage, and the deep underground passage internally comprises an area where shuttle vehicles run; and the deep underground passage comprises a main body layout area and accessory equipment. By applying the embodiment of the invention, through a vertical loading and unloading mode and an underground container logistics transportation mode, cargo transportation is realized, and transportation of ground container trucks is shunted to a certain extent, so that the ground transportation pressure of a port city is relieved, the transportation distance between the container wharf and the out-of-city logistics park is shortened.

The application discloses a kind of vehicle flow path planning method based on logistics park and surrounding road network double constraint, by constructing mathematical model, simultaneously consider the processing capacity limit of internal service node of logistics park and the traffic capacity limit of surrounding road network section and node, accurately present the interaction mechanism of both, solve the problem that prior art cannot accurately depict its complex relationship;Second, based on the solution algorithm, the model is solved, in the double-constrained environment of comprehensive and accurate, fully excavate path combination, quickly find the vehicle flow path scheme that meets the conditions and makes the optimal solution of transportation efficiency, cost and other targets, overcome the problem that optimal solution is difficult to obtain;In addition, the influence of different constraint conditions is analyzed in depth, the action mechanism of vehicle flow path is mastered, and the model and algorithm are optimized accordingly, and the planning scheme can be adjusted in real time according to the actual situation, so that the planning can follow the changes of actual demand, effectively make up for the defects that the prior art is difficult to dynamically optimize and adjust.

The invention discloses a multi-power compatible split direct current charger, belongs to the technical field of chargers, and aims to solve the problems of repeated design and long period caused by diverse requirements of different new energy heavy truck operation scenes on the power of the charger. The charger comprises an alternating-current power distribution unit, a power distribution unit, a control unit, a direct-current output unit, an indication unit and a heat dissipation unit, a symmetrical cabinet body design is adopted, and all the units are arranged in a partitioned mode according to functions. The core is that through specification combination of six-path or four-path AC power distribution modules, a 40kW / 50kW module tray design is compatible, and flexible switching of three-gear power is realized. The system is high in space utilization rate, can quickly respond to different power requirements, greatly reduces the design and production cost, is convenient to install and maintain, and is suitable for various scenes such as outdoor charging stations and port logistics parks.

The utility model discloses a logistics park carbon dioxide emission monitoring device, which relates to the technical field of logistics monitoring equipment and comprises a detection terminal, a connecting pipe communicated with the detection terminal, a filter handle and an air suction pipe communicated with the filter handle. The connecting pipe is communicated with the filtering handle through a deposition box, the upper end of the deposition box is provided with an air inlet pipe communicated with the filtering handle and an air outlet pipe communicated with the connecting pipe, and one side of the deposition box is provided with a drainage hole for drainage; through the arrangement of the deposition box, the drainage baffle discs and the condensation cover, when air filtered and heated by the filtering handle enters the deposition box through the air inlet pipe, the air is guided to be scattered by the drainage baffle discs and is in full contact with the condensation cover, so that the condensation cover is fully contacted with the air inlet pipe; and moisture in the air is condensed and gathered on the condensation cover, so that the removal effect on the moisture in the air is improved, and the air is drier.

The invention discloses a method and a system for intelligently counting loading and transporting vehicles, which are suitable for vehicle transportation management in complex environments such as logistics parks, forest farms, mine fields and the like. The method comprises the following steps: collecting a video stream of an operation area; vehicle detection and tracking are performed by using a deep learning model based on a YOLO architecture, and a detection frame is calculated to associate a target and maintain ID continuity; delimiting a core detection area, and recording coordinates and timestamps before and after a vehicle enters the area; calculating a motion vector based on the coordinate difference value, and judging whether the traffic direction meets an effective transportation requirement or not through a direction filtering mechanism; time continuity verification is adopted, an ID retention threshold value is set, and whether the vehicle completes area crossing within an allowed time interval or not is judged; when the direction and time conditions are simultaneously satisfied, it is determined that the transport is valid and counted. According to the method, the problems of false detection, missing detection and repeated counting caused by vehicle shielding, temporary parking and target loss in a complex environment are effectively solved, and the accuracy and reliability of vehicle statistical data are remarkably improved.

The application discloses a vehicle and unmanned aerial vehicle authentication method based on three factors and PUF, and comprises the following steps: S1, system initialization is completed by an edge server and a consortium chain network; S2, the unmanned aerial vehicle and the vehicle are registered respectively, and initial trust binding between the vehicle, the unmanned aerial vehicle and the edge server is completed; S3, in an online stage, the vehicle sends an access request to the edge server, the edge server sends authentication information to the unmanned aerial vehicle after verification, the unmanned aerial vehicle generates a response after verification, and a shared session key SK is obtained by negotiation between the vehicle and the unmanned aerial vehicle; and S4, after successful completion of authentication, the edge server calls an intelligent contract interface, and metadata of an authentication event is written into a consortium block chain. The application can realize two-way identity authentication and session key negotiation between the vehicle, the edge server and the unmanned aerial vehicle in a single-domain scenario of a low-altitude logistics park, and can guarantee multiple security attributes while controlling online authentication calculation overhead at a low level.

The invention relates to the technical field of concrete maintenance, in particular to a concrete maintenance device for building construction in a logistics park, which comprises a main body mechanism for building, and the main body mechanism is provided with a moving mechanism for moving and a maintenance mechanism for spraying a maintenance agent to a concrete wall; through motor driving, friction wheel transmission and the conical clamping block reversing assembly, the moving direction can be automatically and rapidly switched when an endpoint is encountered on the track module, and continuous reciprocating motion without manual intervention is achieved; the track module is formed by flexibly splicing the vertical track, the horizontal track and the turning track, and customized erection can be carried out according to the height, length and layout of the scaffold in actual construction; and the feeding pipeline is automatically closed during spraying to prevent pressure leakage, and the feeding pipeline is automatically opened to supplement new materials during return stroke, so that the stability of spraying pressure and the covering uniformity are ensured, and the waste of the curing agent is effectively avoided.

The application discloses a kind of logistics park storage intelligent lifting steel frame, including main steel frame, the goods shelf being arranged at one side of main steel frame, multiple supporting plates being fixed in the inside of goods shelf, lifting platform being liftable and being arranged in the inside of main steel frame;Pushing assembly is installed on the top of lifting platform;The logistics park storage intelligent lifting steel frame proposed in the present application effectively solves the problem that the height of pushing plate in traditional intelligent lifting steel frame is not adjustable by designing a L-shaped extension plate that can slide up and down, ensures that the goods can be smoothly pushed into the supporting plate in the steel frame, greatly improves the stability and reliability of storage operation, the height of the L-shaped extension plate can be flexibly adjusted according to actual use requirements, can meet the storage needs of logistics goods of different heights, whether it is a large packaging box or a high-rise cargo, can easily cope with, greatly improves the use flexibility and adaptability of the whole device, so that it can be applied in more extensive logistics scenarios.

This invention provides a method, apparatus, and equipment for diagnosing carbon emissions in logistics parks, relating to the field of carbon emission management technology. The method includes: acquiring vehicle OBD data, warehousing energy consumption data, park charging pile data, and cargo loading / unloading process data from the logistics park and inputting them into a carbon flow diagnosis model for the logistics park; obtaining the carbon emission amount for each spatiotemporal unit corresponding to the current input data to identify high-carbon nodes; during the training of the logistics park carbon flow diagnosis model, each preset spatial grid at each preset time step is treated as a spatiotemporal unit, and the historical actual carbon emission amount for each spatiotemporal unit is calculated based on historical input data according to transportation, warehousing, loading / unloading, park office, and other processes; and obtaining a spatial attention weight matrix and a temporal attention weight matrix based on the historical actual carbon emission amount of each spatiotemporal unit to train a spatiotemporal attention-based LSTM model. This invention can comprehensively track park carbon emissions and accurately locate high-carbon nodes.

The invention discloses a tray operation method, device and equipment of an unmanned forklift and a medium, and the method comprises the steps that when the unmanned forklift operates a target tray in a logistics park, identification information related to the target tray is acquired; measuring the speed information of the unmanned forklift in real time through an IMU (Inertial Measurement Unit); performing reverse compensation on the identification information based on the speed information to obtain attitude compensation identification information; inputting the attitude compensation identification information into a pre-trained neural network model, and predicting to obtain pose data of the target tray; and converting the pose data into a coordinate system of the unmanned forklift to obtain converted pose data, so that the unmanned forklift generates a corresponding control instruction based on the converted pose data, and completes the operation of the target tray through the control instruction.

The application relates to the technical field of route navigation, in particular to an intelligent logistics park unmanned logistics distribution vehicle route navigation method and system, which comprises the following steps: acquiring the current actual position, historical position and planned distribution route of an unmanned vehicle and signal labels; obtaining each signal monitoring group according to the distance distribution condition between the historical position of the unmanned vehicle and the signal labels and the straight-line distance between the signal labels and the planned distribution route; solving the suspected vehicle position according to the overlapping condition between the signal strength ranges of the signal labels in the signal monitoring group; analyzing the error distribution range according to the obstacle blocking degree of the signal labels in the signal monitoring group, and obtaining the current corrected position by combining the information credibility of the overlapping area between the error distribution ranges; and performing route navigation on the unmanned vehicle according to the current corrected position and the current actual position. The application makes the identification result of the current position of the unmanned vehicle more accurate, and thus more accurate navigation results can be obtained.

The utility model relates to the technical field of intelligent warehouses, and provides an electronic commerce logistics park intelligent warehouse which comprises four goods containing boxes, a rotating assembly, a discharging plate, a material pushing assembly and a material pushing plate, every two of the four goods containing boxes form a group, each group of goods containing boxes are fixedly installed in a goods shelf, the goods containing boxes are arranged to be U-shaped, and the rotating assembly is arranged on the rotating assembly. The number of the rotating assemblies is two, the two rotating assemblies are both fixedly installed on the side face of the goods shelf, the number of the discharging plates is four, every two discharging plates form one set, the two sets of discharging plates are arranged on the two rotating assemblies respectively, the two pushing assemblies are both arranged on the goods shelf, and the pushing plates are arranged on the pushing assemblies. By means of the technical scheme, the problem that in the prior art, when a robot is used for taking objects on a goods shelf, adjacent objects are likely to be touched, and therefore the positions of the objects are deviated is solved.

The application discloses a smart logistics park unmanned vehicle cluster cooperative distribution method and system, relates to the related technical field of logistics distribution cooperative control, and comprises the following steps: based on real-time logistics monitoring data of the smart logistics park, a first predicted emergency is obtained by using an emergency prediction model; an initial cooperative distribution strategy group is generated in combination with target distribution orders and vehicle cluster state information; a flexible confrontation index is introduced to evaluate the initial cooperative distribution strategy group, and the first cooperative distribution strategy group is output by optimizing the difference between the flexible confrontation index and a preset flexible confrontation index. The technical problems that the path planning in the prior art has poor adaptability to emergencies and unpredictable events, response is slow, the overall distribution efficiency of the unmanned vehicle cluster is reduced, and operation reliability is insufficient are solved, the anti-interference ability and adaptability of the cooperative distribution strategy of the unmanned vehicle cluster are dynamically enhanced through predictive evaluation and flexible optimization, and the overall distribution efficiency and operation reliability are improved.

The application provides a 3D modeling method and system based on a logistics park and warehouse materials, relates to the technical field of 3D modeling, and solves the technical problem of low warehouse data accuracy of warehouse materials in the logistics park. The method comprises the following steps: in response to a 3D modeling instruction for the materials, a drone in the logistics park sends a broadcast signal in the form of a broadcast; an electronic tag receives the broadcast signal and sends a feedback signal for the broadcast signal according to the to-be-modeled data; the feedback signal contains target warehouse data conforming to the to-be-modeled data and a material identifier of target materials corresponding to the electronic tag; a scanning device arranged on the drone scans all the electronic tags in the logistics park to receive the feedback signal; and a data processing system corresponding to the drone performs 3D modeling of the situation of each target material in the logistics park based on the target warehouse data in the feedback signal and the material identifier, to obtain a 3D model of the warehouse materials.

The invention relates to the technical field of logistics park management, in particular to a smart park safety and efficiency optimization system and method based on Internet of Things and AI, and the system comprises a vehicle access park module, a platform scheduling optimization module, a visitor management module, a perimeter safety module, an AI recognition analysis module, and a park energy consumption management module. According to the invention, the parking efficiency is improved and the waiting time is shortened by analyzing the information of vehicles and cargoes entering the park and dispatching platform allocation, and the cargo loading and unloading position is calculated by using the real-time vehicle position information, so that the residence time of the cargoes in the transfer process is shortened; according to the system, the behaviors of workers are monitored in real time, dangerous behaviors and incorrect equipment wearing personnel are recognized, the accident response speed and the safety management level are improved, the energy utilization rate is increased through facilities such as water and electricity energy consumption collection, and intelligent and green park construction is further promoted.

The invention relates to a logistics park parking space management method and device based on parking space efficiency identification, equipment and a medium, and the method comprises the steps: obtaining real-time multi-source heterogeneous data, recognizing the operation intention of each vehicle according to the multi-source heterogeneous data, and obtaining the loading or unloading operation type of each vehicle according to the operation intention; according to all the operation types of each vehicle, the throughput quantity, related to each parking space in the first preset time period, under the corresponding operation type is obtained; according to the obtained throughput quantity of each parking space under the corresponding operation type, the parking space efficiency of each parking space in a first preset time period in the park is obtained; and according to the operation type of the current vehicle and the parking stall efficiency data of all parking stalls in the park, carrying out adaptive personnel scheduling management including loading and unloading area categories and specific parking stalls under the determined loading and unloading categories on the current vehicle. According to the scheme provided by the invention, the use efficiency and the management level of the parking spaces in the logistics park can be effectively improved.

The invention relates to the technical field of unmanned aerial vehicles, in particular to a modular unmanned aerial vehicle take-off and landing platform adaptive to a logistics park, which comprises a storage module and a landing guide module, and the landing guide module is located at the top of the storage module; a plurality of sealed storage spaces are arranged in the storage module; a communication module for transmitting data is arranged on the storage module; the landing guiding module comprises a visual identification image and a light assembly. Multi-supplier unmanned aerial vehicle compatibility is realized through visual identification images and a modular storage framework, the capital construction cost and space occupation are reduced, the distribution overall planning efficiency is improved by means of two-way communication with a logistics park management system, the complex environment adaptability and operation safety are enhanced by means of environmental perception, and meanwhile, flexible expansion can be realized through framework splicing, so that the system can be widely applied to the logistics park management system. And multi-model and high-frequency unmanned aerial vehicle tail end distribution requirements of logistics parks of different scales can be met.

1. The name of the design product: the graphical user interface of the automatic loading monitoring of the electronic device in the logistics park train. 2. The use of the design product: for an electronic device. 3. The design points of the design product: the content of the graphical user interface. 4. The picture or photo that best shows the design points: front view. 5. The rest is the usual design, omitting the rear view, left view, right view, top view, and bottom view. 6. The use of the graphical user interface: for displaying and controlling the loading auxiliary equipment and the automatic loading monitoring of the multifunctional logistics park train. 7. The human-computer interaction mode of the graphical user interface: the front view is the product homepage; clicking the "system device control" in the front view will get the interface change state diagram. 8. The part covered by the black block is the content picture.

The invention discloses a logistics park platform intelligent management and control method and system based on edge collaboration, and relates to the technical field of park platform management. The method comprises the steps that a target warehouse is provided with a plurality of goods storage areas and a plurality of platforms, and a distance matrix of the goods storage areas and the platforms is established; acquiring vehicle position information and operation demand information of the plurality of transport vehicles in real time, and predicting and acquiring arrival time of the plurality of vehicles according to the vehicle position information of the plurality of transport vehicles; generating an initial vehicle platform matching scheme according to the distance matrix and the operation demand information, and performing conflict detection on the initial vehicle platform matching scheme based on the arrival time of the plurality of vehicles to obtain a conflict detection result; and when the conflicting vehicle platform pair exists in the conflict detection result, optimizing the initial vehicle platform matching scheme according to the distance matrix, generating an optimized vehicle platform matching scheme, and performing logistics park platform management and control. The scheduling precision and the resource utilization efficiency are effectively improved.