110 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 relates to the technical field of unmanned management, and particularly discloses an unmanned weight house management method and system for a coal logistics park, and the method comprises the steps: creating a coal transportation task, and synchronously determining the standard parameters of the coal transportation task; the logistics park is detected in real time, when vehicle information is detected, the vehicle information is identified based on the standard parameters, and guidance information is generated according to an identification result; after the vehicle arrives at the weighing area, a weighing instruction is generated, weighing data are obtained based on weighing equipment, and an electronic scale bill is generated; weighing information in the weighing process is monitored in real time, the weighing information is identified, an abnormal condition is determined, and when the abnormal condition exists, an early warning signal is generated and sent to a management end. According to the invention, the labor cost is low, the efficiency of the weight house weighing process is high, the consumption and workload of human resources are greatly reduced, multiple types of data can be integrated through multi-modal large model license plate recognition, and the accuracy and robustness of vehicle recognition are high.

The present invention relates to the technical field of intelligent manufacturing equipment industry, and more specifically to an intelligent scheduling method, system and storage medium for road-rail intermodal containers, including: obtaining historical environmental data of containers from a memory, preprocessing the historical environmental data, establishing a machine learning model, obtaining internal environmental data, calculating the length of time that materials in the container can be stored, prioritizing all containers, and arranging the stacking positions of containers in the road-rail intermodal logistics park yard based on the priority of the containers; selecting a genetic algorithm framework, creating a scheduling plan for the container, and taking different control measures for the container crane when the container crane executes the scheduling plan to prevent collisions between the container cranes. The present invention can complete the handling of the container before the materials in the container reach the critical conditions for storage.

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.

A global path planning method for a pure electric automatic driving commercial vehicle in a logistics park scene is characterized by comprising the following steps: step 1, acquiring a high-definition map of a target logistics park, and preprocessing the high-definition map into a topological map; 2, calculating the arc length, curvature and gradient between any two adjacent points on the topological map; 3, calculating energy consumption / recovery of the vehicle between two adjacent points on the topological map according to the vehicle longitudinal dynamic model; 4, calculating the running time of the vehicle between two adjacent points on the topological map; 5, constructing a comprehensive weight algorithm of energy consumption and efficiency between two adjacent points on the topological map; 6, calculating the weight of each path on the topological map according to a comprehensive weight algorithm; 7, constructing a cost function by adopting an A * algorithm; 8, constructing a heuristic function according to the characteristics of the topological map; and 9, searching an optimal global path of the vehicle by adopting an improved A * algorithm according to the position information of the starting point and the ending point of the vehicle on the topological map.

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 a logistics park distribution service method. The method comprises the following steps: constructing a path initial solution; acquiring a closed loop around the logistics center; a minimum vehicle type service method is adopted to obtain a plurality of path initial solutions which take the logistics center as a starting point, pass through at least one service site and return to the starting point, and the service sites are adjacent in the sequence of the closed loop; carrying out boxing design on each path initial solution to obtain a path intermediate solution; when boxing is feasible, outputting the path intermediate solution; when encasement fails, increasing the vehicle type for encasement design until encasement is feasible, and outputting the path intermediate solution; if boxing is still failed when the maximum vehicle type is reached, the service place where boxing is failed is removed, the path intermediate solution is output, and the removed service place independently sets the distributed path initial solution; and optimizing the path intermediate solution by adopting a self-adaptive large neighborhood search algorithm in combination with a simulated annealing algorithm to obtain a final path solution. The vehicle distribution and loading efficiency is improved, and the distribution cost is reduced.

The invention relates to the technical field of logistics park management, in particular to a logistics park vehicle tracking and flow counting method and device, equipment and a storage medium. The logistics park vehicle tracking and flow counting method comprises the following steps: obtaining image data of logistics park vehicles, and carrying out labeling and preprocessing to obtain an image data set; constructing a basic model based on a NanoDet network model, improving the basic model by adopting a data enhancement method to obtain a preliminary model, and training the preliminary model by adopting an image data set to obtain a vehicle tracking calculation model; a vehicle tracking calculation model is adopted, and vehicle position and vehicle type information is generated according to the real-time image data; and adopting a target tracking algorithm, generating a driving track of the vehicle according to the vehicle position and the vehicle type information, and carrying out statistics on the vehicles in the logistics park. According to the invention, vehicles in the park can be tracked and recorded in real time, so that the vehicles are effectively scheduled, and the operation efficiency of the park is ensured.

The invention provides a 3D digital virtual logistics scene simulation method and apparatus, and an electronic device, relates to the technical field of virtual scene simulation, and solves the technical problem of low processing efficiency of material state data of materials stored in a logistics park. The method comprises the following steps: controlling an unmanned aerial vehicle to set electronic tags on entity materials entering a logistics park; wherein a gyroscope and a positioning device are arranged in the electronic tag; the logistics park corresponds to a 3D digital virtual logistics scene, and the 3D digital virtual logistics scene comprises a virtual material model corresponding to the entity material; detecting motion data of the entity material through a gyroscope, and detecting position data of the entity material through a positioning device; according to the motion data and the position data, determining a motion track of the entity material in the logistics park; and simulating the motion state of the entity material in the logistics park in the 3D digital virtual logistics scene through the virtual material model based on the motion trail.

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 present application relates to the field of intelligent monitoring technologies, and provides an intelligent monitoring method and system for a logistics park. The method includes: obtaining a floor plan of the logistics park, identifying key areas and arranging an intelligent sensing network; obtaining first monitoring data based on real-time monitoring by fixed edge nodes; obtaining area tasks and evaluating activities, and calculating a task complexity factor; adjusting dynamic nodes based on the complexity factor to obtain area activity data; inputting the activity data into a deep analysis model to obtain a logistics intelligent sensing set; inputting the sensing set and the complexity factor into a risk assessment function to perform multi-level early warning matching and feedback. The present application solves the technical problems of unreasonable resource allocation and untimely risk early warning caused by the difficulty in accurately monitoring the changing frequency of dynamic activities in the logistics park, and realizes the effect of efficiently monitoring and accurately warning by adjusting dynamic edge nodes in real time through an intelligent sensing network and combining multi-dimensional task complexity factors.

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 digital twinning, and particularly discloses a tobacco warehouse management method and system based on digital twinning, and the method comprises the steps: obtaining the building data of a logistics park, carrying out the three-dimensional modeling of the logistics park, and obtaining a park model; the method comprises the following steps: acquiring field data of a logistics park based on acquisition equipment, converting the field data into rendering numerical values, and inserting the rendering numerical values into a park model; receiving a browsing instruction input by a user, and visually displaying the park model based on the browsing instruction; and comparing the field data with a preset threshold value, and when the field data reaches the preset threshold value, reading and displaying a corresponding pop-up panel. According to the invention, the Unity 3D technology is adopted, data can be converted into visual and visible graphs in real time, a more visual observation and understanding mode is provided, the system can be operated on various devices, the applicability and flexibility of a digital twin system are improved, visual and friendly development tools and interfaces are provided, and development is facilitated.

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 utility model provides a battery swap station for an autonomous driving logistics vehicle, which includes a main body, a battery swap point is arranged on the side of the main body, and the vehicle body is close to the battery swap point; a battery swap working part is arranged at the battery swap point, and the battery swap working part faces the battery swap structure; a battery storage part is arranged on the side of the battery swap working part, and the battery storage part includes a placement rack; the battery swap working part includes a manipulator assembly and a track assembly, and the track assembly is arranged on the side of the placement rack, and the manipulator assembly can be movably arranged on the track assembly. The battery swap station for an autonomous driving logistics vehicle realizes the battery replacement of a large autonomous driving logistics vehicle with side battery swapping by using the manipulator assembly and the track assembly of the battery swap working part through the cooperation of the battery swap working part and the battery storage part, thereby ensuring that the large autonomous driving logistics vehicle can always be in working condition, improving the working efficiency of the autonomous driving logistics vehicle, and further improving the working efficiency of the entire logistics park.

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 a method and a system for calculating popularity indexes of coal plant purchase and downstream purchase. The method comprises the following steps: S101, a data acquisition module; s102, a data processing module; s103, an index calculation module; s104, designing a desensitization processing algorithm; and S105, an index release and analysis module. According to the method, the current market condition is reflected based on arithmetic averaging of the data of the near N days, the method has certain perspectiveness, and by introducing a fixed value for desensitization processing, sensitive business information is protected, and the universality and comparability of indexes are ensured. According to the method, the vehicle flow data of the coal logistics park is applied to market popularity evaluation for the first time, direct conversion from data to indexes is realized, and the blank of market popularity evaluation in the coal industry is filled. In addition, the method can be widely applied to upstream and downstream enterprises of the coal industry chain, financial institutions, government supervision departments and the like, and healthy and stable development of the coal market is promoted.

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 is suitable for the technical field of safety production management, and provides a coal logistics park production management and control system based on an operation video recognition technology, and the system comprises a video collection module which is used for obtaining a monitoring image related to a key region through monitoring equipment disposed in a park; the video processing and data analysis module is used for carrying out risk identification on the monitoring image by utilizing an intelligent video analysis technology; the control warning module is used for controlling early warning equipment arranged on the site to work based on the risk identification result; and the terminal display module is used for processing the risk identification result into display information and sending the display information to digital screen equipment. Through the control warning module and the terminal display module, real-time early warning control can be carried out, risks in the park can be displayed in a digital screen mode, and the production operation management and control efficiency and timeliness of the coal logistics park are improved.

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 invention discloses a logistics unmanned aerial vehicle. A logistics unmanned aerial vehicle comprises an unmanned aerial vehicle body, a logistics loading moving box is installed below the unmanned aerial vehicle body, a box body is arranged in the logistics loading moving box, expansion batteries are arranged on the two sides of the box body, even number of installation grooves are formed in the lower portion of the box body, even number of walking driving pieces are installed in the installation grooves, and a distribution box is installed at one end of the box body. And a concave equipment groove is formed between the mounting grooves. A walking driving part on a logistics loading moving box hung below the unmanned aerial vehicle triggers a second torsion driving part and a swing walking foot after the unmanned aerial vehicle returns to the connection position of a logistics park warehouse, folding driving wings of the unmanned aerial vehicle stop rotating, and the box body and the unmanned aerial vehicle above are driven to enter the logistics warehouse through assistance of the swing walking foot; therefore, setting of an open field in the park can be avoided, the logistics express does not need to be transported to the open field to be loaded, the unmanned aerial vehicle directly enters the logistics warehouse, and express loading work is directly completed in the warehouse.

A method for local mapping and navigation of a logistics cart in a park. The logistics cart uses a 16-line lidar as a perception processor, adopts lidar slam positioning technology, pre-establishes a high-precision map and a navigation vector map of the park, and uses the point cloud information collected in real time to determine the current pose of the logistics cart by using the NDT registration algorithm. Global path navigation planning is carried out according to the input destination and the current location, and a new type of local cost map is designed. The efficiency of logistics work is improved, and automation, intelligence, and unmanned operation of the logistics park are realized.

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 present invention relates to the technical field of logistics transportation, and specifically relates to a method and system for tracing the supply chain of a logistics park based on a BIM model. First, the present application preliminarily evaluates the degree of goods loss according to the relative loss of the quality of goods at the starting point and the ending point on different tracing transportation paths. Then, according to the performance of goods loss on the tracing transportation paths passing through each local section, the unreliability of each local section is evaluated; and the priority of path allocation is determined by combining the types of goods that can be compatibly transported in each local section, so as to overall evaluate the final selectability of the tracing transportation path including multiple local sections. Finally, the optimal supply chain path with higher accuracy and robustness is selected for transportation, so that the effect of supply chain tracing according to the optimal supply chain path is better.