Tower drum transportation scheduling system based on data analysis

Abstract

The invention discloses a tower drum transportation scheduling system based on data analysis, and particularly relates to the technical field of tower drum transportation scheduling, the system is mainly composed of a data acquisition module, an analysis processing module, a transportation monitoring module and a communication module, the data acquisition module collects various tower drum transportation data and is connected with various sensors and an information system; the data analysis processing module plans and schedules transportation tasks according to the data, and a built-in model of the data analysis processing module considers various cost and risk factors to generate an optimal scheme; the transportation monitoring module monitors transportation in real time and adjusts the states of the vehicle and the ship according to an instruction; and the communication module ensures data transmission, interaction, security and confidentiality. In addition, the data analysis processing module further comprises a data storage and visual display unit, and the transportation monitoring module is provided with an emergency processing and remote operation unit. According to the invention, the transportation scheme can be effectively optimized, accurate monitoring is realized, data safety is guaranteed, the emergency capability is improved, the transportation efficiency and safety of the tower drum are obviously improved, and the cost and risk are reduced.

Description

Technical Field

[0001] The present invention relates to the technical field of tower transportation scheduling, and more specifically, to a tower transportation scheduling system based on data analysis. Background Art

[0002] In the current energy development pattern, the offshore wind power industry is booming. As the key supporting component of offshore wind turbines, the efficiency and safety of tower transportation are crucial. Traditional tower transportation scheduling mainly relies on manual experience and basic logistics planning, which has many drawbacks.

[0003] As the construction of offshore wind farms moves deeper into the sea, the transportation distance of towers continues to increase, and the transportation routes become more complex, covering different road conditions for land transportation and changeable sea conditions for sea transportation. On land, factors such as road construction, traffic congestion, and undulating terrain frequently affect the progress of transportation; in sea transportation, tidal changes, wave fluctuations, stormy weather, etc. pose a serious threat to the safety of ship navigation.

[0004] Moreover, traditional dispatching methods make it difficult to integrate various data information during transportation. Data such as the location and speed of transport vehicles, the busyness of dock operations, real-time sea conditions, and dynamic changes in weather cannot be effectively collected, analyzed, and utilized. This makes it impossible to accurately assess transportation costs, reasonably arrange transportation resources, and effectively avoid transportation risks when formulating transportation plans.

[0005] In previous projects, due to the lack of accurate predictions of road conditions and weather, transport vehicles often encountered unexpected delays on the way, resulting in the tower being unable to arrive at the dock on time; during the sea transportation stage, due to insufficient consideration of sea conditions, ships sailed in bad weather, which not only endangered the safety of the cargo, but also could cause damage to the ship and casualties.

[0006] At the same time, in terms of transportation monitoring, traditional means can only perform simple location tracking, lack of real-time monitoring of the equipment operation status of vehicles and ships, and once a failure occurs, it is difficult to detect and handle it in time. In the face of emergencies, such as traffic accidents, sudden equipment failures or severe weather, the lack of effective emergency response mechanisms and rapid response capabilities often leads to transportation interruptions, causing huge economic losses and time delays to the project.

[0007] Therefore, a tower transportation scheduling system based on data analysis is proposed. Summary of the invention

[0008] In order to overcome the above-mentioned defects of the prior art, the present invention provides a tower transportation scheduling system based on data analysis to solve the problems raised in the above-mentioned background technology.

[0009] To achieve the above object, the present invention provides the following technical solution: a tower transportation scheduling system based on data analysis, comprising: The data acquisition module is used to collect various data during the tower transportation process, including but not limited to the tower's size parameters, weight data, location information of the transport vehicle, driving speed, road condition information of the transport route, the operating status of the terminal, sea condition information of sea transportation, and weather data; the data acquisition module is connected to various sensors and information systems, and the sensors include positioning sensors and speed sensors installed on the transport vehicle, loading and unloading operation monitoring sensors installed at the terminal, and meteorological sensors and ocean monitoring equipment for obtaining sea conditions and weather information; the information system includes the vehicle management system of the transportation company and the operation management system of the terminal.

[0010] The data analysis and processing module is communicatively connected with the data acquisition module, and is used for receiving and analyzing the collected data, and planning and scheduling the transportation tasks according to the preset algorithms and models; the data analysis and processing module has a built-in transportation cost calculation model, which takes into account factors such as vehicle fuel consumption, labor costs, equipment loss and transportation time; it also has a built-in transportation risk assessment model, which assesses the risks in the transportation process based on historical accident data and real-time road conditions, sea conditions, weather and other information; and according to the urgency of the transportation task, the characteristics of the tower and the availability of transportation resources, an optimal transportation plan is generated through an optimization algorithm, including the deployment of transportation vehicles, the selection of transportation routes and the arrangement of transportation time.

[0011] The transport monitoring module is connected to the data analysis and processing module and the control systems of the transport vehicles and ships, and is used to monitor the transport process in real time and adjust the operating status of the transport vehicles and ships according to the instructions of the data analysis and processing module; the transport monitoring module can receive the real-time position, speed, driving direction and other information of the transport vehicles and ships, and compare it with the preset transport plan. When deviation occurs, it will promptly issue an alarm and send adjustment instructions to the control systems of the vehicles and ships; at the same time, it can also monitor the operating status of the equipment on the vehicles and ships, such as engine temperature, oil pressure and other parameters, to ensure the normal operation of the transport equipment.

[0012] The communication module is used to realize data transmission between the data acquisition module, the data analysis and processing module and the transportation monitoring module, as well as data interaction with external systems such as the terminal management system, the ship dispatching system and the weather forecast system; the communication module adopts wireless communication technology, including but not limited to 4G / 5G network, satellite communication, etc., to ensure stable data transmission in different geographical environments; and has data encryption function to ensure the security and confidentiality of transportation data.

[0013] Preferably, the data analysis and processing module also includes: The data storage unit is used to store the collected historical data and the result data after analysis and processing, and provide data support for subsequent transportation task planning and decision-making; the data storage unit adopts a large-capacity database system, which can store long-term transportation data and has data backup and recovery functions to prevent data loss; at the same time, the stored data is classified and managed to facilitate quick query and call.

[0014] The visualization display unit is connected to the data storage unit and is used to display the results of data analysis and processing to users in intuitive forms such as charts and maps, so as to facilitate users to understand the transportation situation and make decisions; the visualization display unit can generate a transportation route map, mark the real-time position, driving trajectory and estimated arrival time of transportation vehicles and ships; and can also display the composition of transportation costs, the changing trend of transportation efficiency and the assessment results of transportation risks in the form of charts.

[0015] Preferably, the transport monitoring module further includes: The emergency handling unit is used to initiate corresponding emergency measures according to the preset emergency plan when an emergency occurs during transportation, and to notify relevant personnel in a timely manner; the emergency handling unit can automatically identify common emergencies, such as vehicle failures, traffic accidents, severe weather impacts, etc., and handle them according to the emergency plan process; at the same time, it can send alarm information and on-site situation reports to the driver, transportation management personnel and relevant rescue departments through the communication module.

[0016] The remote operation unit, under special circumstances, allows authorized personnel to control some functions of transport vehicles and ships through the remote operation unit to ensure transportation safety; the remote operation unit has a strict identity authentication and authority management mechanism, and only authorized personnel can perform remote operation; and the remote operation process is recorded and audited to ensure the legality and traceability of the operation.

[0017] Preferably, the system scheduling operation includes the following steps: In the data collection step, various data in the tower transportation process are collected in real time through the data collection module, and the data is transmitted to the data analysis and processing module. During the data collection process, the collected data is preliminarily checked and cleaned to remove invalid and abnormal data to ensure the accuracy and reliability of the data. At the same time, the data is prioritized according to its importance and timeliness to ensure that key data can be transmitted and processed in a timely manner.

[0018] In the data analysis step, the data analysis and processing module receives the collected data, uses the built-in transportation cost calculation model and transportation risk assessment model to analyze and evaluate the transportation tasks, and generates multiple feasible transportation plans. During the analysis process, the model parameters are continuously updated and optimized to adapt to different transportation scenarios and actual conditions. In addition, the generated transportation plans are preliminarily screened to eliminate obviously unreasonable plans and improve the efficiency of subsequent decision-making.

[0019] In the plan decision step, the optimal transportation plan is determined from multiple feasible transportation plans based on the preset decision criteria and the user's choice, and the plan instructions are sent to the transportation monitoring module. In the decision-making process, the user's special needs and preferences are fully considered, such as the emphasis on transportation time, transportation cost, and transportation safety. At the same time, plan comparison and evaluation reports are provided to help users make reasonable decisions.

[0020] In the transport monitoring step, the transport monitoring module monitors and adjusts the operation of transport vehicles and ships in real time according to the received plan instructions to ensure that the transportation process is carried out according to the predetermined plan; during the monitoring process, new data in the transportation process is continuously collected and fed back to the data analysis and processing module for dynamic adjustment and optimization; at the same time, key events and abnormal situations in the transportation process are recorded and reported to provide a basis for subsequent transportation management and improvement.

[0021] Preferably, the data analysis step further includes: In the data mining and learning steps, machine learning algorithms are used to mine and learn historical data stored in the data storage unit, continuously optimize the parameters and algorithms of the transportation cost calculation model and the transportation risk assessment model, and improve the accuracy and rationality of the transportation plan; in the data mining and learning process, a variety of machine learning algorithms are used for comparison and verification to select the optimal algorithm and model; and the model is evaluated and updated regularly to ensure the performance and adaptability of the model.

[0022] In the simulation and prediction steps, the optimized model is used to simulate and predict the transportation process according to the current transportation tasks and environmental conditions, to assess possible problems and risks in advance, and to formulate corresponding countermeasures in the transportation plan; in the simulation and prediction process, the influence of various uncertain factors is considered, such as weather changes, traffic congestion, equipment failure, etc., to improve the accuracy and reliability of the prediction; at the same time, a sensitivity analysis of the transportation plan is conducted based on the simulation and prediction results to find out the factors that have a greater impact on the transportation results, and to focus on and optimize them.

[0023] Technical effects and advantages of the present invention: 1. This system collects various transportation data through the data acquisition module. The data analysis and processing module uses the transportation cost calculation model and the transportation risk assessment model to comprehensively consider factors such as vehicle fuel consumption, labor costs, equipment loss, transportation time, road conditions, sea conditions and weather to generate the optimal transportation plan, effectively reduce transportation costs and risks, and accurately select the best routes and time periods for land and sea transportation, significantly improving transportation efficiency and safety.

[0024] 2. The transport monitoring module can receive real-time information such as the location, speed, driving direction and equipment operating status of vehicles and ships, and compare it with the preset transport plan. When the deviation exceeds the threshold, timely alarm and adjustment will be made, and the emergency handling unit can quickly activate the plan to ensure the smooth progress of the transport task and reduce losses.

[0025] 3. The data storage unit of the data analysis and processing module can store a large amount of historical and result data, providing strong support for subsequent transportation planning. Its classification management function facilitates query and call; the visual display unit displays the transportation situation with charts and maps, helping users to intuitively understand and make scientific decisions.

[0026] 4. The communication module adopts 4G / 5G network, satellite communication and other wireless technologies to ensure stable data transmission in different geographical environments. The data encryption function ensures the security and confidentiality of transportation data to prevent information leakage.

[0027] 5. The emergency handling unit of the transport monitoring module can automatically identify common emergencies and handle them according to the process, and notify relevant personnel in time; the remote operation unit allows authorized personnel to remotely control the transport equipment under special circumstances, and the identity authentication, authority management, and operation record audit mechanism ensure that the operation is legal, compliant, and traceable, thereby enhancing the emergency handling capability. DETAILED DESCRIPTION

[0028] Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in the field without making any creative work shall fall within the scope of protection of the present invention.

[0029] The present invention provides a tower transportation scheduling system based on data analysis, comprising: Data acquisition module Positioning sensor: Select high-precision GPS or Beidou positioning system sensors and install them on transport vehicles and ships to obtain real-time location information with sub-meter positioning accuracy. For example, install them on the top of the cab of transport vehicles and the cab or mast of ships to ensure good signal reception.

[0030] Speed ​​sensor: A vehicle-mounted or ship-mounted professional speed sensor is used, which is connected to the power system of the vehicle or ship and can accurately measure the driving speed with an accuracy within ±0.5km / h.

[0031] Loading and unloading monitoring sensors: Pressure sensors, displacement sensors, etc. are installed on the cranes, loaders and other loading and unloading equipment at the dock to monitor the loading and unloading status of the tower, such as lifting weight, lifting height, etc. The pressure sensor accuracy can reach ±0.1% of the full scale, and the displacement sensor accuracy is within ±5mm.

[0032] Meteorological sensors and ocean monitoring equipment: Meteorological stations are set up at docks and ships, including anemometers, thermometers, hygrometers, etc. The wind speed measurement range is 0-50m / s, with an accuracy of ±0.3m / s; the thermometer measurement range is -50℃-50℃, with an accuracy of ±0.5℃; the hygrometer measurement range is 0-100%RH, with an accuracy of ±3%RH. Ocean monitoring equipment such as wave height meters and tide meters, wave height measurement accuracy can reach ±0.1m, and tide meter accuracy is within ±5cm.

[0033] Data analysis and processing module Server: Use high-performance servers, configure multi-core processors (such as Intel Xeon E5 series), main frequency not less than 2.4 GHz, memory not less than 32 GB, use high-speed solid-state drives (SSDs) as system disks, with a capacity of not less than 500 GB for storing operating systems and core programs; and be equipped with large-capacity mechanical hard drives (such as 4 TB) for data storage.

[0034] Network equipment: Gigabit Ethernet switches are used to ensure high-speed and stable communication between the data acquisition module, data analysis and processing module, and transportation monitoring module. In areas where network connections are unstable, such as during maritime transportation, satellite communication equipment is equipped as a backup communication means, such as Inmarsat or Iridium satellite communication terminals.

[0035] Transport monitoring module Vehicle and ship-mounted monitoring terminals: Industrial-grade tablet computers or special monitoring equipment are used, with touch screens, screen sizes of not less than 10 inches, and resolutions of not less than 1280 × 800. They are connected to the vehicle or ship control system via the CAN bus or RS485 serial port to achieve real-time monitoring of the vehicle and ship operating status and transmission of control commands.

[0036] Remote monitoring center: It is set up in the dispatching room of the transportation company, equipped with multiple high-performance computers and installed with monitoring software. It communicates with the transportation monitoring module through the network to achieve centralized monitoring and management of all transportation tasks.

[0037] Data acquisition module software The data acquisition program is written in C++ or Python and runs on the data acquisition device. Data is exchanged with various sensors and information systems through serial communication or network communication protocols (such as TCP / IP, UDP). For example, for positioning sensors and speed sensors, the NMEA0183 protocol is used for data analysis; for loading and unloading operation monitoring sensors, data is read and analyzed according to the communication protocol provided by the sensor manufacturer.

[0038] The data acquisition program has a data cache function. When the network communication is temporarily interrupted, the collected data can be temporarily stored in the local cache and automatically uploaded to the data analysis and processing module after the network is restored. The cache capacity is set according to the frequency of sensor data generation and the expected duration of network interruption. Generally, at least 1 hour of data can be cached.

[0039] Data analysis and processing module software The transportation cost calculation model and transportation risk assessment model are implemented by combining machine learning algorithms and mathematical optimization algorithms. For example, machine learning algorithms such as linear regression and decision trees are used to analyze and model historical transportation cost and risk data, determine the key factors affecting costs and risks and their weights; then combine integer programming, dynamic programming and other mathematical optimization algorithms to generate the optimal transportation plan while meeting the transportation task requirements.

[0040] The data analysis and processing software is developed using Java or Python web frameworks (such as SpringBoot, Django), providing web service interfaces for transport monitoring modules and other external systems to call. The interface design follows the RESTful architecture style and uses JSON format for data transmission to ensure the simplicity and universality of data interaction.

[0041] Transport Monitoring Module Software The vehicle-mounted and ship-mounted monitoring terminal software is developed using the Android or Linux operating system and has a graphical user interface that displays real-time information such as the location, speed, route, tower status, etc. of the transport vehicle or ship. The transport route is visualized through a map engine (such as Baidu Maps and Google Maps API), and the operating status of the vehicle and ship is adjusted according to the instructions of the data analysis and processing module, such as adjusting the speed and changing the course.

[0042] The remote monitoring center software adopts B / S architecture and can be accessed through a browser. Using data visualization libraries such as Echarts, the transportation monitoring data is displayed to dispatchers in the form of charts, maps, etc. At the same time, it has an alarm function. When abnormal situations occur during transportation (such as vehicle deviation from the scheduled route, equipment failure, bad weather, etc.), relevant personnel are notified in a timely manner through pop-up windows, text messages, etc.

[0043] The specific system workflow is as follows: Data collection and transmission The data acquisition module collects various types of data at preset time intervals (such as 1 second) and pre-processes the data, including data verification, denoising, format conversion, etc. For example, coordinate conversion and accuracy verification are performed on positioning data, and digital filtering is performed on analog signals collected by sensors. The processed data is then sent to the data analysis and processing module through the communication module.

[0044] During the data transmission process, data encryption technology (such as SSL / TLS encryption protocol) is used to encrypt the transmitted data to ensure data security. At the same time, the communication module has a data retransmission mechanism. When the receiver does not receive the data correctly, it automatically retransmits the data to ensure data integrity.

[0045] Data analysis and solution generation After receiving the data, the data analysis and processing module first stores the data in the data storage unit. Then, the transportation cost calculation model and transportation risk assessment model are called to analyze and evaluate the transportation task, and multiple feasible transportation plans are generated according to different transportation goals (such as lowest cost, shortest time, lowest risk, etc.). For example, when considering transportation costs, the vehicle fuel consumption, labor costs, equipment rental costs, etc. are comprehensively calculated; when evaluating transportation risks, the impact of factors such as road conditions, sea conditions, and weather on transportation safety is analyzed.

[0046] Genetic algorithms, simulated annealing algorithms and other optimization algorithms are used to optimize and screen the generated transportation plans to determine the best transportation plan. During the optimization process, parameters such as the deployment of transportation vehicles, the selection of transportation routes, and the arrangement of transportation time are continuously adjusted until the preset optimization goal is met or the maximum number of iterations is reached.

[0047] Transport monitoring and adjustment The transport monitoring module receives the transport plan instructions generated by the data analysis and processing module, and sends the instructions to the control systems of the transport vehicles and ships to realize automatic control of the transport process. At the same time, it monitors the operating status of the transport vehicles and ships in real time and compares the actual operating data with the predetermined plan. For example, the actual position of the vehicle is compared with the predetermined route every 5 seconds. If the deviation exceeds a certain threshold (such as 10 meters), an alarm is issued and the vehicle's driving direction is automatically adjusted.

[0048] When emergencies occur during transportation (such as traffic accidents, equipment failures, bad weather, etc.), the emergency handling unit initiates corresponding emergency measures according to the preset emergency plan. For example, when encountering bad weather, the ship's sailing speed and course are automatically adjusted to find the nearest safe haven; when a vehicle breaks down, the maintenance personnel are notified and spare vehicles are dispatched to the scene for rescue. At the same time, the communication module promptly notifies relevant personnel, such as drivers, dispatchers, customers, etc., to inform them of changes in transportation conditions and the response measures taken.

[0049] Data backup and recovery The data storage unit performs a full data backup once a day and backs up the data to an external storage device (such as NAS storage, tape library). The backup data is stored in a redundant manner to ensure data security. At the same time, the backup data is regularly (such as weekly) checked for integrity and tested for recovery to ensure that the data can be quickly restored in the event of data loss or damage.

[0050] When data is abnormal or lost, select the appropriate backup version for data recovery based on the timestamp and data log of the backup data. During the recovery process, verify and check the integrity of the recovered data to ensure the accuracy and integrity of the data.

[0051] Software Updates and Upgrades The system software is upgraded by combining online and offline updates. For some minor functional improvements and bug fixes, the online update mechanism automatically downloads and installs update patches without affecting the normal operation of the system. For major software version upgrades, such as system architecture adjustments or the addition of important functional modules, the offline update method is used to reinstall and configure the software during system downtime maintenance.

[0052] Before software updates and upgrades, the new version of the software is fully tested and verified, including functional testing, performance testing, compatibility testing, etc. Ensure that the new version of the software can run stably and is compatible with existing hardware devices and other system software. At the same time, during the update process, the system data is protected to prevent data loss or damage. Example

[0053] An offshore wind farm project is located 100 nautical miles from the coastline and plans to install 100 sets of tower equipment.

[0054] Specifically, the data acquisition module installed high-precision GPS positioning sensors and speed sensors on the transport vehicles, pressure sensors and displacement sensors on the cranes at the dock, and weather stations and ocean monitoring equipment on the shore and ships. In the early stage of transportation, these sensors collected a large amount of data, including the location information of the transport vehicles, driving speed, loading and unloading of the tower, sea conditions (such as wave height, tidal changes) and weather data (such as wind speed, wind direction, temperature, etc.).

[0055] After receiving these data, the data analysis and processing module uses the built-in transportation cost calculation model and transportation risk assessment model for analysis. For example, the cost of different transportation routes is calculated based on the vehicle's driving speed and route information, combined with fuel consumption data; the risk level in the transportation process is evaluated based on sea conditions and weather data. After analysis, it was found that although an alternative land transportation route from the factory to the dock is slightly longer, the road conditions are better, the vehicle speed is stable, and the overall cost is low; and in the sea transportation process, according to the ocean monitoring data, choosing to transport in a specific time period (avoiding strong winds and big waves) can effectively reduce transportation risks.

[0056] Based on the data analysis results, the system generated a transportation plan. Ten 8-axle 4-tandem hydraulic axle vehicles were arranged for the transportation of the T1 section tower, and 15 16-axle 3-tandem hydraulic axle vehicles were arranged for the transportation of the T2-T4 section tower. The transportation route was determined to start from the tower manufacturing plant, arrive at the dock via the designated land channel, and then be transported by sea to the installation site of the offshore wind farm.

[0057] The transport monitoring module monitors the operating status of vehicles and ships in real time during the transport process. For example, during land transport, it was found that the speed of a transport vehicle was abnormally reduced. After inspection, it was found that the engine of the vehicle was faulty. The emergency handling unit immediately activated the emergency plan, notified nearby maintenance personnel to go to the scene, and dispatched spare vehicles to transfer the tower to ensure that the transportation task was not greatly affected. During the sea transport process, when the ship encountered a sudden strong wind, according to the instructions of the system, the ship automatically adjusted its course and speed and sailed to a nearby shelter, ensuring the safety of the ship and the tower.

[0058] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims

1. A tower transportation scheduling system based on data analysis, characterized in that: include: The data acquisition module is used to collect various data during the tower transportation process, including but not limited to the tower size parameters, weight data, location information of the transport vehicle, driving speed, road condition information of the transport route, operation status of the terminal, sea condition information of the sea transport, and weather data; the data acquisition module is connected to various sensors and information systems, the sensors include positioning sensors and speed sensors installed on the transport vehicle, loading and unloading operation monitoring sensors installed at the terminal, and meteorological sensors and ocean monitoring equipment for obtaining sea condition and weather information; the information system includes the vehicle management system of the transport enterprise and the operation management system of the terminal; The data analysis and processing module is connected to the data acquisition module for receiving and analyzing the collected data, and planning and scheduling the transportation tasks according to the preset algorithms and models; the data analysis and processing module has a built-in transportation cost calculation model, which takes into account factors such as vehicle fuel consumption, labor costs, equipment loss and transportation time; It also has a built-in transportation risk assessment model, which assesses the risks in the transportation process based on historical accident data and real-time road conditions, sea conditions, weather and other information; and generates the best transportation plan through optimization algorithms according to the urgency of the transportation task, the characteristics of the tower and the availability of transportation resources, including the deployment of transportation vehicles, the selection of transportation routes and the arrangement of transportation time; The transport monitoring module is connected to the data analysis and processing module and the control systems of the transport vehicles and ships, and is used to monitor the transport process in real time and adjust the operating status of the transport vehicles and ships according to the instructions of the data analysis and processing module; the transport monitoring module can receive the real-time position, speed, and driving direction information of the transport vehicles and ships, and compare them with the preset transport plan. When deviations occur, an alarm is issued in time and adjustment instructions are sent to the control systems of the vehicles and ships; at the same time, the operating status of the equipment on the vehicles and ships, such as engine temperature, oil pressure and other parameters, is also monitored to ensure the normal operation of the transport equipment; The communication module is used to realize data transmission between the data acquisition module, the data analysis and processing module and the transportation monitoring module, as well as data interaction with external systems such as the terminal management system, the ship dispatching system and the weather forecast system; the communication module adopts wireless communication technology, including but not limited to 4G / 5G network and satellite communication, to ensure stable data transmission in different geographical environments; and has data encryption function to ensure the security and confidentiality of transportation data.

2. A tower transportation scheduling system based on data analysis according to claim 1, characterized in that: The data analysis and processing module also includes: Data storage unit, used to store the collected historical data and the result data after analysis and processing, to provide data support for subsequent transportation task planning and decision-making; The visualization display unit is connected to the data storage unit and is used to display the results of data analysis and processing to users in the form of charts and maps, so that users can understand the transportation situation and make decisions.

3. A tower transportation scheduling system based on data analysis according to claim 2, characterized in that: The data storage unit adopts a large-capacity database system, which can store long-term transportation data and has data backup and recovery functions to prevent data loss; at the same time, the stored data is classified and managed to facilitate quick query and call.

4. The tower transportation scheduling system based on data analysis according to claim 2 is characterized in that: The visualization display unit can generate a transportation route map, marking the real-time position, driving trajectory and estimated arrival time of transportation vehicles and ships; it can also display the composition of transportation costs, the changing trend of transportation efficiency and the assessment results of transportation risks in the form of charts.

5. The tower transportation scheduling system based on data analysis according to claim 1 is characterized in that: The transport monitoring module also includes: The emergency handling unit is used to initiate corresponding emergency measures according to the preset emergency plan when an emergency occurs during transportation, and promptly notify relevant personnel; The remote operation unit allows authorized personnel to control some functions of transport vehicles and ships through the remote operation unit under special circumstances to ensure transportation safety.

6. A tower transportation scheduling system based on data analysis according to claim 5, characterized in that: The emergency handling unit is used to automatically identify common emergencies, including but not limited to vehicle breakdowns, traffic accidents, and severe weather conditions, and handle them in accordance with the emergency plan process; at the same time, it can send alarm information and on-site situation reports to drivers, transportation managers, and relevant rescue departments through the communication module.

7. The tower transportation scheduling system based on data analysis according to claim 5 is characterized in that: The remote operation unit has a strict identity authentication and authority management mechanism, and only authorized personnel can perform remote operation; and the remote operation process is recorded and audited to ensure the legality and traceability of the operation.