Port Flow Optimization Scheduling System and Method Based on Internet of Things Big Data

Abstract

The present invention discloses a port flow optimization and scheduling system and method based on Internet of Things big data, which relates to the field of electronic digital data processing technology. The port flow optimization and scheduling system based on Internet of Things big data includes: a data acquisition module, a congestion assessment module, a signal impact assessment module and a receiver impact assessment module. The present invention obtains a waterway congestion assessment coefficient through ship congestion-related data and determines whether to obtain a ship signal impact assessment coefficient. Then, it obtains a ship signal impact assessment coefficient based on ship signal-related data and determines whether to perform a signal impact adjustment. Finally, it obtains a ship receiver impact assessment coefficient based on ship receiver-related data and determines whether to perform a receiver impact adjustment. This achieves the effect of improving the accuracy of port flow data collection during port flow optimization and scheduling, and solves the problem of inaccurate port flow data collection during port flow optimization and scheduling in the prior art.

Description

Technical Field

[0001] The present invention relates to the technical field of electronic digital data processing, and in particular to a port flow optimization scheduling system and method based on Internet of Things big data. Background Art

[0002] With the continuous development of global trade, ports, as key nodes in international trade, face increasing challenges in traffic management. Optimizing port traffic scheduling is crucial to improving port operational efficiency and service quality. Optimizing scheduling can reduce waiting times for ships and vehicles at ports and improve port throughput efficiency. Rational allocation of port resources, such as berths, storage yards, and loading and unloading equipment, can improve resource utilization and operational efficiency. Real-time monitoring and analysis of port data can promptly identify and address potential safety hazards, ensuring safe and stable port operations. The Internet of Things (IoT) connects objects and everyday devices via the internet to enable interoperability and information sharing. IoT technology has been widely applied in port management.

[0003] The existing system mainly collects real-time data related to port traffic, such as ship entry and exit times, cargo throughput, and container numbers, and uses big data analysis and artificial intelligence technologies to deeply mine and analyze these data. The system can automatically adjust port resource allocation based on the analysis results, optimize ship berthing and cargo loading and unloading processes, and thus improve port operating efficiency.

[0004] For example, the invention patent with announcement number CN117744501B discloses an optimization scheduling and decision-making method for regulating and storing nodes of a water network system taking into account ecological flow, including: determining the study area and obtaining research data; reading hydrological data, extracting annual runoff sequences and monthly runoff sequences, constructing and solving the Copula joint distribution function of annual runoff and monthly runoff, calculating the ecological flow considering the wet and dry characteristics of annual runoff and monthly runoff, and constructing an ecological scheduling scenario set; constructing a multi-objective optimization scheduling model, including objective functions and constraints; constructing a model solving method, solving the multi-objective optimization scheduling model, obtaining a set of feasible solutions, and constructing a decision-making method to select at least one solution from the set of feasible solutions.

[0005] For example, the invention patent with announcement number CN110851977B discloses an optimization method for a multi-objective water supply-power generation-ecological scheduling diagram based on ecological flow, which includes: 1. collecting long-series inflow runoff data of the reservoir, water demand data of the water supply area, ecological base flow data of the downstream river, and existing conventional scheduling diagrams; 2. using a monthly frequency method to determine the long-series ecological flow threshold interval of the downstream river; 3. constructing an optimization model for a multi-objective water supply-power generation-ecological scheduling diagram; 4. using "optimization-simulation" technology to solve the optimization model, obtain an optimized scheduling diagram, and determine various benefit indicators and the reservoir operation process.

[0006] However, in the process of implementing the technical solutions of the embodiments of the present application, the present application discovered that the above technology has at least the following technical problems:

[0007] In the existing technology, the behavior of ships entering and leaving the port is affected by many factors. For example, when a large number of ships sail, the quality of the input port flow data may be affected, resulting in inaccurate port flow data collection during the port flow optimization and scheduling process. Summary of the Invention

[0008] The embodiments of the present application solve the problem of inaccurate port flow data collection in the process of port flow optimization and scheduling in the prior art by providing a port flow optimization and scheduling system and method based on Internet of Things big data, and achieve improved accuracy of port flow data collection in the process of port flow optimization and scheduling.

[0009] An embodiment of the present application provides a port flow optimization and scheduling system based on Internet of Things big data, including a data acquisition module, a congestion assessment module, a signal impact assessment module and a receiver impact assessment module: wherein the data acquisition module is used to obtain ship congestion-related data, ship signal-related data and ship receiver-related data through preset port ship monitoring equipment; the congestion assessment module is used to obtain a channel congestion assessment coefficient based on the acquired ship congestion-related data and reference ship congestion data within a preset first time period, and judge whether to obtain a ship signal impact assessment coefficient based on the acquired channel congestion assessment coefficient, and the channel congestion assessment coefficient is used to evaluate the port channel congestion status; the signal impact assessment module is used to obtain a channel congestion assessment coefficient based on the acquired channel congestion assessment coefficient, The ship signal impact assessment coefficient is obtained based on the ship signal related data and the reference ship signal data, and it is determined whether to perform signal impact adjustment based on the obtained ship signal impact assessment coefficient. The ship signal impact assessment coefficient is used to evaluate the degree of impact of port channel congestion on port ship signals; the receiver impact assessment module is used to obtain the ship receiver impact assessment coefficient based on the obtained channel congestion assessment coefficient, the ship receiver related data and the reference ship receiver data within a preset second time period, and determine whether to perform receiver impact adjustment based on the obtained ship receiver impact assessment coefficient. Port flow optimization scheduling is performed based on the signal impact adjustment and the receiver impact adjustment. The ship receiver impact assessment coefficient is used to evaluate the degree of impact of the port channel congestion condition on the receiver monitoring the port channel.

[0010] Furthermore, the preset port ship monitoring equipment includes radar, timer and spectrum analyzer; the ship congestion-related data includes the number of ships, passing time and signal round-trip time; the ship signal-related data includes signal round-trip time and signal wavelength; the ship receiver-related data includes the number of paths, transmission and reception distance and signal frequency; the number of paths represents the number of signal paths for the signal reflected from the ship to reach the receiver; the preset first time period represents the preset time period in the process of port flow statistics; the preset second time period represents the preset time period corresponding to the preset first time period when the waterway congestion assessment coefficient is not lower than the preset congestion threshold, and the interval between the preset second time period and the preset first time period is the same; the reference ship congestion data includes a preset ship distance threshold, a preset ship flow threshold and the speed of light; the reference ship signal data includes a preset reflection loss threshold and the speed of light; the reference ship receiver data includes a preset multipath ship loss threshold, the speed of light and the preset free space loss threshold.

[0011] Furthermore, the specific process of obtaining the waterway congestion assessment coefficient based on the acquired ship congestion-related data and the reference ship congestion data within the preset first time period is as follows: A1, obtaining the initial ship distance through the signal round-trip time and the speed of light, and the initial ship distance is represented by the result of multiplying the signal round-trip time and the speed of light; A2, obtaining the initial ship distance deviation through the initial ship distance and the preset ship distance threshold, and the initial ship distance deviation is represented by the result of adding the initial ship distance and the preset ship distance threshold; A3, obtaining the ship distance deviation through the initial ship distance deviation and the preset ship distance threshold, and the ship distance deviation is represented by the product of the initial ship distance deviation and the preset ship distance threshold. A4, obtaining the initial ship flow through the number of ships and the passing time, the initial ship flow is expressed by the result of the ratio operation of the number of ships and the passing time; A5, obtaining the initial ship flow deviation through the initial ship flow and the preset ship flow threshold, the initial ship flow deviation is expressed by the result of the addition operation of the initial ship flow and the preset ship flow threshold; A6, obtaining the ship flow deviation through the initial ship flow deviation and the preset ship flow threshold, the ship flow deviation is expressed by the result of the ratio operation of the initial ship flow deviation and twice the preset ship flow threshold; A7, obtaining the waterway congestion assessment coefficient in combination with the ship distance deviation and the ship flow deviation.

[0012] Furthermore, the restricted expression of the waterway congestion assessment coefficient is as follows:

[0013]

[0014] In the formula, YD qIt represents the channel congestion assessment coefficient of the port channel in the qth preset first time period, q=1,2,..,n, q represents the number of the preset first time period, n represents the total number of preset first time periods, It represents the ship distance deviation of the port channel in the qth preset first time period, It represents the ship flow deviation of the port channel in the qth preset first time period, represents the initial ship distance of the port channel in the qth preset first time period, represents the initial ship flow in the port channel during the qth preset first time period, represents the number of ships in the port channel in the qth preset first time period, Indicates the duration of passage through the port channel in the qth preset first time period, It represents the round trip time of the signal of the port channel in the qth preset first time period, Indicates the preset ship distance threshold, The ship flow threshold is preset, c represents the speed of light, and e represents a natural constant.

[0015] Furthermore, the specific process of obtaining the ship signal impact assessment coefficient based on the obtained channel congestion assessment coefficient, ship signal related data and reference ship signal data within the preset second time period is as follows: B1, processing the initial ship distance and signal wavelength to obtain the initial reflection loss, and the initial reflection loss is represented by the result of a logarithmic operation of the initial ship distance and the signal wavelength; B2, obtaining the initial reflection loss deviation through the initial reflection loss and the preset reflection loss threshold, and the initial reflection loss deviation is represented by the result of an addition operation between the initial reflection loss and the preset reflection loss threshold; B3, obtaining the reflection loss deviation through the initial reflection loss deviation and the preset reflection loss threshold, and the reflection loss deviation is represented by the result of a ratio operation between the initial reflection loss deviation and twice the preset reflection loss threshold; B4, obtaining the ship signal impact assessment coefficient in combination with the reflection loss deviation and the channel congestion assessment coefficient of the preset second time period.

[0016] Furthermore, the specific process of obtaining the ship receiver impact assessment coefficient based on the obtained waterway congestion assessment coefficient, ship receiver related data and reference ship receiver data within the preset second time period is as follows: C1, processing the number of paths to obtain the initial propagation loss, and the initial propagation loss is represented by the result of a logarithmic operation on the number of paths; C2, obtaining the initial propagation loss deviation through the initial propagation loss and the preset multipath ship loss threshold, and the initial propagation loss deviation is represented by the result of an addition operation between the initial propagation loss and the preset multipath ship loss threshold; C3, obtaining the propagation loss deviation through the initial propagation loss deviation and the preset multipath ship loss threshold, and the propagation loss deviation is the result of a ratio operation between the initial propagation loss deviation and twice the preset multipath ship loss threshold. Representation; C4, processing the transmitting and receiving distance, signal frequency and speed of light to obtain the initial space loss, and the initial space loss is represented by the result of logarithmic operation of the transmitting and receiving distance, signal frequency and speed of light; C5, obtaining the initial space loss deviation through the initial space loss and the preset free space loss threshold, and the initial space loss deviation is represented by the result of addition operation of the initial space loss and the preset free space loss threshold; C6, obtaining the space loss deviation through the initial space loss deviation and the preset free space loss threshold, and the space loss deviation is represented by the result of ratio operation of the initial space loss deviation and twice the preset free space loss threshold; C7, combining the initial space loss, space loss deviation and the channel congestion assessment coefficient of the preset second time period to obtain the ship receiver impact assessment coefficient.

[0017] The embodiment of the present application provides a port flow optimization scheduling method based on Internet of Things big data, comprising the following steps: S1, obtaining ship congestion-related data, ship signal-related data and ship receiver-related data through preset port ship monitoring equipment; S2, obtaining a channel congestion assessment coefficient based on the obtained ship congestion-related data and reference ship congestion data within a preset first time period, and judging whether to obtain a ship signal impact assessment coefficient based on the obtained channel congestion assessment coefficient, wherein the channel congestion assessment coefficient is used to assess the port channel congestion status; S3, obtaining a ship signal impact assessment coefficient based on the obtained channel congestion assessment coefficient, ship signal-related data and reference ship signal data within a preset second time period. S4, obtaining a ship receiver impact assessment coefficient according to the obtained channel congestion assessment coefficient, ship receiver related data and reference ship receiver data within a preset second time period, determining whether to perform receiver impact adjustment based on the obtained ship receiver impact assessment coefficient, and performing port flow optimization scheduling based on the signal impact adjustment and the receiver impact adjustment, wherein the ship receiver impact assessment coefficient is used to assess the impact of the port channel congestion on the receiver monitoring the port channel.

[0018] One or more technical solutions provided in the embodiments of this application have at least the following technical effects or advantages:

[0019] 1. The waterway congestion assessment coefficient is obtained through ship congestion-related data and reference ship congestion data, and it is determined whether to obtain the ship signal impact assessment coefficient. Then, the ship signal impact assessment coefficient is obtained based on the ship signal-related data and the reference ship signal data, and it is determined whether to perform signal impact adjustment. Finally, the ship receiver impact assessment coefficient is obtained based on the ship receiver-related data and the reference ship receiver data, and it is determined whether to perform receiver impact adjustment. This realizes the dynamic quantification of port flow scheduling, and further realizes the improvement of the accuracy of port flow data collection in the process of port flow optimization scheduling, effectively solving the problem of inaccurate port flow data collection in the process of port flow optimization scheduling in the existing technology.

[0020] 2. By pre-setting the port ship monitoring equipment, the ship congestion related data, ship signal related data and ship receiver related data are obtained. Based on the ship congestion related data, ship signal related data and ship receiver related data, the waterway congestion assessment coefficient, the ship signal impact assessment coefficient and the ship receiver impact assessment coefficient are obtained, thereby achieving the improvement of the real-time performance of obtaining the port flow related data, and then achieving the improvement of the reliability of obtaining the port flow related data.

[0021] 3. The channel congestion assessment coefficient is obtained through the ship distance deviation and the ship flow deviation. Then, the ship signal impact assessment coefficient is obtained by combining the reflection loss deviation and the channel congestion assessment coefficient of the preset second time period. Finally, the ship receiver impact assessment coefficient is obtained by combining the initial space loss, space loss deviation and the channel congestion assessment coefficient of the preset second time period, thereby achieving accurate quantification of port flow optimization scheduling, and then achieving improved reliability of port flow optimization scheduling. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] Figure 1 A schematic diagram of the structure of a port flow optimization and scheduling system based on IoT big data provided in an embodiment of the present application;

[0023] Figure 2 A statistical chart showing changes in the waterway congestion assessment coefficient provided in an embodiment of the present application;

[0024] Figure 3 A flowchart of a port flow optimization scheduling method based on IoT big data provided in an embodiment of the present application;

[0025] Figure 4 This is a general flow chart provided for the embodiments of this application. DETAILED DESCRIPTION

[0026] The embodiments of the present application solve the problem of inaccurate port flow data collection in the process of port flow optimization and scheduling in the prior art by providing a port flow optimization and scheduling system and method based on Internet of Things big data. By obtaining ship congestion-related data, ship signal-related data and ship receiver-related data, and then obtaining a channel congestion assessment coefficient based on the ship congestion-related data and the reference ship congestion data, and judging whether to obtain a ship signal impact assessment coefficient, then obtaining a ship signal impact assessment coefficient based on the channel congestion assessment coefficient, the ship signal-related data and the reference ship signal data within a preset second time period and judging whether to perform a signal impact adjustment, finally obtaining a ship receiver impact assessment coefficient based on the channel congestion assessment coefficient, the ship receiver-related data and the reference ship receiver data within the preset second time period and judging whether to perform a receiver impact adjustment, thereby improving the accuracy of port flow data collection in the process of port flow optimization and scheduling.

[0027] The technical solution in the embodiment of the present application is to solve the problem of inaccurate port flow data collection during the above-mentioned port flow optimization and scheduling process. The overall idea is as follows:

[0028] The obtained channel congestion assessment coefficient is used to determine whether to obtain the ship signal impact assessment coefficient, and then the obtained ship signal impact assessment coefficient is used to determine whether to perform signal impact adjustment. Finally, the obtained ship receiver impact assessment coefficient is used to determine whether to perform receiver impact adjustment, thereby achieving the effect of improving the accuracy of port flow data collection during port flow optimization scheduling.

[0029] In order to better understand the above technical solution, the above technical solution will be described in detail below with reference to the accompanying drawings and specific implementation methods.

[0030] like Figure 1 As shown, it is a structural diagram of the port flow optimization and scheduling system based on Internet of Things big data provided by an embodiment of the present application, including a data acquisition module, a congestion assessment module, a signal impact assessment module and a receiver impact assessment module: wherein the data acquisition module is used to obtain ship congestion-related data, ship signal-related data and ship receiver-related data through preset port ship monitoring equipment, the ship congestion-related data is used to describe the port channel congestion situation, the ship signal-related data is used to describe the impact of port channel congestion on port ship signals, and the ship receiver-related data is used to describe the impact of port channel congestion on receivers monitoring port channels; the congestion assessment module is used to obtain a channel congestion assessment coefficient based on the acquired ship congestion-related data and reference ship congestion data within a preset first time period, and judge whether to obtain a ship signal impact assessment coefficient based on the acquired channel congestion assessment coefficient, and the channel congestion assessment coefficient is used to evaluate the port channel congestion situation; the signal impact assessment module is used to obtain a channel congestion assessment coefficient based on the acquired ship congestion-related data and reference ship congestion data within a preset second time period. A ship signal impact assessment coefficient is obtained based on the obtained channel congestion assessment coefficient, ship signal related data and reference ship signal data, and whether to perform signal impact adjustment is determined based on the obtained ship signal impact assessment coefficient. The signal impact adjustment is used to adjust the ship signal impact assessment coefficient to no higher than a preset signal impact threshold. The ship signal impact assessment coefficient is used to evaluate the degree of impact of port channel congestion on port ship signals; the receiver impact assessment module is used to obtain the ship receiver impact assessment coefficient based on the obtained channel congestion assessment coefficient, ship receiver related data and reference ship receiver data within a preset second time period, and determine whether to perform receiver impact adjustment based on the obtained ship receiver impact assessment coefficient. Port flow optimization scheduling is performed based on the signal impact adjustment and receiver impact adjustment. The receiver impact adjustment is used to adjust the ship receiver impact assessment coefficient to no higher than the preset receiver impact threshold. The ship receiver impact assessment coefficient is used to evaluate the degree of impact of the port channel congestion condition on the receiver monitoring the port channel.

[0031] In this embodiment, extreme weather conditions such as storms, typhoons, heavy rain, heavy fog, and heavy snow can directly impact ship navigation safety and port operational efficiency. For example, severe weather can damage port facilities, preventing ships from safely berthing or unberthing, and thus causing congestion. Signal impact adjustment and receiver impact adjustment help ensure smooth port operations, improve the speed and safety of ship entry and exit, and enhance the port's ability to respond to sudden congestion situations, laying a solid foundation for the port's long-term development. Big data technology can efficiently analyze large amounts of data to extract reference ship congestion data, reference ship signal data, and reference ship receiver data. Internet of Things technology enables real-time monitoring of port operations by installing a predetermined number of GPS (Global Positioning System) sensors and AI (Automatic Identification System) sensors at predetermined monitoring points on port facilities, ships, and cargo, thereby improving the accuracy of port flow data collection during port flow optimization and scheduling.

[0032] It should be understood that the preset port ship monitoring equipment includes radar, timer and spectrum analyzer; ship congestion related data includes the number of ships, passing time and signal round-trip time; ship signal related data includes signal round-trip time and signal wavelength; ship receiver related data includes the number of paths, transmission and reception distance and signal frequency.

[0033] The number of paths indicates the number of signal paths that the signal reflected from the ship takes to reach the receiver; the transmit-receive spacing indicates the distance between the ship and the receiver.

[0034] Specifically, in this embodiment, the radar continuously scans the channel area to identify and record the number of ships that appear within a preset first time period to represent the number of ships. The time points when ships enter and leave the channel area within the first time period are recorded by a timer to obtain the passage time of the ships in the channel. The time difference between the time when the ship transmits the signal and the time when the adjacent ship receives the reflected signal within the first preset time period is recorded by a timer to represent the passage time and round-trip time of the ship. The spectrum analyzer measures the signal wavelength and combines the round-trip time of the signal and the signal propagation speed (such as the speed of light) to obtain the distance between the transmitting point and the receiving point, that is, the transmitting-receiving distance. The spectrum analyzer separates the mixed signals, monitors the changes in the characteristics of the signal (such as amplitude, phase, etc.) based on the signal separation, identifies the number of signal paths, that is, the number of paths, and measures the signal frequency by the spectrum analyzer and displays the spectrum of the measured signal.

[0035] The preset first time period represents the preset time period in the process of port flow statistics; the preset second time period represents the preset time period corresponding to when the channel congestion assessment coefficient in the preset first time period is not lower than the preset congestion threshold, and the interval length of the preset second time period and the preset first time period is the same.

[0036] The reference ship congestion data includes a preset ship distance threshold, a preset ship flow threshold and the speed of light; the reference ship signal data includes a preset reflection loss threshold and the speed of light; the reference ship receiver data includes a preset multipath ship loss threshold, the speed of light and the preset free space loss threshold; the reference ship congestion data, the reference ship signal data and the reference ship receiver data are obtained from the preset database through big data technology. The preset ship distance threshold is represented by the average value of the ship distance in the historical time period in the preset data, and the preset ship flow threshold is represented by the average value of the ship flow in the historical time period in the preset data. The speed of light is generally 3*10 8 , in meters per second. The preset reflection loss threshold is represented by the average value of the reflection loss in the historical time period in the preset data. The preset multipath ship loss threshold is represented by the average value of the multipath ship loss in the historical time period in the preset data. The preset free space loss threshold is represented by the average value of the free space loss in the historical time period in the preset data.

[0037] Furthermore, the specific process of obtaining the waterway congestion assessment coefficient based on the acquired ship congestion-related data and the reference ship congestion data within the preset first time period is as follows: A1, obtaining the initial ship distance through the signal round-trip time and the speed of light, and the initial ship distance is represented by the result of multiplying the signal round-trip time and the speed of light; A2, obtaining the initial ship distance deviation through the initial ship distance and the preset ship distance threshold, and the initial ship distance deviation is represented by the result of adding the initial ship distance and the preset ship distance threshold; A3, obtaining the ship distance deviation through the initial ship distance deviation and the preset ship distance threshold, and the ship distance deviation is represented by the result of the ratio operation between the initial ship distance deviation and the twice of the preset ship distance threshold, and the ship distance deviation is used to reflect A4, obtains the initial ship flow through the number of ships and the length of time of passing, and the initial ship flow is expressed by the ratio operation of the number of ships and the length of time of passing; A5, obtains the initial ship flow deviation through the initial ship flow and the preset ship flow threshold, and the initial ship flow deviation is expressed by the result of adding the initial ship flow and the preset ship flow threshold; A6, obtains the ship flow deviation through the initial ship flow deviation and the preset ship flow threshold, and the ship flow deviation is expressed by the result of the ratio operation of the initial ship flow deviation and twice the preset ship flow threshold, and the ship flow deviation is used to reflect the degree of deviation of the ship flow; A7, obtains the waterway congestion assessment coefficient by combining the ship distance deviation and the ship flow deviation.

[0038] Among them, the restricted expression of the waterway congestion assessment coefficient is as follows:

[0039]

[0040] In the formula, YD q It represents the channel congestion assessment coefficient of the port channel in the qth preset first time period, q=1,2,..,n, q represents the number of the preset first time period, n represents the total number of preset first time periods, It represents the ship distance deviation of the port channel in the qth preset first time period, It represents the ship flow deviation of the port channel in the qth preset first time period, represents the initial ship distance of the port channel in the qth preset first time period, represents the initial ship flow in the port channel during the qth preset first time period, represents the number of ships in the port channel in the qth preset first time period, Indicates the duration of passage through the port channel in the qth preset first time period, It represents the round trip time of the signal of the port channel in the qth preset first time period, Indicates the preset ship distance threshold, The ship flow threshold is preset, c represents the speed of light, and e represents a natural constant.

[0041] In this embodiment, the algorithm of this embodiment combines the ship congestion-related data for comprehensive analysis to obtain the waterway congestion assessment coefficient. The ship congestion-related data in the algorithm of this embodiment do not exist independently, but are interrelated. The more ships there are, the shorter the signal round-trip time is, which does not mean that the waterway congestion assessment coefficient is larger. The impact of the transit time should also be comprehensively analyzed. An increase in the number of ships often leads to an increase in transit time. This is because more ships need to load and unload cargo at the port, which will extend the stay time of each ship in the port. In addition, an increase in the number of ships may also lead to waterway congestion, further increasing the waiting time of ships. An increase in the number of ships may affect the transmission efficiency of the signal, because more ships mean more communication needs. In a high-density ship traffic environment, the sending and receiving of signals may be interfered with, resulting in an increase in the signal round-trip time. The parameters of the algorithm of this embodiment need to be considered together and simultaneously to affect the results.

[0042] Specifically, assuming that the ship distance deviation The range is 0.6-1.5, the ship flow deviation The range is 0.6-1.5, such as Figure 2 As shown in the figure, it is a statistical diagram of the change of the waterway congestion assessment coefficient provided in this embodiment, which is obtained by Figure 2 It can be seen that when the ship flow deviation Fixed to 1, varies with ship distance The channel congestion assessment coefficient gradually decreases, which means that the degree of ship congestion gradually decreases; when the ship distance deviation Fixed to 1, with the deviation of ship traffic The channel congestion assessment coefficient gradually increases, which means that the degree of ship congestion gradually increases; the accurate quantification of ship congestion is achieved, and then the accuracy of port flow data collection in the process of port flow optimization scheduling is improved.

[0043] Specifically, the specific process of determining whether to obtain the ship signal impact assessment coefficient based on the obtained channel congestion assessment coefficient is as follows: determine whether the channel congestion assessment coefficient is not lower than the preset congestion threshold, and obtain the ship signal impact assessment coefficient when the channel congestion assessment coefficient is not lower than the preset congestion threshold; when the channel congestion assessment coefficient is lower than the preset congestion threshold, send a prompt to the preset personnel to remind them that the current channel congestion level is low and perform port flow scheduling.

[0044] It should be understood that the preset congestion threshold is represented by the variance of ship traffic in the historical time period in the preset data. Port traffic scheduling includes adjusting the order of ships entering and leaving the port, optimizing berth allocation, coordinating the time intervals between ships, etc.

[0045] Furthermore, the specific process of judging whether to perform signal impact adjustment based on the acquired ship signal impact assessment coefficient is as follows: LL1, judging whether the ship signal impact assessment coefficient is not higher than the preset signal impact threshold, if the ship signal impact assessment coefficient is not higher than the preset signal impact threshold, no signal impact adjustment is performed, otherwise LL2 is executed; LL2, performing noise filtering, when the monitored ship signal impact assessment coefficient is not higher than the preset signal impact threshold, the signal impact adjustment is stopped, otherwise LL3 is executed, noise filtering means filtering the noise and interference caused by congestion through an anti-interference algorithm; LL3, performing transmission time period adjustment, when the monitored ship signal impact assessment coefficient is not higher than the preset signal impact threshold, the signal impact adjustment is stopped, otherwise feedback is given to the preset personnel to issue an alarm prompt, and the transmission time period adjustment means allowing the ship to transmit signals in different time periods through time division multiplexing method.

[0046] In this embodiment, the preset signal impact threshold is represented by the variance of ship transmission losses within a historical time period in preset data. Noise filtering includes the fact that in the event of port channel congestion, signal transmission between ships may be subject to various forms of interference, such as signal collision and signal attenuation. The anti-interference algorithm can analyze the received signal, identify the noise component therein, and separate it from the original signal. Transmission time period adjustment means dividing time into a preset number of time slots and allowing each time slot to transmit signals separately. In the event of port channel congestion, by changing the ship's transmission time period, signal collision and interference caused by multiple ships transmitting signals simultaneously can be avoided. By filtering noise and optimizing the transmission time period, the impact of congestion on ship signal transmission is reduced, thereby improving port operating efficiency and signal transmission quality.

[0047] Furthermore, the specific process of obtaining the ship signal impact assessment coefficient based on the obtained channel congestion assessment coefficient, ship signal related data and reference ship signal data within the preset second time period is as follows: B1, the initial ship distance and signal wavelength are processed to obtain the initial reflection loss, and the initial reflection loss is represented by the result of the logarithmic operation of the initial ship distance and the signal wavelength; B2, the initial reflection loss deviation is obtained through the initial reflection loss and the preset reflection loss threshold, and the initial reflection loss deviation is represented by the result of the addition operation of the initial reflection loss and the preset reflection loss threshold; B3, the reflection loss deviation is obtained through the initial reflection loss deviation and the preset reflection loss threshold, and the reflection loss deviation is represented by the result of the ratio operation of the initial reflection loss deviation and twice the preset reflection loss threshold, and the reflection loss deviation is used to reflect the deviation of the signal loss during transmission when encountering an adjacent ship; B4, the ship signal impact assessment coefficient is obtained by combining the reflection loss deviation and the channel congestion assessment coefficient of the preset second time period.

[0048] Among them, the limiting expression of the ship signal impact assessment coefficient is as follows:

[0049]

[0050] Where, XH s Indicates the ship signal impact assessment coefficient of the s-th preset second time period, s=1,2,..,g, s represents the number of the preset second time period, g represents the total number of preset second time periods, Indicates the reflection loss deviation of the sth preset second time period, YD s represents the waterway congestion assessment coefficient for the sth preset second time period, represents the initial reflection loss of the s-th preset second time period, represents the initial ship distance of the port channel in the sth preset second time period, represents the signal wavelength of the s-th preset second time period, represents the preset return loss threshold, and e represents a natural constant.

[0051] In this embodiment, the waterway congestion assessment coefficient YD of the sth preset second time period is s , represents the channel congestion assessment coefficient corresponding to when the channel congestion assessment coefficient in the preset first time period is not less than the preset congestion threshold. The algorithm of this embodiment combines the ship signal related data for comprehensive analysis to obtain the ship signal impact assessment coefficient. The ship signal related data in the algorithm of this embodiment does not exist independently and are interrelated. The longer the initial ship distance, the larger the channel congestion assessment coefficient in the preset second time period. This does not mean that the ship signal impact assessment coefficient is larger. The influence of the signal wavelength should also be comprehensively considered. The signal round-trip time may be affected by channel congestion. When the channel is congested, communication between ships may increase, resulting in delays in signal transmission, thereby increasing the signal round-trip time. At the same time, an increase in the channel congestion assessment coefficient means an increase in the density of ships in the channel, which may lead to more signal interference and communication delays, further affecting the signal round-trip time. Signals with longer wavelengths may produce greater reflection and scattering on the ship structure, which may also affect the signal propagation efficiency. The parameters of the algorithm of this embodiment need to be considered together and simultaneously in their impact on the results.

[0052] Specifically, assuming the return loss deviation The range is 0.6-1, and the channel congestion assessment coefficient YD for the second time period is preset s The range is 0.1-1, as shown in Table 1, which is a statistical table of changes in the ship signal impact assessment coefficient provided in this embodiment:

[0053] Table 1 Statistics of changes in ship signal impact assessment coefficients

[0054]

[0055] As shown in Table 1, as the reflection loss deviation And the channel congestion assessment coefficient YD for the preset second time period s The ship signal impact assessment coefficient XH s The gradual increase means that the impact of port channel congestion on port ship signals is gradually increasing; the accurate quantification of the impact of port channel congestion on port ship signals is achieved, thereby improving the accuracy of port flow data collection during port flow optimization and scheduling.

[0056] Furthermore, the specific process of determining whether to perform receiver impact adjustment based on the acquired ship receiver impact assessment coefficient is as follows: KK1, determining whether the ship receiver impact assessment coefficient is not higher than the preset receiver impact threshold. If the ship receiver impact assessment coefficient is not higher than the preset receiver impact threshold, no receiver impact adjustment is performed, otherwise KK2 is executed; KK2, compressing the transmitted data. When the monitored ship receiver impact assessment coefficient is not higher than the preset receiver impact threshold, the receiver impact adjustment is stopped, otherwise KK3 is executed. Compressing the transmitted data is used to reduce the network burden to improve the quality of the ship's transmitted signal to the receiver; KK3, sending a prompt to the preset personnel to adjust the position of the receiver at a preset angle. When the monitored ship receiver impact assessment coefficient is not higher than the preset receiver impact threshold, the receiver impact adjustment is stopped, otherwise an alarm prompt is issued.

[0057] Specifically, the preset receiver impact threshold is represented by the variance of the ship's free space loss within a historical time period in the preset data. Compressed transmission data uses data compression technology to reduce the size of the transmitted data, thereby reducing network transmission latency and bandwidth usage. During the receiver position adjustment phase, the system prompts the preset personnel to adjust the receiver's position based on the preset angle. The receiver includes an antenna, RF amplifier, GPS receiver, etc. Adjusting the receiver's position can improve the signal transmission path between the receiver and the ship's transmitter, reduce signal attenuation and interference, and ensure that the receiver can accurately and stably receive signals transmitted by the ship, thereby improving the quality of signal reception and, in turn, improving the accuracy of port flow data collection during port flow optimization and scheduling.

[0058] Furthermore, the specific process of obtaining the ship receiver impact assessment coefficient based on the acquired channel congestion assessment coefficient, the ship receiver related data and the reference ship receiver data within the preset second time period is as follows: C1, the number of paths is processed to obtain the initial propagation loss, and the initial propagation loss is represented by the result of the logarithmic operation of the number of paths; C2, the initial propagation loss deviation is obtained through the initial propagation loss and the preset multipath ship loss threshold, and the initial propagation loss deviation is represented by the result of the addition operation of the initial propagation loss and the preset multipath ship loss threshold; C3, the propagation loss deviation is obtained through the initial propagation loss deviation and the preset multipath ship loss threshold, and the propagation loss deviation is represented by the result of the ratio operation of the initial propagation loss deviation and twice the preset multipath ship loss threshold. The propagation loss deviation is used to reflect the deviation of the multipath propagation loss between the ship reflection signal and the receiver. C4, the transmitting and receiving distance, signal frequency and speed of light are processed to obtain the initial space loss, and the initial space loss is represented by the result of the logarithmic operation of the transmitting and receiving distance, signal frequency and speed of light; C5, the initial space loss deviation is obtained by the initial space loss and the preset free space loss threshold, and the initial space loss deviation is represented by the result of the addition operation of the initial space loss and the preset free space loss threshold; C6, the space loss deviation is obtained by the initial space loss deviation and the preset free space loss threshold, and the space loss deviation is represented by the result of the ratio operation of the initial space loss deviation and twice the preset free space loss threshold, and the space loss deviation is used to reflect the deviation of the free space loss between the ship's reflected signal and the receiver; C7, the ship receiver impact assessment coefficient is obtained by combining the initial space loss, the space loss deviation and the preset channel congestion assessment coefficient of the second time period.

[0059] Among them, the limiting expression of the ship receiver impact assessment coefficient is as follows:

[0060]

[0061] Where, JS s Indicates the ship receiver impact assessment coefficient of the s-th preset second time period, s=1,2,..,g, s represents the number of the preset second time period, g represents the total number of preset second time periods, represents the propagation loss deviation of the s-th preset second time period, Indicates the space loss deviation of the sth preset second time period, YD s represents the waterway congestion assessment coefficient for the sth preset second time period, represents the initial propagation loss of the s-th preset second time period, represents the initial space loss of the s-th preset second time period, represents the number of paths in the sth preset second time period, represents the transmission and reception distance of the sth preset second time period, represents the signal frequency of the s-th preset second time period, represents the preset multipath ship loss threshold, c represents the speed of light, Indicates the preset free space loss threshold.

[0062] In this embodiment, the waterway congestion assessment coefficient YD of the sth preset second time period is s , represents the corresponding channel congestion assessment coefficient when the channel congestion assessment coefficient during the preset first time period is no less than the preset congestion threshold. The algorithm of this embodiment combines ship receiver-related data with comprehensive analysis to derive the ship receiver impact assessment coefficient. The ship receiver-related data in this embodiment's algorithm are not independent and are interrelated. A greater number of paths, a longer transmit-receive distance, and a higher signal frequency do not necessarily result in a higher ship receiver impact assessment coefficient. The impact of the channel congestion assessment coefficient during the preset second time period should also be considered. The number of paths may be affected by the transmit-receive distance. A larger transmit-receive distance may result in more paths covered by the signal, thereby increasing the number of paths. In congested waterways, to ensure effective signal transmission, it may be necessary to reduce the transmit-receive distance to improve signal reliability. The transmit-receive distance may be affected by signal frequency. Different signal frequencies may require different transmit-receive distances to optimize signal transmission. For example, high-frequency signals may require shorter distances to reduce signal attenuation. The algorithm parameters of this embodiment must be considered together to influence the results. This achieves accurate quantification of the impact of port channel congestion on ship receivers, thereby improving the accuracy of port flow data collection during port flow optimization and scheduling.

[0063] like Figure 3As shown, it is a flow chart of the port flow optimization and scheduling method based on the Internet of Things big data provided in an embodiment of the present application. The port flow optimization and scheduling method based on the Internet of Things big data provided in an embodiment of the present application includes the following steps: S1, obtaining data: obtaining ship congestion-related data, ship signal-related data and ship receiver-related data through preset port ship monitoring equipment, the ship congestion-related data is used to describe the port channel congestion situation, the ship signal-related data is used to describe the impact of port channel congestion on port ship signals, and the ship receiver-related data is used to describe the impact of port channel congestion on receivers monitoring port channels; S2, obtaining a channel congestion assessment coefficient: obtaining a channel congestion assessment coefficient according to the obtained ship congestion-related data and reference ship congestion data within a preset first time period, judging whether to obtain a ship signal impact assessment coefficient based on the obtained channel congestion assessment coefficient, and judging whether to obtain a ship signal impact assessment coefficient based on the obtained channel congestion assessment coefficient, and the channel congestion assessment coefficient is used to assess the port channel congestion situation; S3, obtaining a ship signal impact assessment coefficient: obtaining a ship signal impact assessment coefficient within a preset second time period A ship signal impact assessment coefficient is obtained based on the obtained channel congestion assessment coefficient, ship signal related data and reference ship signal data, and whether to perform signal impact adjustment is determined based on the obtained ship signal impact assessment coefficient. The signal impact adjustment is used to adjust the ship signal impact assessment coefficient to no higher than a preset signal impact threshold. The ship signal impact assessment coefficient is used to assess the degree of impact of port channel congestion on port ship signals; S4, obtaining a ship receiver impact assessment coefficient: within a preset second time period, a ship receiver impact assessment coefficient is obtained based on the obtained channel congestion assessment coefficient, ship receiver related data and reference ship receiver data, and whether to perform receiver impact adjustment is determined based on the obtained ship receiver impact assessment coefficient. Port flow optimization scheduling is performed based on the signal impact adjustment and the receiver impact adjustment. The receiver impact adjustment is used to adjust the ship receiver impact assessment coefficient to no higher than a preset receiver impact threshold. The ship receiver impact assessment coefficient is used to assess the degree of impact of the port channel congestion condition on the receiver monitoring the port channel.

[0064] like Figure 4 As shown, this is the overall flow chart provided by the embodiment of the present application. The waterway congestion assessment coefficient is a direct indicator for assessing the congestion status of the port waterway. It is also the basis for obtaining the ship signal impact assessment coefficient and the ship receiver impact assessment coefficient. The waterway congestion assessment coefficient, the ship signal impact assessment coefficient and the ship receiver impact assessment coefficient are interdependent in the assessment process. Through signal impact adjustment and receiver impact adjustment, not only can the interference of congestion on ship signal transmission be effectively reduced and the port operation efficiency be improved, but the negative impact of congestion on the overall port operation can also be significantly reduced, thereby achieving optimized scheduling and efficient management of port traffic. Strengthening the coordinated management of port facilities and equipment, ensuring information sharing and linkage control between various devices, and realizing the improvement of the accuracy of port traffic data collection in the process of port traffic optimization scheduling.

[0065] To sum up, the embodiment of the present application obtains the waterway congestion assessment coefficient through ship congestion related data and reference ship congestion data and determines whether to obtain the ship signal impact assessment coefficient, then obtains the ship signal impact assessment coefficient based on the ship signal related data and the reference ship signal data and determines whether to perform signal impact adjustment, and finally obtains the ship receiver impact assessment coefficient based on the ship receiver related data and the reference ship receiver data and determines whether to perform receiver impact adjustment, thereby realizing dynamic quantification of port flow scheduling, and then realizing the improvement of the accuracy of port flow data collection in the process of port flow optimization scheduling, effectively solving the problem of inaccurate port flow data collection in the process of port flow optimization scheduling in the prior art.

[0066] It will be understood by those skilled in the art that embodiments of the present invention may be provided as methods, systems, or computer program products. Thus, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware. Furthermore, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to magnetic disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0067] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowcharts and / or block diagrams, as well as combinations of processes and / or blocks in the flowcharts and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowcharts and / or block diagrams. Figure 1 a process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0068] These computer program instructions may also be stored in a computer readable memory that can direct a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 a process or multiple processes and / or boxes Figure 1 The function specified in one or more boxes.

[0069] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operational steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing the instructions executed on the computer or other programmable device for implementing the process. Figure 1 a process or multiple processes and / or boxes Figure 1 The steps for the function specified in one or more boxes.

[0070] Although the preferred embodiments of the present invention have been described, those skilled in the art may make additional changes and modifications to these embodiments once they have learned the basic creative concept. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications that fall within the scope of the present invention.

[0071] Obviously, those skilled in the art may make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if such changes and modifications fall within the scope of the claims and their equivalents, the present invention is intended to include such changes and modifications.

Claims

1. The port flow optimization and scheduling system based on IoT big data is characterized by: Including data acquisition module, congestion assessment module, signal impact assessment module and receiver impact assessment module: The data acquisition module is used to acquire ship congestion related data, ship signal related data and ship receiver related data through preset port ship monitoring equipment; The congestion assessment module is used to obtain a waterway congestion assessment coefficient based on the acquired ship congestion-related data and reference ship congestion data within a preset first time period, and determine whether to obtain a ship signal impact assessment coefficient based on the acquired waterway congestion assessment coefficient, wherein the waterway congestion assessment coefficient is used to assess the congestion status of the port waterway; The signal impact assessment module is used to obtain a ship signal impact assessment coefficient based on the acquired channel congestion assessment coefficient, ship signal related data and reference ship signal data within a preset second time period, and determine whether to perform signal impact adjustment based on the acquired ship signal impact assessment coefficient. The ship signal impact assessment coefficient is used to assess the degree of impact of port channel congestion on port ship signals; The receiver impact assessment module is used to obtain a ship receiver impact assessment coefficient based on the acquired channel congestion assessment coefficient, ship receiver-related data and reference ship receiver data within a preset second time period, determine whether to perform receiver impact adjustment based on the acquired ship receiver impact assessment coefficient, and perform port flow optimization scheduling based on the signal impact adjustment and the receiver impact adjustment, wherein the ship receiver impact assessment coefficient is used to assess the degree of impact of the port channel congestion condition on the receiver monitoring the port channel; The preset port ship monitoring equipment includes radar, timer and spectrum analyzer; The ship congestion related data includes the number of ships, passing time and signal round-trip time; Said ship signal related data includes signal round trip time and signal wavelength; Said ship receiver related data includes the number of paths, the transmission and reception distance and the signal frequency; The number of paths represents the number of signal paths for a signal reflected from a ship to reach a receiver; The preset first time period represents a preset time period during the process of performing port flow statistics; The preset second time period refers to a preset time period corresponding to when the waterway congestion assessment coefficient is not lower than the preset congestion threshold value in the preset first time period, and the interval between the preset second time period and the preset first time period is the same in length; The reference ship congestion data includes a preset ship distance threshold, a preset ship flow threshold and the speed of light; The reference ship signal data includes a preset reflection loss threshold and light speed; The reference vessel receiver data includes a preset multipath vessel loss threshold, a speed of light, and a preset free space loss threshold; The specific process of obtaining the waterway congestion assessment coefficient based on the acquired ship congestion related data and the reference ship congestion data within the preset first time period is as follows: A1, obtaining an initial ship distance by using the signal round-trip time and the speed of light, wherein the initial ship distance is represented by the product of the signal round-trip time and the speed of light; A2, obtaining an initial ship distance deviation by using the initial ship distance and a preset ship distance threshold, wherein the initial ship distance deviation is represented by a result of adding the initial ship distance and the preset ship distance threshold; A3, obtaining a ship distance deviation based on the initial ship distance deviation and a preset ship distance threshold, wherein the ship distance deviation is represented by a ratio calculation result of the initial ship distance deviation and twice the preset ship distance threshold; A4, obtaining an initial ship flow rate by calculating the number of passing ships and the passing time, wherein the initial ship flow rate is represented by the result of calculating the ratio of the number of ships to the passing time; A5, obtaining an initial ship flow deviation by using the initial ship flow and a preset ship flow threshold, wherein the initial ship flow deviation is represented by a result of adding the initial ship flow and the preset ship flow threshold; A6, obtaining a ship flow deviation by using the initial ship flow deviation and a preset ship flow threshold, wherein the ship flow deviation is represented by a ratio calculation result of the initial ship flow deviation and twice the preset ship flow threshold; A7, combining the ship distance deviation and the ship flow deviation to obtain the channel congestion assessment coefficient; The specific process of obtaining the ship signal impact assessment coefficient according to the obtained waterway congestion assessment coefficient, the ship signal related data and the reference ship signal data within the preset second time period is as follows: B1, processing the initial ship distance and the signal wavelength to obtain an initial reflection loss, wherein the initial reflection loss is represented by a result of a logarithmic operation of the initial ship distance and the signal wavelength; B2, obtaining an initial return loss deviation through the initial return loss and a preset return loss threshold, wherein the initial return loss deviation is represented by a result of adding the initial return loss and the preset return loss threshold; B3, obtaining a return loss deviation by using the initial return loss deviation and a preset return loss threshold, wherein the return loss deviation is represented by a ratio operation result of the initial return loss deviation and twice the preset return loss threshold; B4, combining the reflection loss deviation and the channel congestion assessment coefficient of the preset second time period to obtain a ship signal impact assessment coefficient; The specific process of obtaining the ship receiver impact assessment coefficient according to the obtained waterway congestion assessment coefficient, the ship receiver related data and the reference ship receiver data within the preset second time period is as follows: C1, processing the number of paths to obtain an initial propagation loss, wherein the initial propagation loss is represented by the result of a logarithmic operation on the number of paths; C2, obtaining an initial propagation loss deviation by using the initial propagation loss and a preset multipath ship loss threshold, wherein the initial propagation loss deviation is represented by a result of adding the initial propagation loss to the preset multipath ship loss threshold; C3, obtaining a propagation loss deviation based on the initial propagation loss deviation and a preset multipath ship loss threshold, wherein the propagation loss deviation is represented by a ratio calculation result of the initial propagation loss deviation and twice the preset multipath ship loss threshold; C4, processing the transmitting and receiving distance, signal frequency and light speed to obtain an initial spatial loss, wherein the initial spatial loss is represented by the result of a logarithmic operation of the transmitting and receiving distance, signal frequency and light speed; C5, obtaining an initial space loss deviation by using the initial space loss and a preset free space loss threshold, wherein the initial space loss deviation is represented by a result of adding the initial space loss and the preset free space loss threshold; C6, obtaining a space loss deviation by using the initial space loss deviation and a preset free space loss threshold, wherein the space loss deviation is represented by a ratio calculation result of the initial space loss deviation and twice the preset free space loss threshold; C7, combining the initial space loss, the space loss deviation and the channel congestion assessment coefficient of the preset second time period to obtain the ship receiver impact assessment coefficient.

2. The port flow optimization and scheduling system based on Internet of Things big data as claimed in claim 1 is characterized in that: The restricted expression of the waterway congestion assessment coefficient is as follows: In the formula, YD q It represents the channel congestion assessment coefficient of the port channel in the qth preset first time period, q=1,2,..,n, q represents the number of the preset first time period, n represents the total number of preset first time periods, It represents the ship distance deviation of the port channel in the qth preset first time period, It represents the ship flow deviation of the port channel in the qth preset first time period, represents the initial ship distance of the port channel in the qth preset first time period, represents the initial ship flow in the port channel during the qth preset first time period, represents the number of ships in the port channel in the qth preset first time period, Indicates the duration of passage through the port channel in the qth preset first time period, It represents the round trip time of the signal of the port channel in the qth preset first time period, Indicates the preset ship distance threshold, The ship flow threshold is preset, c represents the speed of light, and e represents a natural constant.

3. The port flow optimization and scheduling system based on Internet of Things big data as claimed in claim 2 is characterized in that: The specific process of determining whether to obtain the ship signal impact assessment coefficient based on the obtained waterway congestion assessment coefficient is as follows: Determine whether the waterway congestion assessment coefficient is not lower than a preset congestion threshold; When the waterway congestion assessment coefficient is lower than the preset congestion threshold, a prompt is sent to the preset personnel to prompt port flow scheduling.

4. The port flow optimization and scheduling system based on Internet of Things big data as claimed in claim 1 is characterized in that: The specific process of determining whether to perform signal impact adjustment based on the acquired ship signal impact assessment coefficient is as follows: LL1: Determine whether the ship signal impact assessment coefficient is not higher than the preset signal impact threshold. If the ship signal impact assessment coefficient is not higher than the preset signal impact threshold, no signal impact adjustment is performed. Otherwise, LL2 is executed. LL2, performs noise filtering. When the monitored ship signal impact assessment coefficient is not higher than the preset signal impact threshold, the signal impact adjustment is stopped. Otherwise, LL3 is executed; LL3, adjust the transmission time period. When the monitored ship signal impact assessment coefficient is not higher than the preset signal impact threshold, stop the signal impact adjustment. Otherwise, feedback is given to the preset personnel to issue an alarm prompt.

5. The port flow optimization and scheduling system based on Internet of Things big data as claimed in claim 1 is characterized in that: The specific process of determining whether to perform receiver impact adjustment based on the obtained ship receiver impact assessment coefficient is as follows: KK1, determines whether the ship receiver impact assessment coefficient is not higher than the preset receiver impact threshold. If the ship receiver impact assessment coefficient is not higher than the preset receiver impact threshold, no receiver impact adjustment is performed. Otherwise, KK2 is executed; KK2, compresses the transmission data. When the monitored ship receiver impact assessment coefficient is not higher than the preset receiver impact threshold, the receiver impact adjustment is stopped. Otherwise, KK3 is executed; KK3 sends a prompt to the preset personnel to adjust the position of the receiver at a preset angle. When the monitored ship receiver impact assessment coefficient is not higher than the preset receiver impact threshold, the receiver impact adjustment is stopped. Otherwise, an alarm prompt is issued.

6. A port traffic optimization scheduling method based on IoT big data is characterized by: The method is implemented by the port flow optimization and scheduling system based on Internet of Things big data according to any one of claims 1 to 5, and comprises the following steps: S1, obtaining ship congestion related data, ship signal related data and ship receiver related data through preset port ship monitoring equipment; S2, obtaining a waterway congestion assessment coefficient based on the acquired ship congestion-related data and reference ship congestion data within a preset first time period, and determining whether to obtain a ship signal impact assessment coefficient based on the acquired waterway congestion assessment coefficient, wherein the waterway congestion assessment coefficient is used to assess the port waterway congestion condition; S3, obtaining a ship signal impact assessment coefficient based on the obtained channel congestion assessment coefficient, the ship signal-related data, and the reference ship signal data within a preset second time period, and determining whether to perform a signal impact adjustment based on the obtained ship signal impact assessment coefficient, wherein the ship signal impact assessment coefficient is used to assess the degree of impact of port channel congestion on port ship signals; S4, obtaining a ship receiver impact assessment coefficient based on the acquired channel congestion assessment coefficient, ship receiver related data and reference ship receiver data within a preset second time period, judging whether to perform receiver impact adjustment based on the acquired ship receiver impact assessment coefficient, and performing port flow optimization scheduling based on the signal impact adjustment and the receiver impact adjustment, wherein the ship receiver impact assessment coefficient is used to evaluate the degree of impact of the port channel congestion condition on the receiver monitoring the port channel.

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