Port traffic optimization scheduling system and method based on Internet of Things big data

Abstract

The invention discloses a port traffic optimization scheduling system and method based on Internet of Things big data, and relates to the technical field of electric digital data processing. The port traffic optimization scheduling system based on the Internet of Things big data comprises a data acquisition module, a congestion evaluation module, a signal influence evaluation module and a receiver influence evaluation module. According to the method, the channel congestion evaluation coefficient is obtained through the ship congestion related data, whether the ship signal influence evaluation coefficient is obtained or not is judged, then the ship signal influence evaluation coefficient is obtained according to the ship signal related data, and whether signal influence adjustment is carried out or not is judged; and finally, obtaining a ship receiver influence evaluation coefficient according to the related data of the ship receiver, and judging whether receiver influence adjustment is carried out or not, thereby achieving the effect of improving the collection accuracy of the port flow data in the port flow optimization scheduling process. The problem that port flow data collection is inaccurate in the port flow optimization scheduling process in the prior art is solved.

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 important nodes of international trade, face increasing challenges in traffic management. In order to improve the operational efficiency and service quality of ports, it is particularly important to optimize port traffic scheduling. By optimizing scheduling, the waiting time of ships and vehicles in ports can be reduced, and the throughput efficiency of ports can be improved. Rationally allocate various resources in ports, such as berths, yards, loading and unloading equipment, etc., to improve resource utilization and operational efficiency. By real-time monitoring and analysis of various data in ports, potential safety hazards can be discovered and handled in a timely manner to ensure the safe and stable operation of ports. The Internet of Things refers to connecting objects and various devices in daily life through the Internet to achieve interconnection and information sharing. In port management, Internet of Things technology has been widely used.

[0003] The existing system mainly collects real-time data related to port traffic, such as ship entry and exit times, cargo throughput, number of containers, etc., and uses big data analysis and artificial intelligence technology 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, thereby improving port operating efficiency.

[0004] For example, the invention patent with announcement number: CN117744501B announces an optimization scheduling and decision-making method for regulating and storing nodes of a water network system considering 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, constructing a decision-making method, and selecting at least one solution from the set of feasible solutions.

[0005] For example, the invention patent with announcement number: CN110851977B announces an optimization method for a multi-objective water supply-power generation-ecological scheduling diagram based on ecological flow, including: 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 the 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 the "optimization-simulation" technology to solve the optimization model, obtain the optimized scheduling diagram, and determine various benefit indicators and the reservoir operation process.

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

[0007] In the prior art, since the behavior of ships entering and leaving the port is affected by many factors, such as a large number of ships sailing, which causes problems with the quality of input port flow data, the port flow data collection is inaccurate during the port flow optimization 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 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 acquire 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 judge whether to acquire a ship signal impact assessment coefficient based on the acquired waterway congestion assessment coefficient, and the waterway congestion assessment coefficient is used to evaluate the port waterway congestion status; the signal impact assessment module is used to acquire a waterway congestion assessment coefficient based on the acquired waterway 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, and the ship signal impact assessment coefficient is used to evaluate the impact of port channel congestion on port ship signals; the receiver impact assessment module is used to obtain the ship receiver impact assessment coefficient according to the obtained channel congestion assessment coefficient, the ship receiver related data and the reference ship receiver data within a preset second time period, and it is determined whether to perform receiver impact adjustment based on the obtained ship receiver impact assessment coefficient, and port flow optimization scheduling is performed based on the signal impact adjustment and the receiver impact adjustment, and the ship receiver impact assessment coefficient is used to evaluate the 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 path number represents the number of signal paths for the signal reflected by 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 according to 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 multiplying 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 represented 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 represented 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 represented 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 qrepresents 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, 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 in the qth preset first time period, represents the number of ships in the port channel in the qth preset first time period, It represents the duration of passage of 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 according to the acquired 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 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 adding 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 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 according to the acquired 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, the number of paths is processed to obtain the initial propagation loss, and the initial propagation loss is represented by the result of 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 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 the result of ratio operation of 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 preset second time period waterway congestion assessment coefficient to obtain the ship receiver impact assessment coefficient.

[0017] The embodiment of the present application provides a port flow optimization scheduling method based on the 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 a preset port ship monitoring device; S2, obtaining a waterway congestion assessment coefficient according to 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 waterway congestion assessment coefficient, wherein the waterway congestion assessment coefficient is used to assess the port waterway congestion status; S3, obtaining a 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 a preset second time period. S4, obtaining a ship receiver impact assessment coefficient according to the acquired channel congestion assessment coefficient, ship receiver related data and reference ship receiver data within a preset second time period, determining whether to perform a 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 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 the present 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 according to the ship signal related data and the reference ship signal data, and it is determined whether to adjust the signal impact. Finally, the ship receiver impact assessment coefficient is obtained according to the ship receiver related data and the reference ship receiver data, and it is determined whether to adjust the receiver impact. 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, which effectively solves the problem of inaccurate port flow data collection in the process of port flow optimization scheduling in the prior art.

[0020] 2. By presetting the port ship monitoring equipment, the ship congestion related data, the ship signal related data and the ship receiver related data are obtained. According to the ship congestion related data, the ship signal related data and the 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 realizing the improvement of the real-time performance of obtaining the port flow related data, and then realizing 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, and 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 realizing the accurate quantification of the port flow optimization scheduling, and then realizing the improvement of the reliability of the 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 graph showing changes in the waterway congestion assessment coefficient provided in an embodiment of the present application;

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

[0025] Figure 4 An overall flow chart provided for an embodiment of the present application. DETAILED DESCRIPTION

[0026] The embodiment of the present application solves 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 waterway 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 waterway 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 waterway 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 in the above-mentioned port flow optimization scheduling process. The overall idea is as follows:

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

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

[0030] like Figure 1 As shown, it is a structural schematic diagram of a 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 acquire ship congestion related data, ship signal related data and ship receiver related data through a preset port ship monitoring device, the ship congestion related data is used to describe the port channel congestion status, 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 the port channel; the congestion assessment module is used to acquire a channel congestion assessment coefficient according to the acquired ship congestion related data and the reference ship congestion data within a preset first time period, and judge whether to acquire the ship signal impact assessment coefficient based on the acquired channel congestion assessment coefficient, and the channel congestion assessment coefficient is used to assess the port channel congestion status; the signal impact assessment module is used to acquire a channel congestion assessment coefficient according to the acquired ship congestion related data and the reference ship congestion data within a preset second time period. A ship signal impact assessment coefficient is obtained according to the acquired waterway congestion assessment coefficient, ship signal related data and reference ship signal data; whether to perform signal impact adjustment is determined based on the acquired 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; the receiver impact assessment module is used to obtain the ship receiver impact assessment coefficient according to the acquired waterway congestion assessment coefficient, ship receiver related data and reference ship receiver data within a preset second time period; whether to perform receiver impact adjustment is determined based on the acquired 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.

[0031] In this embodiment, extreme weather conditions such as storms, typhoons, heavy rains, heavy fog, and heavy snow will directly affect the navigation safety of ships and the operating efficiency of ports. For example, severe weather may cause damage to port facilities, and ships cannot safely berth or leave the berth, thereby causing congestion. Signal impact adjustment and receiver impact adjustment help ensure smooth port operations, improve the speed and safety of ships entering and leaving the port, and enhance the port's ability to respond to sudden congestion, laying a solid foundation for the long-term development of the port. Big data technology can efficiently analyze a large amount of data, thereby extracting reference ship congestion data, reference ship signal data, and reference ship receiver data. Internet of Things technology realizes real-time monitoring of port operations by installing a preset number of GPS (Global Positioning System) sensors and AI S (Automatic Identification System) sensors at preset monitoring points on port facilities, ships, and cargoes; and improves 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; 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.

[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 the 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 signal wavelength is measured by a spectrum analyzer and combined with 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 and receiving distance; the mixed signals are separated by a spectrum analyzer, and the changes in the characteristics of the signal (such as amplitude, phase, etc.) are monitored on the basis of the signal separation, the number of signal paths, that is, the number of paths, are identified, the signal frequency is measured by the spectrum analyzer and the spectrum of the measured signal is displayed.

[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 waterway congestion assessment coefficient in the preset first time period 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.

[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 a preset free space loss threshold; the reference ship congestion data, the reference ship signal data and the reference ship receiver data are obtained from a 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, and 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 according to 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 ratio operation between the initial ship distance deviation and twice the preset ship distance threshold, and the ship distance deviation is used for reflection A4, obtaining the initial ship flow through the number of ships and the duration of passage, the initial ship flow is represented by the result of the ratio operation between the number of ships and the duration of passage; A5, obtaining the initial ship flow deviation through the initial ship flow and the preset ship flow threshold, the initial ship flow deviation is represented by the result of the addition operation between 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 represented by the result of the ratio operation between the initial ship flow deviation and twice the preset ship flow threshold, the ship flow deviation is used to reflect the deviation degree of the ship flow; A7, obtaining 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 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, 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 in the qth preset first time period, represents the number of ships in the port channel in the qth preset first time period, It represents the duration of passage of 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 does not exist independently, but is 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 at 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 consider the impact on the results together.

[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 FIG. 1 , a statistical diagram of changes in the waterway congestion assessment coefficient provided in this embodiment is shown in FIG. 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 flow The channel congestion assessment coefficient gradually increases, which means that the degree of ship congestion is gradually increasing; the accurate quantification of ship congestion is achieved, and then the accuracy of port flow data collection is improved during the port flow optimization and scheduling process.

[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 prompt 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, and 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, stop the signal impact adjustment, otherwise execute LL3, noise filtering means filtering the noise and interference caused by congestion through the 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, stop the signal impact adjustment, 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 the ship transmission loss in the historical time period in the preset data. The noise filtering includes that in the case of port channel congestion, the signal transmission between ships may be subject to various forms of interference, such as signal collision, signal attenuation, etc. The anti-interference algorithm can analyze the received signal, identify the noise component therein, and separate it from the original signal. The transmission time period adjustment means dividing the time into a preset number of time slots, and allowing each time slot to transmit the signal separately. In the case of port channel congestion, by changing the transmission time period of the ship, the signal collision and interference caused by multiple ships transmitting signals at the same time can be avoided. By filtering noise and optimizing the transmission time period to reduce the impact of congestion on ship signal transmission, the port operation efficiency and signal transmission quality are improved.

[0047] Furthermore, the specific process of obtaining the ship signal impact assessment coefficient according to the acquired 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 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 adding 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 ratio operation between 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] In the formula, XH s represents the ship signal impact assessment coefficient of the sth 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 sth 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 reflection 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 corresponding channel congestion assessment coefficient when the channel congestion assessment coefficient in the preset first time period is not lower 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, but has mutual correlation. The longer the initial ship distance, the larger the channel congestion assessment coefficient in the preset second time period, which does not mean that the ship signal impact assessment coefficient is larger, and the influence of the signal wavelength should also be considered comprehensively. The round-trip time of the signal may be affected by the congestion of the channel. When the channel is congested, the communication between ships may increase, resulting in a delay in signal transmission, thereby increasing the round-trip time of the signal. At the same time, the increase in the channel congestion assessment coefficient means that the density of ships in the channel increases, which may lead to more signal interference and communication delays, further affecting the round-trip time of the signal. Signals with longer wavelengths may produce greater reflections and scattering on the ship structure, which may also affect the propagation efficiency of the signal. The parameters of the algorithm of this embodiment need to consider the impact on the results together.

[0052] Specifically, assuming the reflection 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 can be seen from Table 1, as the reflection loss deviation and the waterway congestion assessment coefficient YD for the preset second time period s The ship signal impact assessment coefficient XH s It gradually increases, which means that the impact of port channel congestion on port ship signals is gradually increasing; it realizes the accurate quantification of the impact of port channel congestion on port ship signals, and then realizes the improvement of the accuracy of port flow data collection in the process of port flow optimization 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. The compressed 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 is issued.

[0057] Specifically, the preset receiver impact threshold is represented by the variance of the ship's free space loss in the historical time period in the preset data, and the compressed transmission data reduces the size of the transmission data through data compression technology, thereby reducing the delay and bandwidth occupancy of network transmission. During the receiver position adjustment stage, the system will prompt the preset personnel to adjust the position of the receiver according to the preset angle. The receiver includes an antenna, a radio frequency amplifier, a GPS receiver, etc. The adjustment of the receiver position can improve the signal transmission path between the receiver and the ship transmitter, reduce signal attenuation and interference, and ensure that the receiver can accurately and stably receive the signal transmitted by the ship, thereby improving the signal reception quality, and then improving the accuracy of port flow data collection during the port flow optimization scheduling process.

[0058] Furthermore, the specific process of obtaining the ship receiver impact assessment coefficient according to the acquired 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, 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, and the propagation loss deviation is used to reflect the deviation of the multipath propagation loss between the ship reflection signal and the receiver. condition; C4, the transmitting and receiving interval, signal frequency and light speed are processed to obtain the initial space loss, and the initial space loss is represented by the result of logarithmic operation of the transmitting and receiving interval, signal frequency and light speed; C5, the initial space loss deviation is obtained 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, the space loss deviation is obtained 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, and the space loss deviation is used to reflect the deviation of the free space loss between the ship reflection 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 second time period waterway congestion assessment coefficient.

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

[0060]

[0061] In the formula, JS s represents 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 sth 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 sth 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 waterway congestion assessment coefficient when the waterway congestion assessment coefficient in the preset first time period is not lower than the preset congestion threshold. The algorithm of this embodiment combines the relevant data of the ship receiver to comprehensively analyze and obtain the ship receiver impact assessment coefficient. The relevant data of the ship receiver in the algorithm of this embodiment do not exist independently and are interrelated. The more the number of paths, the longer the transmission and reception interval, and the greater the signal frequency, do not mean that the ship receiver impact assessment coefficient is greater. The impact of the waterway congestion assessment coefficient in the preset second time period should also be comprehensively considered. The number of paths may be affected by the transmission and reception interval. A larger transmission and reception interval may cause the signal to cover more paths, thereby increasing the number of paths. In a congested waterway, in order to ensure the effective transmission of the signal, it may be necessary to reduce the transmission and reception interval to improve the reliability of the signal. The transmission and reception interval may be affected by the signal frequency. Different signal frequencies may require different transmission and reception intervals to optimize the transmission of the signal. For example, a high-frequency signal may require a shorter interval to reduce the attenuation of the signal. The parameters of the algorithm of this embodiment need to consider the impact on the result together and at the same time; the accurate quantification of the impact of port channel congestion on ship receivers is achieved, thereby achieving the improvement of the accuracy of port flow data collection during the port flow optimization scheduling process.

[0063] like Figure 3As shown, it is a flow chart of a 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 a preset port ship monitoring device, 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 the port channel; S2, obtaining a channel congestion assessment coefficient: obtaining a channel congestion assessment coefficient according to the obtained ship congestion related data and the 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 the channel congestion assessment coefficient is used to assess the port channel congestion situation; S3, obtaining a ship signal impact assessment coefficient: within a preset second time period A ship signal impact assessment coefficient is obtained according to the obtained waterway congestion assessment coefficient, ship signal related data and reference ship signal data, and it is determined whether to perform signal impact adjustment 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 according to the obtained waterway congestion assessment coefficient, ship receiver related data and reference ship receiver data, and it is determined whether to perform receiver impact adjustment based on the obtained ship receiver impact assessment coefficient, and 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, it 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, and 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, it can not only effectively reduce the interference of congestion on ship signal transmission and improve port operation efficiency, but also significantly reduce the negative impact of congestion on the overall operation of the port, 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 equipment, and realizing the improvement of the accuracy of port traffic data collection in the process of port traffic optimization scheduling.

[0065] To summarize, 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 the 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 the receiver impact adjustment, thereby realizing the 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, and effectively solving the problem of inaccurate port flow data collection in the process of port flow optimization scheduling in the prior art.

[0066] Those skilled in the art will appreciate that embodiments of the present invention may be provided as methods, systems, or computer program products. Therefore, the present invention may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, 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 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 flowchart and / or block diagram, as well as the combination of processes and / or blocks in the flowchart and / or block diagram, 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 flowchart and / or block diagram. 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 capable of directing a computer or other programmable data processing device to operate 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 A 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 operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions 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 other 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 can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include these modifications and variations.

Claims

1. The port flow optimization and dispatching 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: Wherein, 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 channel congestion assessment coefficient according to 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 channel congestion assessment coefficient, and the channel congestion assessment coefficient is used to assess the port channel congestion status; The signal impact assessment module is used to obtain a ship signal impact assessment coefficient according to the acquired channel congestion assessment coefficient, ship signal related data and reference ship signal data within a preset second time period, and judge whether to perform signal impact adjustment based on the acquired ship signal impact assessment coefficient, and the ship signal impact assessment coefficient is used to assess the degree of influence 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 waterway 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. The ship receiver impact assessment coefficient is used to evaluate the degree of impact of the port channel congestion condition on the receiver that monitors the port channel.

2. The port flow optimization and scheduling system based on the Internet of Things big data as claimed in claim 1 is characterized in that: The preset port ship monitoring equipment includes radar, timer and spectrum analyzer; The ship congestion related data include 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, the transmission and reception distance and the signal frequency; The number of paths represents the number of signal paths for the signal reflected by the ship to reach the receiver; The preset first time period represents a preset time period in the process of performing port flow statistics; The preset second time period refers to the preset time period corresponding to when the waterway congestion assessment coefficient in the preset first time period 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 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.

3. The port flow optimization and dispatching system based on the Internet of Things big data as claimed in claim 2 is characterized in that: The specific process of obtaining the waterway congestion assessment coefficient according to 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 through 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 through an initial ship distance deviation and a preset ship distance threshold, wherein the ship distance deviation is represented by a result of a ratio operation between the initial ship distance deviation and twice the preset ship distance threshold; A4, obtaining an initial ship flow rate by the number of passing ships and the passing time, wherein the initial ship flow rate is represented by a result of a ratio calculation between the number of ships and the passing time; A5, obtaining an initial ship flow deviation through 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 to the preset ship flow threshold; A6, obtaining a ship flow deviation through an initial ship flow deviation and a preset ship flow threshold, wherein the ship flow deviation is represented by a result of a ratio operation between 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 waterway congestion assessment coefficient.

4. The port flow optimization and dispatching system based on the Internet of Things big data as claimed in claim 3 is characterized in that: The limiting expression of the waterway congestion assessment coefficient is as follows: In the formula, YD q 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, 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 in the qth preset first time period, represents the number of ships in the port channel in the qth preset first time period, It represents the duration of passage of 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.

5. The port flow optimization and dispatching system based on the Internet of Things big data as claimed in claim 4 is characterized in that: The specific process of judging 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.

6. The port flow optimization and dispatching system based on the Internet of Things big data as claimed in claim 2 is characterized in that: The specific process of obtaining the ship signal impact assessment coefficient according to the acquired waterway 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 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 reflection loss deviation through the initial reflection loss and a preset reflection loss threshold, wherein the initial reflection loss deviation is represented by a result of adding the initial reflection loss to the preset reflection loss threshold; B3, obtaining a reflection loss deviation through an initial reflection loss deviation and a preset reflection loss threshold, wherein the reflection loss deviation is represented by a result of a ratio operation between the initial reflection loss deviation and twice the preset reflection loss threshold; B4, obtaining a ship signal impact assessment coefficient by combining the reflection loss deviation and the waterway congestion assessment coefficient of the preset second time period.

7. The port flow optimization and dispatching system based on the Internet of Things big data as claimed in claim 2 is characterized in that: The specific process of obtaining the ship receiver impact assessment coefficient according to the acquired 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 a result of a logarithmic operation on the number of paths; C2, obtaining an initial propagation loss deviation through 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 through an initial propagation loss deviation and a preset multipath ship loss threshold, wherein the propagation loss deviation is represented by a result of a ratio operation between the initial propagation loss deviation and twice the preset multipath ship loss threshold; C4, processing the transmission and reception interval, signal frequency and light speed to obtain an initial space loss, wherein the initial space loss is represented by the result of a logarithmic operation of the transmission and reception interval, signal frequency and light speed; C5, obtaining an initial space loss deviation through 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 through an initial space loss deviation and a preset free space loss threshold, wherein the space loss deviation is represented by a result of a ratio operation between the initial space loss deviation and twice the preset free space loss threshold; C7, obtains the ship receiver impact assessment coefficient by combining the initial space loss, the space loss deviation and the waterway congestion assessment coefficient of the preset second time period.

8. The port flow optimization and dispatching system based on the Internet of Things big data as claimed in claim 6 is characterized in that: The specific process of judging whether to perform signal impact adjustment based on the acquired ship signal impact assessment coefficient is as follows: LL1, judge 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, perform noise filtering, and stop signal impact adjustment when the monitored ship signal impact assessment coefficient is not higher than the preset signal impact threshold, otherwise execute LL3; 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.

9. The port flow optimization and dispatching system based on the Internet of Things big data as claimed in claim 7 is characterized in that: The specific process of judging whether to perform receiver impact adjustment based on the acquired ship receiver impact assessment coefficient is as follows: KK1, judging 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.

10. A port flow optimization scheduling method based on IoT big data, characterized in that: The following steps are involved: 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 according to the acquired 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 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 according to the acquired channel congestion assessment coefficient, ship signal related data and reference ship signal data within a preset second time period, and judging whether to perform signal impact adjustment based on the acquired 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 according to the acquired waterway 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 waterway congestion condition on the receiver monitoring the port waterway.

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