Intelligent channel environment data acquisition management system and method

Abstract

The invention relates to the technical field of data acquisition and management, and particularly discloses an intelligent channel environment data acquisition and management system and method, and the method comprises the steps: S1, obtaining environment data at a channel monitoring point; in the past acquisition time interval, the total number of ships passing by the monitoring point is obtained according to the standard acquisition period, and a conventional monitoring point is determined; s2, other monitoring points are divided into control groups, and the change difference quantity in the most control group is obtained; s3, key monitoring points are determined according to the change difference quantity and a difference quantity threshold value; s4, acquiring an average discrete coefficient of the key monitoring points, and acquiring an acquisition period of the key monitoring points according to the average discrete coefficient and a standard acquisition period; s5, acquiring environmental data of the key monitoring points and the conventional monitoring points; by paying attention to the correlation between data sets and eliminating redundant data points, collection and management of channel environment monitoring data are optimized.

Description

Technical Field

[0001] The present invention relates to the technical field of data collection and management, and in particular to a smart waterway environment data collection and management system and method. Background Art

[0002] Smart waterway environment data refers to data related to the waterway environment of ships that is collected, processed and shared through modern information technology and sensor equipment; waterway environment data can greatly improve the safety and efficiency of navigation and provide real-time information to support ship navigation and management.

[0003] Data collection management is a key process to ensure that high-quality data can be collected, stored and processed accurately and timely; data collection management includes multiple aspects, from initial data collection to final data utilization; including data demand analysis, data collection methods and data quality management.

[0004] With the deepening development of globalization and the increasing frequency of international trade, the increase in the number of ships as important water transportation tools seems to have become an irreversible trend, so the collection of ship channel environmental data has become increasingly important; in the existing technology, due to the increasing number of ship channels and the increasing diversity of channels, how to quickly and accurately obtain channel environmental data, improve the efficiency of channel data collection and reduce the collection cost is the problem we need to solve. Summary of the invention

[0005] The purpose of the present invention is to provide a smart waterway environment data collection and management system and method to solve the above technical problems.

[0006] The purpose of the present invention can be achieved through the following technical solutions: A method for collecting and managing smart waterway environment data comprises the following steps: Step S1: Acquire all waterways, select a number of monitoring points on the waterways, and the monitoring points are used to acquire environmental data, and the environmental data includes a number of indicators; Set a collection time interval and a standard collection cycle T0, and obtain environmental data at the monitoring point and the total number of ships passing by N according to the standard collection cycle in the past collection time interval; and set a number threshold n, select monitoring points with N ≥ n, and record them as regular monitoring points; Step S2: Record the monitoring points other than the conventional monitoring points as the remaining monitoring points, and record the remaining monitoring points with the closest distance between each other as a control group; obtain the change difference C of the environmental data between two remaining monitoring points, where: ; Where m is the total number of environmental data indicators, i represents the i-th indicator, i∈[1,m] and i is a positive integer, f(t) and g(t) are the curves of environmental data and collection times of the two remaining monitoring points in the past collection time interval, p represents the p-th intersection of f(t) and g(t), t p is the time corresponding to the pth intersection, n is the total number of intersections of f(t) and g(t); Step S3: setting a difference threshold ε, if C≤ε, then selecting one of the remaining monitoring points in the control group as a key monitoring point so that the sum of the distances between the key monitoring points reaches a minimum value; Step S4: Obtain the average dispersion coefficient of key monitoring points ,in Represents the ratio of the standard deviation of the change rate of the ith indicator in the environmental data collected within the collection time interval to the average change rate; according to the average dispersion coefficient and the standard collection cycle, the collection cycle of the key monitoring point is obtained , where α is a preset coefficient and α>0; Step S5: Acquire environmental data at each key monitoring point according to the collection cycle and use it as the environmental data of the remaining monitoring points in its control group; and acquire environmental data collected by the ship that passed the regular monitoring point most recently as the environmental data of the regular monitoring point.

[0007] As a further solution of the present invention: the process of selecting the monitoring points includes: Obtain the navigation routes of all ships, and all navigation routes constitute all waterways; A distance interval threshold is set, and every other distance interval threshold in the waterway is taken as a monitoring point, and the selection of the monitoring points includes the starting point and the end point of the waterway.

[0008] As a further solution of the present invention: the setting range of the collection time interval is [3,12] months, the environmental data includes river water pollution data, and the indicators of the environmental data include physical indicators, chemical indicators and biological indicators.

[0009] As a further solution of the present invention: the process of setting the number threshold includes: Obtain the total number of ships passing through each monitoring point in the past acquisition time interval, and obtain a data set, recorded as {N1, N2, ..., N k}, N1 is the total number of ships passing by the first monitoring point, k is the total number of monitoring points; then the average value of the total number of ships passing by is obtained , where e∈[1,k] and e is a positive integer; The standard deviation σ is obtained from the data set, where: ; Then the setting range of the number threshold is (N ave -σ,N ave +σ).

[0010] As a further solution of the present invention, the process of determining the control group according to the remaining monitoring points with the shortest distances between each other comprises: Randomly select two adjacent remaining monitoring points as a combination, obtain the position coordinates of the two remaining monitoring points in the combination, and record them as (x1, y1) and (x2, y2) respectively; then the distance between the two remaining monitoring points is ; Get the sum of the distances between the two remaining monitoring points in each combination , where j∈[1, k / 2] and j is a positive integer; when ST reaches the minimum value, the two remaining monitoring points in the combination are recorded as a control group.

[0011] As a further solution of the present invention: if C>ε of the remaining monitoring points, then the two remaining monitoring points in the control group are directly recorded as key monitoring points.

[0012] As a further solution of the present invention: the process of obtaining the standard deviation of the rate of change and the average rate of change includes: Obtain the environmental data of the key monitoring point in the past collection time interval, and obtain the change rate Cr of the environmental data collected twice adjacently a =(E a+1 -E a ) / T0, where E a represents the environmental data collected for the ath time, Cr a is the ath rate of change; get the average rate of change , where num is the total number of collections; Obtain the standard deviation s of the rate of change, where: .

[0013] As a further solution of the present invention: a smart waterway environment data collection and management system, comprising: Sample data collection: obtain all waterways, select several monitoring points on the waterways, and the monitoring points are used to obtain environmental data, and the environmental data includes several indicators; Set a collection time interval and a standard collection cycle T0, and obtain environmental data at the monitoring point and the total number of ships passing by N according to the standard collection cycle in the past collection time interval; and set a number threshold n, select monitoring points with N ≥ n, and record them as regular monitoring points; Primary screening module: record the monitoring points other than the conventional monitoring points as the remaining monitoring points, and record the remaining monitoring points with the closest distance between each other as a control group; obtain the change difference C of the environmental data between two remaining monitoring points, where: ; Where m is the total number of environmental data indicators, i represents the i-th indicator, i∈[1,m] and i is a positive integer, f(t) and g(t) are the curves of environmental data and collection times of the two remaining monitoring points in the past collection time interval, p represents the p-th intersection of f(t) and g(t), t p is the time corresponding to the pth intersection, n is the total number of intersections of f(t) and g(t); Secondary screening module: set the difference threshold ε, if C≤ε, then select one of the remaining monitoring points in the control group as the key monitoring point, so that the sum of the distances between the key monitoring points reaches the minimum value; Period correction module: obtain the average dispersion coefficient of key monitoring points ,in Represents the ratio of the standard deviation of the change rate of the ith indicator in the environmental data collected within the collection time interval to the average change rate; according to the average dispersion coefficient and the standard collection cycle, the collection cycle of the key monitoring point is obtained , where α is a preset coefficient and α>0; Environmental data collection module: obtains environmental data at each key monitoring point according to the collection cycle and uses it as the environmental data of the remaining monitoring points in its control group; and obtains the environmental data collected by the ship that passed the regular monitoring point most recently as the environmental data of the regular monitoring point.

[0014] Beneficial effects of the present invention: In the prior art, as the number of ship channels increases and the channels become more and more diverse, how to quickly and accurately obtain the environmental data of the channels, improve the collection efficiency of channel data and reduce the collection cost is the problem we need to solve; therefore, the present invention sets a number of monitoring points in the channel, and screens out the monitoring points with a small total number of ships passing through different monitoring points according to the different total numbers of ships passing through; the monitoring points with a small total number of ships passing through are recorded as regular monitoring points, and the environmental data collected by the ship that passed through the regular monitoring point most recently is directly obtained as the environmental data of the regular monitoring point, which reduces unnecessary data collection and improves the overall data collection efficiency; for the remaining monitoring points with a small total number of ships passing through, the remaining monitoring points are first grouped and paired according to the distance between each other; the distance between two remaining monitoring points in the same control group is obtained. The amount of difference in environmental data changes; the amount of difference in environmental data changes reflects the size of the difference in environmental data obtained each time at two other monitoring points; if the difference in environmental data of two other monitoring points in the same control group is not large, the environmental data of the two other monitoring points can replace each other, and only the environmental data of one of the other monitoring points can be obtained, thereby reducing the number of acquisitions; therefore, for the two other replaceable monitoring points, one of them is selected as the key monitoring point, and in the selection process of the key monitoring points described herein, it is ensured that the sum of the distances between the key monitoring points finally obtained by selection reaches the minimum value, so as to reduce the route distance during the acquisition process; in addition, for the key monitoring points, the acquisition period of the key monitoring points is determined according to the fluctuation of the environmental data of the key monitoring points; if the fluctuation of the environmental data of the key monitoring points is greater, the acquisition period is smaller, thereby ensuring the accuracy of the collected environmental data; The present invention optimizes the collection and management of waterway environment monitoring data by focusing on the correlation between data sets and eliminating redundant data points; it streamlines the number of monitoring points, enables a more reasonable allocation of resources, and reduces monitoring costs; and it can adjust the monitoring plan in real time according to the fluctuation of the monitoring data and the collection cycle to ensure the timeliness and reliability of the data. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] The present invention will be further described below in conjunction with the accompanying drawings.

[0016] Figure 1 It is a flow chart of a smart waterway environment data collection management system and method of the present invention. DETAILED DESCRIPTION

[0017] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0018] See also Figure 1 As shown, the present invention is a method for collecting and managing smart waterway environment data, comprising the following steps: Step S1: Acquire all waterways, select a number of monitoring points on the waterways, and the monitoring points are used to acquire environmental data, and the environmental data includes a number of indicators; Set a collection time interval and a standard collection cycle T0, and obtain environmental data at the monitoring point and the total number of ships passing by N according to the standard collection cycle in the past collection time interval; and set a number threshold n, select monitoring points with N ≥ n, and record them as regular monitoring points; It should be noted that the total number of ships passing through the monitoring point is the total number of ships passing through the monitoring point in the past collection time interval; It can be understood that, firstly, several monitoring points are selected on the waterway, and these monitoring points are used to collect environmental data; the environmental data includes multiple indicators, such as water quality, temperature, flow rate, etc.; according to the total number of ships passing through different monitoring points, the monitoring points with a small total number of ships passing through are screened out; the monitoring points with a small total number of ships passing through are recorded as regular monitoring points, and the environmental data collected by the ship that passed through the regular monitoring point most recently is directly obtained as the environmental data of the regular monitoring point, which reduces unnecessary data collection and improves the overall data collection efficiency; The process of selecting the monitoring points includes: Obtain the navigation routes of all ships, and all navigation routes constitute all waterways; Setting a distance interval threshold, taking every distance interval threshold in the waterway as a monitoring point, wherein the selection of the monitoring points includes the starting point and the end point of the waterway; The setting range of the collection time interval is [3,12] months, the environmental data includes river water pollution data, and the indicators of the environmental data include physical indicators, chemical indicators and biological indicators; It is understandable that the navigation routes of all ships are obtained and used to construct a complete waterway map; in the entire waterway, monitoring points are set according to the set distance interval threshold, and these monitoring points cover the entire range from the starting point to the end point of the waterway; by obtaining the navigation routes of all ships and setting reasonable interval monitoring points, full coverage monitoring of the waterway is ensured and monitoring blind spots are avoided; the environmental data of the waterway sometimes changes significantly with the seasons, and selecting 3 to 12 months can cover a complete seasonal change cycle; in addition, long-term trends such as climate change require longer time series data to observe, and through continuous data analysis for several months, the impact of these long-term changes on the waterway environment can be more accurately assessed; therefore, the collection time interval is set to 3 to 12 months, and the monitoring cycle can be flexibly adjusted according to actual needs, which improves the adaptability of the monitoring plan; The process of setting the number threshold includes: Obtain the total number of ships passing through each monitoring point in the past acquisition time interval, and obtain a data set, recorded as {N1, N2, ..., N k}, N1 is the total number of ships passing by the first monitoring point, k is the total number of monitoring points; then the average value of the total number of ships passing by is obtained , where e∈[1,k] and e is a positive integer; The standard deviation σ is obtained from the data set, where: ; Then the setting range of the number threshold is (N ave -σ,N ave +σ); It can be understood that, according to the total number of ships passing through each monitoring point, the average value and the standard deviation are obtained, and the setting range of the number threshold is obtained according to the average value and the standard deviation; the total number of ships passing through each monitoring point exceeds the number threshold, that is, the total number of ships passing through the monitoring point is relatively large; Step S2: Record the monitoring points other than the conventional monitoring points as the remaining monitoring points, and record the remaining monitoring points with the closest distance between each other as a control group; obtain the change difference C of the environmental data between two remaining monitoring points, where: ; Where m is the total number of environmental data indicators, i represents the i-th indicator, i∈[1,m] and i is a positive integer, f(t) and g(t) are the curves of environmental data and collection times of the two remaining monitoring points in the past collection time interval, p represents the p-th intersection of f(t) and g(t), t p is the time corresponding to the pth intersection, n is the total number of intersections of f(t) and g(t); It should be noted that, according to the environmental data at the two remaining monitoring points obtained in the past collection time interval; a rectangular coordinate system is established with time as the horizontal coordinate and the value of the environmental data indicator as the vertical coordinate; the environmental data collected at the remaining monitoring points each time are converted into coordinate points in the rectangular coordinate system, and a discrete point graph is obtained in the rectangular coordinate system; the coordinate points on the discrete point graph are connected with a smooth curve, and the curve is recorded as the curve of the environmental data and the number of collections of the remaining monitoring points in the past collection time interval; according to the above steps, the curves f(t) and g(t) of the environmental data and the number of collections of the two remaining monitoring points in the past collection time interval are obtained, and t is the time of each collection; wherein It represents the area difference between every two adjacent intersection points of f(t) and g(t), and represents the difference in environmental data collected by the two other monitoring points in the past collection time interval; the change difference is the average difference of all indicators; Step S3: setting a difference threshold ε, if C≤ε, then selecting one of the remaining monitoring points in the control group as a key monitoring point so that the sum of the distances between the key monitoring points reaches a minimum value; If C of the remaining monitoring points is greater than ε, then the two remaining monitoring points in the control group are directly recorded as key monitoring points; It is understandable that if the environmental data of two other monitoring points in the same control group are not much different, the environmental data of the two other monitoring points can replace each other, and only the environmental data of one of the other monitoring points can be obtained, thereby reducing the number of collection times; therefore, for the two other monitoring points that can be replaced, one of them is selected as the key monitoring point; in addition, in the selection process of the key monitoring point, it is ensured that the sum of the distances between the key monitoring points finally obtained by the selection reaches the minimum value, thereby reducing the route distance during the collection process; It should be noted that the difference threshold depends on many factors, including specific environmental parameters, monitoring purposes, data analysis methods, and navigation standards. The appropriate difference threshold is set according to the specific conditions of the experimental data. The process of determining the control group based on the remaining monitoring points with the closest distances between each other includes: Randomly select two adjacent remaining monitoring points as a combination, obtain the position coordinates of the two remaining monitoring points in the combination, and record them as (x1, y1) and (x2, y2) respectively; then the distance between the two remaining monitoring points is ; Get the sum of the distances between the two remaining monitoring points in each combination , where j∈[1, k / 2] and j is a positive integer; when ST reaches the minimum value, the two remaining monitoring points in the combination are recorded as a control group; It can be understood that when the distance between two remaining monitoring points is closer, the possibility that the environmental data of the two remaining monitoring points are closer is greater, so the two adjacent and closest remaining monitoring points are directly selected as the control group to determine the difference in environmental data of the two remaining monitoring points; Step S4: Obtain the average dispersion coefficient of key monitoring points ,in Represents the ratio of the standard deviation of the change rate of the ith indicator in the environmental data collected within the collection time interval to the average change rate; according to the average dispersion coefficient and the standard collection cycle, the collection cycle of the key monitoring point is obtained , where α is a preset coefficient and α>0; The process of obtaining the standard deviation of the rate of change and the average rate of change includes: Obtain the environmental data of the key monitoring point in the past collection time interval, and obtain the change rate Cr of the environmental data collected twice adjacently a =(Ea+1 -E a ) / T0, where E a represents the environmental data collected for the ath time, Cr a is the ath rate of change; get the average rate of change , where num is the total number of collections; Obtain the standard deviation s of the rate of change, where: ; It can be understood that the average dispersion coefficient is used to measure the fluctuation of environmental data at key monitoring points. The larger the dispersion coefficient, the greater the fluctuation of environmental data; the smaller the dispersion coefficient, the smaller the fluctuation of environmental data; for key monitoring points with large fluctuations in environmental data, the shorter the collection cycle needs to be set, because a short collection cycle can capture rapid changes in data more timely and accurately, and frequent monitoring can reduce accidental errors caused by single sampling, improve the accuracy and stability of overall data, and ensure navigation safety of waterways; Step S5: acquiring environmental data at each key monitoring point according to the collection cycle and using it as environmental data for the remaining monitoring points in the control group; and acquiring environmental data collected by the ship that passed the conventional monitoring point most recently as environmental data for the conventional monitoring point; It can be understood that the present invention optimizes the collection and management of waterway environment monitoring data by focusing on the correlation between data sets and eliminating redundant data points; streamlines the number of monitoring points, enables a more reasonable allocation of resources, and reduces monitoring costs; and can adjust the monitoring plan in real time according to the fluctuation of the monitoring data and the collection cycle to ensure the timeliness and reliability of the data.

[0019] A smart waterway environment data collection and management system, comprising: Sample data collection: obtain all waterways, select several monitoring points on the waterways, and the monitoring points are used to obtain environmental data, and the environmental data includes several indicators; Set a collection time interval and a standard collection cycle T0, and obtain environmental data at the monitoring point and the total number of ships passing by N according to the standard collection cycle in the past collection time interval; and set a number threshold n, select monitoring points with N ≥ n, and record them as regular monitoring points; Primary screening module: record the monitoring points other than the conventional monitoring points as the remaining monitoring points, and record the remaining monitoring points with the closest distance between each other as a control group; obtain the change difference C of the environmental data between two remaining monitoring points, where: ; Where m is the total number of environmental data indicators, i represents the i-th indicator, i∈[1,m] and i is a positive integer, f(t) and g(t) are the curves of environmental data and collection times of the two remaining monitoring points in the past collection time interval, p represents the p-th intersection of f(t) and g(t), t p is the time corresponding to the pth intersection, n is the total number of intersections of f(t) and g(t); Secondary screening module: set the difference threshold ε, if C≤ε, then select one of the remaining monitoring points in the control group as the key monitoring point, so that the sum of the distances between the key monitoring points reaches the minimum value; Period correction module: obtain the average dispersion coefficient of key monitoring points ,in Represents the ratio of the standard deviation of the change rate of the ith indicator in the environmental data collected within the collection time interval to the average change rate; according to the average dispersion coefficient and the standard collection period, the collection period of the key monitoring point is obtained, where α is a preset coefficient and α>0; Environmental data collection module: obtains environmental data at each key monitoring point according to the collection cycle and uses it as the environmental data of the remaining monitoring points in its control group; and obtains the environmental data collected by the ship that passed the regular monitoring point most recently as the environmental data of the regular monitoring point.

[0020] The above is a detailed description of an embodiment of the present invention, but the content is only a preferred embodiment of the present invention and cannot be considered to limit the scope of implementation of the present invention. All equivalent changes and improvements made within the scope of the present invention should still fall within the scope of the patent coverage of the present invention.

Claims

1. A method for collecting and managing smart waterway environment data, characterized in that: The following steps are involved: Step S1: Acquire all waterways, select a number of monitoring points on the waterways, the monitoring points are used to acquire environmental data, and the environmental data includes a number of indicators; Set a collection time interval and a standard collection cycle T0, and obtain environmental data at the monitoring point and the total number of ships passing by N according to the standard collection cycle in the past collection time interval; And set the number threshold n, select the monitoring points with N ≥ n, and record them as regular monitoring points; Step S2: Record the monitoring points other than the conventional monitoring points as the remaining monitoring points, and record the remaining monitoring points with the closest distance between each other as a control group; obtain the change difference C of the environmental data between two remaining monitoring points, where: ; Where m is the total number of environmental data indicators, i represents the i-th indicator, i∈[1,m] and i is a positive integer, f(t) and g(t) are the curves of environmental data and time of the two remaining monitoring points in the past collection time interval, p represents the p-th intersection of f(t) and g(t), t p is the time corresponding to the pth intersection, n is the total number of intersections of f(t) and g(t); Step S3: setting a difference threshold ε, if C≤ε, then selecting one of the remaining monitoring points in the control group as a key monitoring point so that the sum of the distances between the key monitoring points reaches a minimum value; Step S4: Obtain the average dispersion coefficient of key monitoring points ,in Represents the ratio of the standard deviation of the change rate of the ith indicator in the environmental data collected within the collection time interval to the average change rate; according to the average dispersion coefficient and the standard collection cycle, the collection cycle of the key monitoring point is obtained , where α is a preset coefficient and α>0; Step S5: Acquire environmental data at each key monitoring point according to the collection cycle and use it as the environmental data of the remaining monitoring points in its control group; and acquire environmental data collected by the ship that passed the regular monitoring point most recently as the environmental data of the regular monitoring point.

2. According to claim 1, a smart waterway environment data collection and management method is characterized in that: In step S1, the process of selecting the monitoring points includes: Obtain the navigation routes of all ships, and all navigation routes constitute all waterways; A distance interval threshold is set, and every other distance interval threshold in the waterway is taken as a monitoring point, and the selection of the monitoring points includes the starting point and the end point of the waterway.

3. The method for collecting and managing smart waterway environment data according to claim 1, characterized in that: In step S1, the collection time interval is set within a range of [3, 12] months, the environmental data includes river water pollution data, and the indicators of the environmental data include physical indicators, chemical indicators and biological indicators.

4. The method for collecting and managing smart waterway environment data according to claim 1, characterized in that: In step S1, the process of setting the number threshold includes: Obtain the total number of ships passing through each monitoring point in the past acquisition time interval, and obtain a data set, recorded as {N1, N2, ..., N k }, N1 is the total number of ships passing by the first monitoring point, k is the total number of monitoring points; then the average value of the total number of ships passing by is obtained , where e∈[1,k] and e is a positive integer; The standard deviation σ is obtained from the data set, where: ; Then the setting range of the number threshold is (N ave -σ,N ave +σ).

5. A smart waterway environment data collection and management method according to claim 4, characterized in that: In step S3, the process of determining the control group according to the remaining monitoring points with the shortest distances between each other includes: Randomly select two adjacent remaining monitoring points as a combination, obtain the position coordinates of the two remaining monitoring points in the combination, and record them as (x1, y1) and (x2, y2) respectively; then the distance between the two remaining monitoring points is ; Get the sum of the distances between the two remaining monitoring points in each combination , where j∈[1, k / 2] and j is a positive integer; when ST reaches the minimum value, the two remaining monitoring points in the combination are recorded as a control group.

6. The method for collecting and managing smart waterway environment data according to claim 1, characterized in that: In step S3, if C>ε of the remaining monitoring points, then the two remaining monitoring points in the control group are directly recorded as key monitoring points.

7. The method for collecting and managing smart waterway environment data according to claim 1, characterized in that: In step S4, the process of obtaining the standard deviation of the rate of change and the average rate of change includes: Obtain the environmental data of the key monitoring point in the past collection time interval, and obtain the change rate Cr of the environmental data collected twice adjacently a =(E a+1 -E a ) / T0, where E a represents the environmental data collected for the ath time, Cr a is the ath rate of change; get the average rate of change , where num is the total number of collections; Obtain the standard deviation s of the rate of change, where: .

8. The smart waterway environment data collection and management system according to claim 1, comprising: Sample data collection: obtain all waterways, select several monitoring points on the waterways, and the monitoring points are used to obtain environmental data, and the environmental data includes several indicators; Set a collection time interval and a standard collection cycle T0, and obtain environmental data at the monitoring point and the total number of ships passing by N according to the standard collection cycle in the past collection time interval; And set the number threshold n, select the monitoring points with N ≥ n, and record them as regular monitoring points; Primary screening module: record the monitoring points other than the conventional monitoring points as the remaining monitoring points, and record the remaining monitoring points with the closest distance between each other as a control group; obtain the change difference C of the environmental data between two remaining monitoring points, where: ; Where m is the total number of environmental data indicators, i represents the i-th indicator, i∈[1,m] and i is a positive integer, f(t) and g(t) are the curves of environmental data and collection times of the two remaining monitoring points in the past collection time interval, p represents the p-th intersection of f(t) and g(t), t p is the time corresponding to the pth intersection, n is the total number of intersections of f(t) and g(t); Secondary screening module: set the difference threshold ε, if C≤ε, then select one of the remaining monitoring points in the control group as the key monitoring point, so that the sum of the distances between the key monitoring points reaches the minimum value; Period correction module: obtain the average dispersion coefficient of key monitoring points ,in Represents the ratio of the standard deviation of the change rate of the ith indicator in the environmental data collected within the collection time interval to the average change rate; according to the average dispersion coefficient and the standard collection cycle, the collection cycle of the key monitoring point is obtained , where α is a preset coefficient and α>0; Environmental data collection module: obtains environmental data at each key monitoring point according to the collection cycle and uses it as the environmental data of the remaining monitoring points in its control group; and obtains the environmental data collected by the ship that passed the regular monitoring point most recently as the environmental data of the regular monitoring point.

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