JP7323404B2 - Suspicious ship monitoring system - Google Patents

Description

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to a suspicious ship monitoring system, and more particularly to a suspicious ship monitoring system that identifies and monitors suspicious ships by analyzing behavior patterns of ships using AIS information.

In recent years, a large number of ships are navigating the seas of the world, and the probability of maritime accidents due to abnormal approach between ships is extremely high. In addition, in important sea areas where tankers, cargo ships, military vessels, etc. navigate, as well as EEZs (Exclusive Economic Zones), there is an increase in the number of suspicious ships that attempt to commit acts of piracy or invade territorial waters. are doing. Smuggling by ship-to-ship transfers of cargo from ship to ship at sea is also a problem.

In order to deal with such situations, ships have been conventionally monitored by radar or by visual inspection. However, with the conventional method, it is necessary to send patrol boats and aircraft to the site, which not only increases fuel and personnel costs, but also identifies vessels with a high probability of being suspicious vessels from a large number of vessels. it was difficult to

In addition, from the viewpoint of avoiding collisions between ships and ensuring the safety of human life, according to the SOLAS treaty, ships that meet certain standards are required to be equipped with an AIS (Automatic Identification System). AIS information communicated using AIS includes dynamic information such as position, course, speed, MMSI number (Maritime Mobile Service Identity) which is an ID number that identifies a ship, ship name, ship It contains static information such as the size of the vessel and type of vessel, and voyage-related information such as the draft of the vessel, type of cargo loaded, purpose and estimated time of arrival.

As a conventional ship monitoring system using such an AIS, for example, the system disclosed in Patent Document 1 compares pre-registered AIS information with received AIS information to identify the ship requested for monitoring. I try to understand behavior patterns. In addition, in the suspicious ship determination method disclosed in Patent Document 2, based on radar, camera, AIS information, etc., the probability of terrorism occurring in a ship navigating a specific sea area and the severity of the assumed situation are determined. It is determined whether or not the vessel is a suspicious vessel.

JP 2008-009846 A JP 2007-265067 A

However, the inventions described in Patent Literature 1 and Patent Literature 2 mentioned above specify a specific vessel, monitor the behavior of the vessel, and determine whether or not it is a suspicious vessel. It is not intended to comprehensively monitor the behavior of unspecified number of ships transmitting AIS information to identify suspicious ships.

Therefore, in order to judge whether or not it is a suspicious ship among the unspecified number of ships transmitting AIS information, there is no choice but to rely on radar and visual surveillance as before. there were.

SUMMARY OF THE INVENTION The present invention has been devised in view of such problems, and provides a suspicious ship monitoring system capable of identifying and monitoring a suspicious ship from an unspecified number of ships transmitting AIS information. With the goal.

According to the present invention, there is provided a data center that aggregates AIS information transmitted by ships, and a monitoring device that monitors suspicious ships using the AIS information, and the monitoring device uses the AIS information to Analyzes the behavioral patterns of the vessels, assigns flags that are presumed to be suspicious vessels when the behavioral patterns correspond to predetermined rules, counts the number of flags to calculate a score, and identifies the suspicious vessels based on the scores. There is provided a suspicious ship monitoring system characterized by being configured to identify.

The monitoring device may calculate the score by adding a weighted value to the flag for each rule.

The above rules include the movement of vessels other than fishing vessels to reverse course 180 degrees at sea, long-term berths in sea areas where vessels do not anchor, stoppage of AIS signals for long periods of time, and no vessels other than fishing vessels to call at other ports. Movement to return to the original port, repeated alteration of the static information included in the AIS information, alteration of the static information included in the AIS information to unauthorized data, and vessels other than fishing vessels repeatedly sailing in the same sea area. It may be any one of reciprocating motion, abnormal proximity of two ships, or a combination of two or more of these.

Further, according to the present invention, there is provided a data center that aggregates AIS information transmitted by ships, and a monitoring device that monitors suspicious ships using the AIS information, and the monitoring device uses the AIS information to analyzing the action pattern of the ship, creating a heat map in advance on a nautical chart from the action pattern, predicting the future action pattern of the given ship using the heat map from the current position of the given ship, A suspicious vessel monitoring system is provided, wherein the suspicious vessel is identified by comparing the actual behavior pattern of the predetermined vessel with the future behavior pattern.

Further, according to the present invention, there is provided a data center that aggregates AIS information transmitted by ships, and a monitoring device that monitors suspicious ships using the AIS information, and the monitoring device uses the AIS information to Analyze the behavior pattern of the vessel, assign a flag to be presumed to be a suspicious vessel when the behavior pattern corresponds to a predetermined rule, calculate a score by totaling the number of the flags, and calculate the suspicious vessel based on the score Further, the monitoring device creates a heat map in advance on a nautical chart from the behavior patterns, and uses the heat map from the current position of a predetermined ship to identify the predetermined ship. A suspicious vessel monitoring system, characterized in that it is configured to predict a future behavior pattern of a vessel, and to identify the suspicious vessel by comparing the actual behavior pattern of the predetermined vessel with the future behavior pattern. is provided.

The monitoring device may be configured to monitor the behavior pattern in real time.

According to the suspicious ship monitoring system according to the present invention described above, AIS information is used to analyze the behavioral patterns of ships, and the behavioral patterns are scored according to a predetermined rule. A suspicious ship can be identified and monitored from many ships. Further, according to the present invention, by predicting the future behavior patterns of ships using a heat map, it is possible to identify and monitor suspicious ships from an unspecified number of ships transmitting AIS information. .

1 is a block diagram showing a suspicious ship monitoring system according to one embodiment of the present invention; FIG. 2 is a processing flow of the monitoring device shown in FIG. 1; It is a processing flow of long-term monitoring. It is a figure which shows an example of the output result of long-term monitoring. It is explanatory drawing of heat map monitoring, (a) shows an example of a heat map, (b) shows an example which divided area|region (alpha) on a heat map by latitude and longitude.

Embodiments of the present invention will be described below with reference to FIGS. 1 to 5B. Here, FIG. 1 is a block diagram showing a suspicious ship monitoring system according to one embodiment of the present invention. FIG. 2 is a processing flow of the monitoring device shown in FIG.

A suspicious ship monitoring system according to one embodiment of the present invention comprises a ship 1 equipped with an automatic identification system (AIS) and an AIS satellite for receiving AIS information transmitted from the ship 1, as shown in FIG. 2 and an AIS ground receiving station 3, a data center 4 that collects AIS information transmitted by the ship 1 via the AIS satellite 2 and the AIS ground receiving station 3, and a suspicious ship using the AIS information acquired from the data center 4. and a monitoring device 5 for monitoring.

The ship 1 is, for example, a commercial ship such as a cargo ship, a passenger ship, or a ferry, a special ship such as a fishing boat, or a marine research ship. However, the ship 1 is not limited to these ships, and is intended to include all ships equipped with AIS.

An automatic identification system (AIS) is required to be installed on a prescribed ship from the viewpoint of collision avoidance between ships and safety of human life. AIS information communicated by AIS includes dynamic information such as position, course, speed, MMSI number (maritime mobile service identification code), which is an ID number that identifies a ship, ship name, ship size, ship type, etc. and voyage-related information such as the vessel's draft, cargo type, purpose, and estimated time of arrival.

The AIS satellite 2 is an artificial satellite that receives AIS information transmitted from ships 1 navigating the seas of the world. The AIS ground receiving station 3 is, for example, equipment for receiving AIS information transmitted from the ship 1 sailing within a range of about 100 km. AIS ground receiving stations 3 are located at important ports and sea areas.

Since the amount of data of AIS information is enormous, the AIS satellite 2 receives wide-range and low-density AIS information, and the AIS ground receiving station 3 receives local and high-density AIS information. Therefore, by using both the AIS satellites 2 and the AIS ground receiving stations 3, the data center 4 can acquire AIS information covering sea areas all over the world.

The monitoring device 5 includes, for example, a transmission/reception unit 51 that requests AIS information from the data center 4 and acquires AIS information, a calculation unit 52 that performs arithmetic processing for identifying a suspicious ship from the acquired AIS information, and a suspicious ship. setting of rules for specifying the current position information of a given ship; an input unit 53 for inputting an instruction signal to the monitoring device 5; and a display unit 54 for outputting, etc.

Currently, AIS information is used as data for position confirmation of the ship 1 . On the other hand, this embodiment is characterized by analyzing the behavior pattern of the ship 1 from AIS information and automatically specifying a suspicious ship. Here, the "suspicious vessel" is a vessel that deviates from the behavior pattern of ordinary vessels and adopts a behavior pattern that is a specific object of caution.

For example, vessels other than fishing vessels turn their course 180 degrees on the ocean, long-term berths in designated sea areas (areas where vessels do not anchor, etc.), AIS signal stops for long periods of time, and vessels other than fishing vessels enter other ports. Movements of returning to the original port without calling at a port, repeated alterations of static information included in AIS information, alteration of static information included in AIS information to unauthorized data, non-fishing vessels doing what they did in the same sea area. Any one of the reciprocating motions, the abnormal approach of two ships, or a combination of two or more of these can be presumed to be "suspicious ships". Also, if the ship 1 is registered in the blacklist of an international organization or if the ship 1 is registered in a specific country, it can be presumed to be a "suspicious ship".

The monitoring device 5 performs processing for monitoring a suspicious ship according to the processing flow shown in FIG. 2, for example. The monitoring device 5 performs a data acquisition process Step 1 to acquire AIS information from the data center 4, a data cleansing process Step 2 to delete inappropriate information from the acquired AIS information, and converts the acquired AIS information into dynamic information and data for each ship. Data merging process Step 3 for organizing static information and navigation-related information in chronological order, data analysis process Step 4 for analyzing behavior patterns of the ship 1, real-time monitoring process Step 5 for real-time monitoring, and long-term monitoring for long-term monitoring. It is configured to be able to execute a processing flow including a process Step 6 and a heat map monitoring process Step 7 for performing heat map monitoring.

The AIS information acquired in the data acquisition step Step 1 includes noise information with insufficient data, and information on vessels such as liner vessels for which it is not necessary to determine whether or not they are suspicious vessels. Therefore, in the data cleansing process Step 2, the processing load of the monitoring device 5 is reduced by thinning out the AIS information including such unnecessary information.

In the data analysis step Step 4, for example, the positional information of AIS information is plotted on a nautical chart in chronological order to identify the action pattern of the ship 1, and dynamic information, static information, and voyage-related information are plotted on the action pattern. Perform processing such as associating.

The real-time monitoring process Step 5 to the heat map monitoring process Step 7 can be arbitrarily selected and processed. In addition, the monitoring device 5 may have a configuration in which the real-time monitoring process Step 5 is omitted as necessary, and the monitoring device 5 performs only either the long-term monitoring process Step 6 or the heat map monitoring process Step 7. It may be a configuration.

The real-time monitoring step Step5 is a step of displaying the behavior pattern calculated by the data analysis step Step4 in a real-time monitorable manner. Specifically, the behavior pattern is displayed in real time on the display unit 54 of the monitoring device 5 . By monitoring the behavior patterns displayed by the monitor, it is possible to predict collisions between ships and identify suspicious ships based on experience and past cases.

The long-term monitoring step Step 6 is a step of analyzing behavior patterns of the vessel 1 over a long period of time, such as several hours or several days, and automatically identifying suspicious vessels. Specifically, the monitoring device 5 identifies the suspicious ship according to the processing flow shown in FIG. Here, FIG. 3 is a processing flow of long-term monitoring. FIG. 4 is a diagram showing an example of the output result of long-term monitoring.

As shown in FIG. 3, the monitoring device 5 includes a determination step Step 61 for determining whether or not the behavior pattern of the ship 1 calculated by the data analysis step Step 4 corresponds to a predetermined rule, and a suspicious A flagging process Step 62 of giving the ship 1 a flag that is presumed to be a ship, a score calculating process Step 63 of calculating a score by totaling the number of flags, a sorting process Step 64 of sorting the scores according to a predetermined condition, and the calculated It is configured to be able to execute a processing flow including an evaluation step Step 65 of identifying whether or not the ship is a suspicious ship based on the score.

That is, the monitoring device 5 assigns a flag to be presumed to be a suspicious ship when the behavior pattern corresponds to a predetermined rule, counts the number of assigned flags to calculate a score, and based on the calculated score It is configured to identify suspicious vessels.

Rules for assigning flags include, for example, whether a vessel other than a fishing vessel is reversing its course at sea, whether it is anchored for a long time in a predetermined sea area (a sea area where no vessels are anchored, etc.), or whether the AIS signal is long. Whether the waves are temporarily stopped, whether vessels other than fishing vessels are moving to return to the original port without calling at other ports, whether the static information included in the AIS information has been changed repeatedly, and whether the AIS information The static information contained in the data has been changed to invalid data, whether a non-fishing vessel is making repeated round trips in the same sea area, whether two vessels are approaching abnormally, or whether it is located in a specific country. Whether the ship is flagged, etc. This rule can be added or deleted as needed.

The "abnormal approach flag" shown in FIG. 4 is an item to which "1" is given when the ship 1 is abnormally close to another ship. The "long-term anchorage flag" is an item to which "1" is given when the ship 1 is anchored in a predetermined sea area for a long period of time. "Country flag" is an item to which "1" is given when the ship 1 is registered in a specific country. Further, the "illegal data flag" is an item to which "1" is assigned when static information included in AIS information is changed to invalid data. Further, the "AIS long-term cessation flag" is an item to which "1" is given when the ship 1 has not transmitted AIS information for a long time (that is, when the AIS signal has been discontinued for a long time). .

In the score calculation step Step63, the monitoring device 5 may calculate the score by adding a weighted value to the flag for each rule. For example, if the weighting for the flag Fi is Wi, the score S can be calculated by the formula S=ΣFi·Wi (i=1, 2, . . . , n).

The value of the weighting Wi is set according to the degree of suspicion of the rule. For example, a rule that determines whether a ship is registered in a blacklist of an international organization may set a large value of the weighting Wi, and a rule that determines whether a ship has been anchored in a predetermined sea area for a long time may set a small value of the weighting Wi. can be set.

In the sorting step Step64, for example, the scores may be sorted in descending order of score, or the scores may be sorted for each flagged rule. FIG. 4 shows a state in which the scores are sorted in descending order of score.

In the evaluation step Step 65, for example, a threshold may be set for the score, and if the score is equal to or greater than a predetermined threshold, the ship may be identified as a suspicious ship, and if the score is less than the threshold, the ship may be evaluated as non-suspicious. For example, in FIG. 4, "10" is set as the score threshold, and "1" is given as the suspicious flag when the total score is 10 or more. Further, in the evaluation step Step 65, when a specific rule is flagged, a suspicious flag may always be given.

In the example of the long-term monitoring output result shown in FIG. 4, it is determined that the ship 1 with the MMSI number xxxxx87 displayed at the top is the ship with the highest probability of being a suspicious ship. Therefore, the behavior of the vessel 1 with the MMSI number xxxxx87 can be monitored intensively, and can be switched to real-time monitoring.

The heat map monitoring process Step 7 is a process of specifying a suspicious ship using a heat map 6 created in advance based on the action pattern of the ship 1 . Here, FIG. 5 is an explanatory diagram of heat map monitoring, in which (a) shows an example of the heat map, and (b) shows an example of dividing the area α on the heat map by latitude and longitude.

The monitoring device 5 analyzes the action pattern of the ship 1 using AIS information, creates a heat map 6 in advance on the nautical chart from the action pattern, and uses the heat map 6 from the current position of the predetermined ship 1. It is configured to predict a future behavior pattern of a predetermined ship 1, compare the actual behavior pattern of the predetermined ship 1 with the future behavior pattern, and identify a suspicious ship.

For example, consider the ship 1 passing through the area α indicated by □ on the heat map 6 of FIG. 5( a ). The area α can be divided into a plurality of cells based on latitude and longitude, as shown in FIG. 5(b). Assume now that the area α is divided into nine cells P1 to P9.

In each cell P1 to P9 on the heat map 6, for example, as shown in Table 1, latitude, longitude, average speed of the ship 1 passing through each cell P1 to P9, speed standard deviation, average course, course standard Information such as deviation and maximum destination is assigned.

Therefore, for example, when the current position (latitude and longitude) of a predetermined ship 1 is input to the monitoring device 5, a cell containing the current position is specified, and the average speed, speed standard deviation, and average speed of the ship 1 passing through the cell are determined. Information on course, course standard deviation, and maximum destination can be obtained.

In this way, by preparing the heat map 6 in advance, dividing it into a plurality of cells, and assigning information based on the behavior patterns of the ship 1, it is possible to predict the future speed, course, etc. of the ship 1 passing through the cells. Behavioral patterns can be predicted. Then, if the subsequent actual action pattern (speed, course, destination, etc.) of the ship 1 differs from the future action pattern, the ship 1 can be presumed to be a suspicious ship.

In the heat map monitoring step Step7, as described above, by selecting the specific ship 1 and inputting the current position to the monitoring device 5, it is possible to determine whether the specific ship 1 is a suspicious ship. In addition, in the heat map monitoring step Step 7, by selecting and designating a specific area α, behavior patterns of all vessels 1 passing through the area α are analyzed to automatically determine whether or not they are suspicious vessels. can also be determined.

The vessel 1 identified as a suspicious vessel by the long-term monitoring process Step 6 and the heat map monitoring process Step 7 is displayed on the display unit 54 with a color or a mark different from that of other vessels 1, for example. In addition, regarding the vessel 1 that has been identified as a suspicious vessel in the past, even if it is not determined to be a suspicious vessel, when displaying the behavior pattern or heat map on the display unit 54, the vessel 1 may be compared with other vessels 1. They may be displayed with different colors or marks.

According to the suspicious ship monitoring system according to the present embodiment described above, AIS information is transmitted by analyzing the action pattern of the ship 1 using AIS information and scoring the action pattern according to a predetermined rule. A suspicious ship can be identified and monitored from among an unspecified number of ships 1. - 特許庁Further, according to the present embodiment, by predicting the future behavior pattern of the ship 1 using the heat map 6, a suspicious ship can be identified and monitored from an unspecified number of ships 1 transmitting AIS information. can do.

The present invention is not limited to the above-described embodiments, and various modifications are possible without departing from the scope of the present invention.

1 Ship 2 AIS satellite 3 AIS ground receiving station 4 Data center 5 Monitoring device 6 Heat map 51 Transmission/reception unit 52 Calculation unit 53 Input unit 54 Display unit Step 1 Data acquisition process Step 2 Data cleansing process Step 3 Data merging process Step 4 Data analysis process Step 5 Real-time monitoring Step 6 long-term monitoring step Step 61 judgment step Step 62 flagging step Step 63 score calculation step Step 64 sorting step Step 65 evaluation step Step 7 heat map monitoring step

Claims (6)

A data center that aggregates AIS information sent by ships;
and a monitoring device that monitors suspicious ships using the AIS information,
The monitoring device uses the AIS information to analyze the behavioral pattern of the vessel, assigns a flag that is assumed to be a suspicious vessel when the behavioral pattern corresponds to a predetermined rule, and aggregates the number of flags to obtain a score. is configured to identify the suspicious ship based on the score,
A suspicious ship monitoring system characterized by: 2. The suspicious ship monitoring system according to claim 1, wherein said monitoring device calculates said score by adding a weighted value to said flag for each rule. The above rules include the movement of vessels other than fishing vessels to reverse course 180 degrees at sea, long-term berths in sea areas where vessels do not anchor, stoppage of AIS signals for long periods of time, and no vessels other than fishing vessels to call at other ports. Movement to return to the original port, repeated alteration of the static information included in the AIS information, alteration of the static information included in the AIS information to unauthorized data, and vessels other than fishing vessels repeatedly sailing in the same sea area. 3. The suspicious ship monitoring system according to claim 1 or 2, wherein the system is one of reciprocating motion, abnormal approach of two ships, or a combination of two or more of these. A data center that aggregates AIS information sent by ships;
and a monitoring device that monitors suspicious ships using the AIS information,
The monitoring device uses the AIS information to analyze the behavioral pattern of the vessel, prepares a heat map in advance on a nautical chart from the behavioral pattern, and uses the heat map from the current position of a predetermined vessel to It is configured to predict a future behavior pattern of a predetermined vessel and compare the actual behavior pattern of the predetermined vessel with the future behavior pattern to identify the suspicious vessel.
A suspicious ship monitoring system characterized by: A data center that aggregates AIS information sent by ships;
and a monitoring device that monitors suspicious ships using the AIS information,
The monitoring device uses the AIS information to analyze the behavioral pattern of the vessel, assigns a flag that is assumed to be a suspicious vessel when the behavioral pattern corresponds to a predetermined rule, and aggregates the number of flags to obtain a score. is configured to identify the suspicious vessel based on the score,
Further, the monitoring device prepares a heat map in advance on a nautical chart from the behavior patterns, predicts the future behavior pattern of the predetermined ship using the heat map from the current position of the predetermined ship, and predicts the future behavior pattern of the predetermined ship. is configured to identify the suspicious ship by comparing the actual behavior pattern of the ship and the future behavior pattern,
A suspicious ship monitoring system characterized by: The suspicious ship monitoring system according to claim 5, wherein said monitoring device is configured to be able to monitor said behavior pattern in real time.