# US 2018/0025644 A1 · Method and apparatus for monitoring marine traffic > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 2018/0025644 A1 - Document ID: US20180025644A1 - Status: Published application - Kind: A1 - Application number: 15/655,996 - Filed: 2017-07-21 - Published: 2018-01-25 - Earliest claimed: 2016-07-22 - Assignees: Mokpo National Maritime University Industry-Academic Corporation Foundation - Applicants: Mokpo National Maritime University Industry-Academic Corporation Foundation - Inventors: Jung Sik JEONG; Joo Sung KIM - Web page: https://patentgrep.com/patent/US20180025644A1 ## CPC - G08G 1/166: {for active traffic, e.g. moving vehicles, pedestrians, bikes} - G08G 3/02: Anti-collision systems - G08G: TRAFFIC CONTROL SYSTEMS (guiding railway traffic, ensuring the safety of railway traffic B61L; arrangement of road signs or traffic signals E01F9/00; radar or analogous systems, sonar systems, lidar systems specially adapted for traffic control G01S13/91, G01S15/88, G01S17/88; {radar or analogous systems, sonar systems, lidar systems specially adapted for anti-collision purposes G01S13/93, G01S15/93, G01S17/93}) ## Abstract The present disclosure in some embodiments relates to a method and an apparatus for monitoring a marine traffic, which learn navigation data of a plurality of ships sailing over an area to be monitored to calculate standard navigation data models for respective navigation sections, and monitor the state of navigation of the ship to be monitored based on the calculated standard navigation data models, and thereby provide an accurate and objective marine traffic monitoring. ## Claims ### Claim 1 An apparatus for monitoring a marine traffic, comprising at least one processor to implement: a navigation data collection unit configured to collect navigation data including a ship-related information of a plurality of ships sailing over an area to be monitored; a sectional navigation data generating unit configured to generate sectional navigation data by classifying the navigation data for each of navigation sections based on the ship-related information; a learned data generating unit configured to learn a sectional ship-related information included in the sectional navigation data, and generate learned data; and a standard navigation data model calculation unit configured to calculate standard navigation data models for respective navigation sections by using the learned data. ### Claim 2 (depends on 1) The apparatus of claim 1, wherein the processor further implements a navigation state monitoring unit configured to obtain navigation data of a ship to be monitored, and monitor a state of navigation of the ship to be monitored by applying the standard navigation data models to obtained navigation data. ### Claim 3 (depends on 2) The apparatus of claim 2, wherein the navigation state monitoring unit comprises a navigation monitoring module which comprises at least one of: a deviation discrimination unit configured to discriminate whether or not the ship to be monitored exhibits a deviation; a location prediction unit configured to predict a location of the ship to be monitored; and an emergency situation judgement unit configured to determine whether or not an emergency situation occurs in the ship to be monitored, wherein the navigation monitoring module monitors the state of navigation based on a corresponding standard navigation data model corresponding to a navigation section of the ship to be monitored among the standard navigation data models. ### Claim 4 (depends on 3) The apparatus of claim 3, wherein the deviation discrimination unit is configured to calculate, on a standard travel route of the ship defined in the corresponding standard navigation data model, an approximate point having the smallest positional difference from a current location of the ship to be monitored, and discriminate whether or not the ship to be monitored exhibits a deviation or navigational irregularity based on a defined navigation data for the approximate point and the navigation data of the ship to be monitored. ### Claim 5 (depends on 3) The apparatus of claim 3, wherein the location prediction unit is configured to calculate, on a standard travel route of the ship defined in the corresponding standard navigation data model, an approximate point having the smallest positional difference from a current location of the ship to be monitored, and calculate an estimated location of the ship to be monitored based on a defined navigation data for a navigation section spanning from the approximate point to an end point of the standard travel route and on an input value of a location estimation time of the ship to be monitored. ### Claim 6 (depends on 3) The apparatus of claim 3, wherein the emergency situation judgement unit is configured to calculate, on a standard travel route of the ship defined in the corresponding standard navigation data model, an approximate point having the smallest positional difference from a current location of the ship to be monitored, and determine whether or not there is a danger of collision between an approaching ship within a range preset with respect to the approximate point and the ship to be monitored. ### Claim 7 (depends on 6) The apparatus of claim 6, wherein the emergency situation judgement unit is configured to determine whether or not there is the danger of collision based on at least one of: whether there is a potential collision spot having the smallest positional difference between the ship to be monitored and the approaching ship in a navigation section spanning between the approximate point and an end point of the standard travel route, and an expected arrival time of the ship to be monitored and the approaching ship to the potential collision spot. ### Claim 8 (depends on 1) The apparatus of claim 1, wherein the navigation data collection unit is configured to collect ship specification information comprising types and sizes of the ships and ship navigation information comprising information on locations, speeds and courses of the ships, as the navigation data. ### Claim 9 (depends on 1) The apparatus of claim 1, wherein the sectional navigation data generating unit is configured to confirm navigation start points and navigation end points of the plurality of ships and calculate navigation section information for each of the plurality of ships, and generate the sectional navigation data by classifying navigation data of ships having an identical navigation section among the plurality of ships, into a common group. ### Claim 10 (depends on 1) The apparatus of claim 1, wherein the standard navigation data model calculation unit is configured to calculate the standard navigation data model comprising some or all of: an extracted track model defining standard travel routes of the ships navigating the navigation sections based on the learned data; an extracted speed change model defining standard speed information of the ships navigating the navigation sections; and a course change model defining standard navigation direction information of the ships navigating the navigation sections. ### Claim 11 (depends on 1) The apparatus of claim 1, wherein the learned data generating unit is configured to learn the sectional ship-related information included in the sectional navigation data based on a machine learning algorithm. ### Claim 12 (depends on 1) The apparatus of claim 1, wherein the standard navigation data model calculation unit is configured to generate a plurality of candidate navigation data models defining pattern information of at least one of travel routes, speed changes and course changes of the ships navigating the navigation sections based on the learned data, and calculate a candidate navigation data model whose validation error is the minimum among the plurality of candidate navigation data models as the standard navigation data model. ### Claim 13 A method of monitoring a marine traffic, comprising: collecting navigation data including a ship-related information of a plurality of ships sailing over an area to be monitored; generating sectional navigation data by classifying the navigation data for each of navigation sections based on the ship-related information; learning a sectional ship-related information included in the sectional navigation data and generating learned data; and calculating standard navigation data models for respective navigation sections by using the learned data. ### Claim 14 (depends on 13) The method of claim 13, further comprising: obtaining navigation data of a ship to be monitored; and monitoring a state of navigation of the ship to be monitored by applying the standard navigation data models to obtained navigation data. ### Claim 15 (depends on 14) The method of claim 14, wherein the monitoring of the state of navigation is performed based on the standard navigation data models and navigation data of the ship to be monitored and comprises at least one of: discriminating whether or not the ship to be monitored exhibits a deviation or navigational irregularity; predicting a location of the ship to be monitored; and determining whether or not an emergency situation occurs in the ship to be monitored.