• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.1202-1205
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• 2005

This paper describes a method for vision-based person identification that can detect, track, and recognize person from video using multiple cues: height and dressing colors. The method does not require constrained target's pose or fully frontal face image to identify the person. First, the system, which is connected to a pan-tilt-zoom camera, detects target using motion detection and human cardboard model. The system keeps tracking the moving target while it is trying to identify whether it is a human and identify who it is among the registered persons in the database. To segment the moving target from the background scene, we employ a version of background subtraction technique and some spatial filtering. Once the target is segmented, we then align the target with the generic human cardboard model to verify whether the detected target is a human. If the target is identified as a human, the card board model is also used to segment the body parts to obtain some salient features such as head, torso, and legs. The whole body silhouette is also analyzed to obtain the target's shape information such as height and slimness. We then use these multiple cues (at present, we uses shirt color, trousers color, and body height) to recognize the target using a supervised self-organization process. We preliminary tested the system on a set of 5 subjects with multiple clothes. The recognition rate is 100% if the person is wearing the clothes that were learned before. In case a person wears new dresses the system fail to identify. This means height is not enough to classify persons. We plan to extend the work by adding more cues such as skin color, and face recognition by utilizing the zoom capability of the camera to obtain high resolution view of face; then, evaluate the system with more subjects.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.14 no.6
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• pp.1453-1459
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• 2010

Recently, the aim of cold storage warehouse is not only to provide preservation of the quality of perishable foods but also to use state-of-the-art information systems to rapidly move products across the cold chain. An RFID (Radio Frequency Identification) is an automatic identification method that detects signals from mobile objects, and tracks and traces movement of the objects. RFID can be used to turn a cold storage warehouses into a real-time system. In this paper, we develop an cold storage management system to support the optimized business processes with RFID system. First of all, business processes in the cold storage warehouse are analyzed. Then design factors which should be considered for incorporating RFID are defined. Design values which set to the design factors can be extracted from using RFID deployment simulator. as a result, the design values make RFID to be efficiently integrated to existing business processes.

• Journal of the Institute of Convergence Signal Processing
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• v.14 no.2
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• pp.77-81
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• 2013

The international standard AIS, which stands for the safety of ship navigation and vessel traffic management, provides 27 messages to exchange the navigational information of ship. Among 27 messages, message ID 6 and 8 are defined as the binary data format to exchange application specific information and are classified into IFM for international use and RFM for national or regional use. Since international standards are based on English, there have been some needs to exchange data in Hangul text for vessel traffic management to correct the static and dynamic ships' information. In this paper, I analyze international standards to provide a Hangul text messaging service based on RFM and propose a RFM message and a simple protocol to correct information of a ship.

• Journal of the Korean Institute of Intelligent Systems
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• v.23 no.3
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• pp.256-261
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• 2013

The AIS(Automatic Identification System) has been widely used for ship safety at sea over the last 10 years. The AIS traffic load at VDL(VHF Data Link) has been continuously increased. As the traffic load at VDL increases, the quality of AIS service may be deteriorated. In the previous research, the AIS traffic has been analyzed in the major ports of Korea, and its problem due to traffic overload has been suggested. However, no solutions has been given so far. In this paper, the method of autimatically controlling the VDL traffic at AIS base station is represented.

• The Journal of the Korea Contents Association
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• v.7 no.12
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• pp.333-345
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• 2007

In the recent years, the companies have manually recorded a production status in a work diary or have mainly used a bar code in order to collect each process's progress status, production performance and quality information in the production and logistics process in real time. But, it requires an additional work because the worker's record must be daily checked or the worker must read it with the bar code scanner. At this time, data's accuracy is decreased owing to the worker's intention or mistake, and it causes the problem of the system's reliability. Accordingly, in order to solve such problem, the companies have introduced RFID which comes into the spotlight in the latest automatic identification field. RFID is an automatic identification technology by radio communication technology that allows us to identify or record information without contacting the corresponding object, and as Gen2 and EPCIS, EPCglobal's standard tag for RFID, have recently been established, it will be introduced to the whole computation industry. This study suggests RFID type Modeling Notation for analyzing logistics flow to improve MES focusing on extended model of EPCIS, and EPCISEvent Template in manufacturing industry.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2009.06a
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• pp.425-431
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• 2009

Recently, new technology has been introducing according to the efforts for maritime safety, traffic and environmental protection that uses electronic method to make use of maritime information effectively. To be associated with the tendance, international society which centered to IALA Introduces advanced technology of AtoN with Automatic Identification System(AIS) that it is crucial method to collect and transmit maritime data. This article is to thoroughly analyse and investigate the international and national regulation of related AtoN AIS, and propose to be included and applied into national radio-communication equipment regulation.

• Journal of the Korean Institute of Intelligent Systems
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• v.22 no.6
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• pp.761-767
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• 2012

Maritime traffic assessment is important to understand the characteristics of maritime traffic and to prevent maritime accidents. The maritime traffic assessment can be calculated from the ship trajectory data observed by using AIS(Automatic Identification System). This paper developes a maritime traffic assessment tool using ship's position and speed, course, time data from ships navigating waterways. The results are represented in terms of the number of traffic quantity and traffic distribution, speed distribution, geometric collision candidates. The developed tool will contributes to advance maritime traffic safety by VTS(Vessel Traffic Services).

• Journal of the Korea Society of Computer and Information
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• v.24 no.10
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• pp.65-70
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• 2019

In recently, ship trajectory data consisting of ship position, speed, course, and so on can be obtained from the Automatic Identification System device with which all ships should be equipped. These data are gathered more than 2GB every day at a crowed sea port and used for analysis of ship traffic statistic and patterns. In this study, we propose a method to process ship trajectory data efficiently with distributed computing resources using MapReduce algorithm. In data preprocessing phase, ship dynamic and static data are integrated into target dataset and filtered out ship trajectory that is not of interest. In mapping phase, we convert ship's position to Geohash code, and assign Geohash and ship MMSI to key and value. In reducing phase, key-value pairs are sorted according to the same key value and counted the ship traffic number in a grid cell. To evaluate the proposed method, we implemented it and compared it with IALA waterway risk assessment program(IWRAP) in their performance. The data processing performance improve 1 to 4 times that of the existing ship trajectory analysis program.

• International Journal of Naval Architecture and Ocean Engineering
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• v.12 no.1
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• pp.440-454
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• 2020

To prevent pollution from ships, the Energy Efficiency Design Index (EEDI) is a mandatory guideline for all new ships. The Ship Energy Efficiency Management Plan (SEEMP) has also been applied by MARPOL to all existing ships. SEEMP provides the Energy Efficiency Operational Indicator (EEOI) for monitoring the operational efficiency of a ship. By monitoring the EEOI, the shipowner or operator can establish strategic plans, such as routing, hull cleaning, decommissioning, new building, etc. The key parameter in calculating EEOI is Fuel Oil Consumption (FOC). It can be measured on board while a ship is operating. This means that only the shipowner or operator can calculate the EEOI of their own ships. If the EEOI can be calculated without the actual FOC, however, then the other stakeholders, such as the shipbuilding company and Class, or others who don't have the measured FOC, can check how efficiently their ships are operating compared to other ships. In this study, we propose a method to estimate the EEOI without requiring the actual FOC. The Automatic Identification System (AIS) data, ship static data, and environment data that can be publicly obtained are used to calculate the EEOI. Since the public data are of large capacity, big data technologies, specifically Hadoop and Spark, are used. We verify the proposed method using actual data, and the result shows that the proposed method can estimate EEOI from public data without actual FOC.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2020.11a
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• pp.54-55
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• 2020

In 4th Industrial Revolution, technologies such as artificial intelligence, Internet of Things, and Big data are closely related to the maritime industry, which led to the birth of autonomous vessels. Due to the technical characteristics of the current vessel, the speed cannot be suddenly lowered, so complex communication such as the help of a tug boat, boarding of a pilot, and control of the vessel at the onshore control center is required to berth at the port. In this study, clustering analysis was used to resolve how to establish control criteria for vessels to enter port when autonomous vessels are operating. K-Means clustering was used to quantitatively stage the arrival pattern based on the accumulated AIS(Automatic Identification System) data of the incoming vessel, and the arrival phase using SOG(Speed over Ground), COG(Course over Ground), and ROT(Rate of Turn) Was divided into six phase.