Despite the maritime industry’s significant role in the global economy, maritime accidents are a threat to life at sea and maritime economic performance. Furthermore, the human factor still accounted for as the main factor causing maritime accidents. Every year, many maritime accidents occur in Japan and Hong Kong, with collisions being the most common. In this study, Human Error Assessment and Reduction Technique (HEART) method is applied to the collisions data to identify the common mistakes committed by seafarers by determining the generic task, error-producing conditions and the value of Human Error Probability (HEP). This study aims to find the causes of collision in Japan and Hong Kong, compare them between the two countries, and apply HEART methodology to various maritime accidents. The data was sourced from the maritime accident data report of the Japan Transportation and Safety Board and the Government of the Hong Kong Special Administrative Region of the Marine Department from 2008 to 2016. There are 27 collision cases for Japan and 21 for Hong Kong. In general, human error is the most common factor leading to collisions. In conclusion, in Japan’s collision assessment, fairly simple tasks performed rapidly or with scant attention are identified as the most common generic task. However, in Hong Kong, most of the accidents occur during complex tasks. Japan has 101 EPCs for 27 cases while there are 115 EPCs for 21 cases that occurred in Hong Kong. Both Japan and Hong Kong have the time shortage, inadequate checking of progress, and poor information exchange among seafarers on the bridge as the common error-producing conditions occurred.

최근 GPS와 Wi-Fi가 내장된 스마트폰의 보급으로 이를 이용한 위치기반 서비스 (Location-based Service)가 발전하고 있다. 하지만 위치기반 서비스들의 오차 범위는 3∼4m 내외로 크기 때문에 사용자들은 더 정확한 위치를 제공하기를 바라고 있다. 본 논문에서 위치기반 서비스의 핵심기능을 담당하는 측위기술 중 흔히 사용되고 있는 삼각측량법을 활용하여 핑거프린트 방법의 측위오차를 줄일 수 있는 방안을 연구하였 고 프로그램으로 구현한 후 테스트를 실시하였다. 프로그램은 Labview2010으로 구현 하였고, 각각의 알고리즘을 모듈화하여 필터링 적용 전 후 및 개선효과를 비교하기 쉽 도록 구성하였다. 실내 테스트는 인하대학교의 강의실에서 실시하였고 실외 테스트는 인하대학교 운동장에서 실시하였다. 테스트 결과 실내의 경우 본 논문에서 제시하는 필터링 방법을 적용하기 전의 오차가 1.02미터에서 0.83미터로 감소하였고 실외에서는 0.74미터에서 0.54미터로 오차가 감소하였다.

Location-Based Services(LBS) is a service that provide location information by using communication network or satellite signal. In order to provide LBS precisely and efficiently, we studied how we can reduce the error on location determination of objects such people and things. We focus on using the least square method and triangulation positioning method to improves the accuracy of the existing location determination method. Above two methods is useful if the distance between the AP and the tags can be find. Though there are a variety of ways to find the distance between the AP and tags, least squares and triangulation positioning method are wildely used. In this thesis, positioning method is composed of preprocessing and calculation of location coordinate and detail of methodology in each stage is explained. The distance between tag and AP is adjusted in the preprocessing stage then we utilize least square method and triangulation positioning method to calculate tag coordinate. In order to confirm the performance of suggested method, we developed the test program for location determination with Labview2010. According to test result, triangulation positioning method showed up loss error than least square method by 38% and also error reduction was obtained through adjustment process and filtering process. It is necessary to study how to reduce error by using additional filtering method and sensor addition in the future and also how to improve the accuracy of location determination at the boundary location between indoor and outdoor and mobile tag.

본 논문에서는 위치기반서비스의 핵심기능을 담당하는 측위기술 중 흔히 사용되고 있는 삼각측량법과 최소자승법을 보정한 방법을 이용하여 객체의 위치를 결정하는 알고리즘의 산포를 감소시키는 방안을 연구하였다. 두 측위 방법에서 사용되는 거리값은 모두 동일한 보정과 필터링 과정을 적용하였으며, 프로그램 구현 후 실내에서 테스트를 실시하였다. 프로그램은 LabView 2010으로 구현하였고, 각각의 알고리즘을 모듈화하여 필터링 적용 전후 및 개선효과를 비교하기 쉽도록 구성하였다. 일반적인 환경에서 실험한 결과 삼각측량이 최소자승법보다 더 좋은 정확도를 보여주었고, 필터링 과정을 거칠수록 정확도가 향상되는 것을 확인하였다.

Location-Based Service(LBS) is a service that provides a variety of convenience in life using location information that can be obtained by mobile communication network or satellite signal. In order to provide LBS precisely and efficiently, we need the location determination technology, platform technology and server technology. In this study, we studied on how we can reduce the error on location determination of objects such people and things. Fingerprint location determination method was applied to this study because it can be used at current wireless communication infrastructure and less influenced by a variety of noisy environment than other location determination methods. We converted the probability value to logarithmic scale value because using the sum of k probability values is not suitable to be applied to weight determination. In order to confirm the performance of suggested method, we developed location determination test program with Visual Basic 6.0 and performed the test. According to indoor and outdoor test results, the suggested stochastic method reduced the distance error by 17%, 18% and 9% respectively at indoor environment and 25%, 11% and 4% at outdoor environment compared with deterministic NN, kNN and kWNN fingerprint methods.