스마트폰 센서 데이터를 이용한 실내 응급대피용 위치 추정 연구 (A Study on the Indoor Location Determination using Smartphone Sensor Data For Emergency Evacuation)

서지정보

· 발행기관 : 대한안전경영과학회
· 수록지 정보 : 대한안전경영과학회지 / 21권 / 4호 / 51 ~ 58페이지
· 저자명 : 전욱, 장정환, 진혜명, 조용철, 이창호

초록

The LBS(Location Based Service) technology plays an important role in reducing wastes of time, losses of human lives and economic losses by detecting the user's location in order by suggesting the optimal evacuation route of the users in case of safety accidents. We developed an algorithm to estimate indoor location, movement path and indoor location changes of smart phone users based on the built-in sensors of smartphones and the dead-reckoning algorithm for pedestrians without a connection with smart devices such as Wi-Fi and Bluetooth. Furthermore, seven different indoor movement scenarios were selected to measure the performance of this algorithm and the accuracy of the indoor location estimation was measured by comparing the actual movement route and the algorithm results of the experimenter(pedestrian) who performed the indoor movement. The experimental result showed that this algorithm had an average accuracy of 95.0%.

영어초록

The LBS(Location Based Service) technology plays an important role in reducing wastes of time, losses of human lives and economic losses by detecting the user's location in order by suggesting the optimal evacuation route of the users in case of safety accidents. We developed an algorithm to estimate indoor location, movement path and indoor location changes of smart phone users based on the built-in sensors of smartphones and the dead-reckoning algorithm for pedestrians without a connection with smart devices such as Wi-Fi and Bluetooth. Furthermore, seven different indoor movement scenarios were selected to measure the performance of this algorithm and the accuracy of the indoor location estimation was measured by comparing the actual movement route and the algorithm results of the experimenter(pedestrian) who performed the indoor movement. The experimental result showed that this algorithm had an average accuracy of 95.0%.

참고자료

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