• 한국정보통신학회논문지
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• 제4권1호
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• pp.179-189
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• 2000

최근 들어 심해개발에 대한 관심이 고조됨에 따라 AUV 또는 수중 로봇과 같은 수중 무인작업선의 개발을 위하여 많은 노력을 하였다. 본 논문은 초음파의 전송지연을 고려하지 않고 최대 처리량의 일정수준을 확보하고 다중 초음파 통신 채널을 통하여 고속의 데이터 전송이 가능한 새로운 고효율의 음향 기반 수중 영상 통신시스템을 제시한다. 제시된 시스템은 중심주파수가 136khz이고 10khz의 밴드 폭에서 동작하는 음향 트랜스듀서, 전단증폭기, $\pi/4 QPSK$ 변복조 방식, JPEG 기술을 사용한 영상 압축방식과 수정된 Stop & Wait 프로토콜로 구성한다. 실험 결과는 수조 테스트에서 고효율의 수중영상 전송이 가능하였고, 또한 그 결과는 기존에 개발된 시스템과 타당한 전송성능을 비교 입증하였고 해양에서 실용 가능성을 연구 검토하였다.

• 센서학회지
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• 제31권6호
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• pp.433-440
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• 2022

Recently, owing to global warming, average summer temperatures are increasing and the number of hot days is increasing is increasing, which leads to an increase in heat stroke. In particular, outdoor workers directly exposed to the heat are at higher risk of heat stroke; therefore, preventing heat-related illnesses and managing safety have become important. Although various wearable devices have been developed to prevent heat stroke for outdoor workers, applying various sensors to the safety helmets that workers must wear is an excellent alternative. In this study, we developed a smart helmet that measures various vital signs of the wearer such as body temperature, heart rate, and sweat rate; external environmental signals such as temperature and humidity; and movement signals of the wearer such as roll and pitch angles. The smart helmet can acquire the various data by connecting with a smartphone application. Environmental data can check the status of heat wave advisory, and the individual vital signs can monitor the health of workers. In addition, we developed an algorithm that classifies the risk of heat-related illness as normal and abnormal by inputting a set of vital signs of the wearer using a support vector machine technique, which is a machine learning technique that allows for rapid binary classification with high reliability. Furthermore, the classified results suggest that the safety manager can supervise the prevention of heat stroke by receiving feedback from the control system.