• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.3
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• pp.469-478
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• 2022

This paper contains the results of developing smart devices and applications to monitor the load power of the industrial manufacturing machine and evaluate its performance. The smart devices in this paper are divided into two functionalities, which are collecting load power along with operating environment data of industrial manufacturing machines and transmitting the data to servers. Load power data collected from the smart devices are uploaded to MariaDB inside the Amazon Web Service (AWS) server. Using the RESTFul API, the uploaded power data can be retrieved and shown on the web and mobile application in the form of a graph to provide monitoring capability. To evaluate the performance of the developed system, the response time from MariaDB to web and mobile applications was measured. The results is ranging from 0.0256 to 0.0545 seconds in a 4G (LTE) network environment and from 0.6126 to 1.2978 seconds in a 3G network environment, which is considered a satisfactory result.

• Proceedings of the Korea Information Processing Society Conference
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• 2024.05a
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• pp.546-547
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• 2024

의료용 헬스케어 데이터를 기반으로 혈당, 혈압, 온도와 같은 헬스케어 의료기기 개발에서 정확하고 정밀도가 높은 결과를 얻기 위해 다기능의 센서들이 집적화 되고 있다. 그러나 이러한 헬스케어용 의료기기들은 24 시간 구동하기 때문에 전력소모가 크므로 실시간 모니터링이 필요하다. 본 논문은 웨어러블 센서에 보조전력 구동을 위한 유연태양전지의 전기적 및 광학적 데이터 분석을 통해 향후 헬스케어 디바이스 장치 구동을 위한 고효율의 태양전지를 전원보조장치로 활용하고자 한다.