DOI QR코드

DOI QR Code

Smart Air Conditioning Service Using Bio-signal and Emotional Lighting

생체신호와 감성조명을 이용한 스마트 에어컨 서비스

  • Kim, Jong-Min (Dept. of Computer Engineering, Dongshin University) ;
  • Ryu, Gab-Sang (Dept. of Computer Engineering, Dongshin University)
  • 김종민 (동신대학교 컴퓨터공학과) ;
  • 류갑상 (동신대학교 컴퓨터공학과)
  • Received : 2021.08.31
  • Accepted : 2021.09.20
  • Published : 2021.09.28

Abstract

Recently, in the market of home appliances, the technical differentiation of products using convergence technology has been receiving a lot of response to satisfy consumer demand. However, air-conditioner products are an area that requires research and development in the early stages of convergence technology. In this paper, it is developed that a non-contact bio-signal(respiration, movement) collection technology using IR-UWB(Impulse-Radio Ultra Wideband) technology, which controls the air-conditioner direction according to the user's location and also monitors sleep to provide an optimal sleep environment. In addition, emotional lighting and ASMR are developed to provide a comfortable and emotional place of life. Finally, based on the developed convergence technology, we develop intelligent smart air-conditioning services for the convenience of daily life and a comfortable resting space.

최근들어 가전시장에서 융합기술을 이용한 제품 차별화는 소비자로부터 많은 호응을 얻고 있다. 그러나 에어컨 제품은 기계적 운영에서 센서와 플랫폼이 결합된 인공지능을 위한 융합기술이 적용하는 초기단계에 있어서 많은 연구개발이 필요한 분야이다. 본 논문에서는 IR-UWB 기술을 이용한 비접촉 방식의 생체신호(호흡수, 이동) 수집기술을 개발하였다. 생체신호를 이용하여 사용자의 위치에 따라 에어컨 방향을 제어한다. 또한 최적의 수면 환경을 제공하기 위해 수면상태를 모니터링 한다. 감성조명과 ASMR은 안락하고 감성적인 삶의 공간을 제공하기 위해 개발되었다. 그리고 개발된 융합기술을 기반으로 편리하고 안락한 휴식공간을 제공하는 지능형 스마트 에어컨 서비스 플랫폼을 제안하였다.

Keywords

References

  1. J. H. Ryu. (2017). Industry status and prospect - Home Appliance Industry : Forcusing on White Goods. KEA. http://www.gokea.org.
  2. N. M. Park. (2021). Research Trend of Artificial Intelligence Control of Multi-System Air Conditioner. The Magazine of the Society of Air-Conditioning and Refrigerating Engineers of Korea, 50(2), 72-84. ISSN : 1229-6430
  3. J. H. Choi, J. W. Choi, & Y. I. Yoon. (2016). IoT Platform Technology Review. Korea Information Processing Society, 23(3), 19-24. ISSN : 1226-9182, E-ISSN 0387-5806
  4. L. Min, G. Wenbin, C. Wei, H. Yeshen, W. Yannian, Z. Yiying, et al. (2018). Smart Home: Architecture, Technologies, and Systems. Procedia Computer Science, 131, 393-400. DOI : 10.1016/j.procs.2018.04.219
  5. J. H. Hong, & K. H. Lee. (2019). A Scheme on Object Tracking Techniques in Multiple CCTV IoT Enviroments, Journal of The Korea Internet of Things Society, 5(1), 7-11. DOI : 10.20465/KIOTS.2019.5.1.007
  6. T. K. Kim. (2016). IoT-based Indoor Localization Scheme, Journal of The Korea Internet of Things Society, 2(4), 35-39. DOI : 10.20465/KIOTS.2016.2.4.035
  7. S. S. Byun. (2019). A Non-contact Realtime Heart Rate Estimation Using IR-UWB Radar. Journal of Embedded Systems and Applications, 14(3), 123-131. DOI : 10.14372/IEMEK.2019.14.3.123
  8. A. Q. Javaid, C. M. Noble, R. Rosenberg, & M. A. Weitnauer. (2015). Towards Sleep Apnea Screening with an Under-the-mattress IR-UWB Radar Using Machine Learning. Proceedings of IEEE International Conference on Machine Learning and Applications, 837-842. DOI : 10.1109/ICMLA.2015.79
  9. Y. J. Park, H. S. Cho, & H. K. Lyu. (2016). A method of detection of respiration rate on Android using UWB Impulse Radar. ICT Express, 2(4), 145-149. DOI : 10.1016/j.icte.2016.08.012
  10. K. W. Choi, C. S. Kim, C. S. Yang, & J. G. Lee. (2014). A study on a target-tracking and noncontact type biosignal measurement system Using IR-Radar and Pan-Tilt system. The Journal of the Korean Institute of Information and Communication Engineering, 18(9), 2237-2242. DOI : 10.6109/jkiice.2014.18.9.2237
  11. J. W. Choi, Y. N. Lee, S. H. Cho, & Y. H. Lim. (2017). Sleep Efficiency Measurement Algorithm Using an IR UWB Radar Sensor. The Korean Institute of Communications and Information Sciences, 42(1), 214-217. DOI : 10.7840/kics.2017.42.1.214
  12. J. C. Lee. (2020). Design of Smart Pillow System for Managing Sleep Apnea. Journal of the Korea Convergence Society, 11(1), 33-39. DOI : 10.15207/JKCS.2020.11.1.033
  13. D. W. Lee, S. I. Park, & M. C. Whang (2017). Emotion Recognition Method Using Heart-Respiration Connectivity. Korean Society for Emotion and Sensibility, 20(3), 61-70. DOI : 10.14695/KJSOS.2017.20.3.61
  14. K. T. Kim, S. Y. Oh, M. Yu, C. H. Yu, & T. K. Kwon. (2014). Study on Human Physiological Responses to Emotional Lighting System using LED Flat Lighting. Korean Society for Emotion and Sensibility, 17(3), 29-38. DOI : 10.14695/KJSOS.2014.17.3.29
  15. S. J. Yun, S. I. Hong, & C. H. Lin. (2016). An Efficient Smart Indoor Emotional Lighting Control System based on Android Platform using Biological Signal. Journal of Korean Institute of Internet, Broadcasting and Communication, 16(1), 199-207. DOI : 10.7236/JIIBC.2016.16.1.199
  16. J. C. Lee, & J. R. Kim. (2019). Analysis of The Relaxing Effect of ASMR Sound Contents. Journal of the Institute of Electronics and Information Engineers, 56(3), 139-145. DOI : 10.5573/ieie.2019.56.3.139
  17. Wikipedia. Respiratory rate. https://ko.wikipedia.org