DOI QR코드

DOI QR Code

Implementation of Intelligent Remote Control System based on Internet of Things

사물인터넷을 활용한 지능형원격제어시스템 구현

  • Kim, Dong Min (Department of Internet of Things, Soonchunhyang University)
  • Received : 2020.02.26
  • Accepted : 2020.03.05
  • Published : 2020.04.30

Abstract

The remote control system, in which the remote control server and the actuator are connected and operated through a wireless network, has a great potential risk as well as its convenience. The control commands can be lost because of unreliable wireless channels. The intelligent remote control system is a system that adds a function to infer a control command to the actuator to operate even if the control command is not received. In this paper, we implemented an intelligent remote control system testbed and confirmed the problems that could occur in the remote control system through experiments and verified that the intelligent remote control system solves the problem. The intelligent remote control system can achieve the performance that can be achieved when general remote control system has high communication overhead with less communication overhead.

원격제어서버와 작동기가 무선네트워크를 통해 연결되어 동작하는 원격제어시스템은 그 편의성이 큰 만큼 잠재된 위험성도 크다. 신뢰할 수 없는 무선 채널로 인해 제어명령이 유실될 수 있기 때문이다. 지능형원격제어시스템은 작동기에 제어명령을 유추할 수 있는 기능을 추가하여 제어명령을 수신하지 못하는 경우에도 동작하도록 해주는 시스템이다. 본 논문에서는 지능형원격제어시스템 테스트베드를 구현하여 원격제어시스템에서 발생할 수 있는 문제 상황들을 실험을 통해 확인하고 지능형원격제어시스템이 문제를 해결하는 것을 검증하였다. 지능형원격제어시스템은 일반적인 원격제어시스템이 높은 통신오버헤드를 감수해야 달성할 수 있는 성능을 더 적은 통신오버헤드만으로도 달성할 수 있음을 확인하였다.

Keywords

References

  1. M. R. Alam, M. B. I. Reaz, and M. A. M. Ali, "A review of smart homes-Past, present, and future," IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews), vol. 42, no. 6, pp. 1190-1203, Apr. 2012. https://doi.org/10.1109/TSMCC.2012.2189204
  2. J. Pan, R. Jain, and S. Paul, "A survey of energy efficiency in buildings and microgrids using networking technologies," IEEE Communications Surveys & Tutorials, vol. 16, no. 3, pp. 1709-1731, Jun. 2014. https://doi.org/10.1109/SURV.2014.060914.00089
  3. B. Holfeld, D. Wieruch, T. Wirth, L. Thiele, S. A. Ashraf, J. Huschke, I. Aktas, and J. Ansari, "Wireless communication for factory automation: An opportunity for LTE and 5G systems," IEEE Communications Magazine, vol. 54, no. 6, pp. 36-43, Jun. 2016. https://doi.org/10.1109/MCOM.2016.7497764
  4. K. Lee, Y. Shin, Y. Lee, and S. Seol, "A study on user interface and control method of web-based remote control platform," Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology, vol. 7, no. 6, pp. 827-837, Jun. 2017. https://doi.org/10.14257/AJMAHS.2017.06.59
  5. K. Cho, M. Jeon, and C. Oh, "Development of equipment control system based on DB access method for industrial IoT," Journal of the Korea Institute of Information and Communication Engineering, vol. 20, no. 6, pp. 1142-1147, Jun. 2016. https://doi.org/10.6109/jkiice.2016.20.6.1142
  6. M. A. Lema, A. Laya, T. Mahmoodi, M. Cuevas, J. Sachs, J. Markendahl, and M. Dohler, "Business case and technology analysis for 5G low latency applications," IEEE Access, vol. 5, pp. 5917-5935, Apr. 2017. https://doi.org/10.1109/ACCESS.2017.2685687
  7. A. Seuret, L. Hetel, J. Daafouz, and K. H. Johansson, Delays and Networked Control Systems, Springer, 2014.
  8. D. Jang, C. Y. Son, J. Yoo, H. J. Kim, and K. H. Johansson, "Efficient neworked UAV control using event-triggered predictive control," in Proceeding of the 8th IFAC Symposium on Mechatronic Systems MECHATRONICS 2019, Vienna, Austria, 2019.
  9. H. Li, K. Ota, and M. Dong, "Learning IoT in edge: deep learning for the Internet of Things with edge computing," IEEE Network, vol. 32, no. 1, pp. 96-101, Jan. 2018. https://doi.org/10.1109/MNET.2018.1700202
  10. G. Premsankar, M. D. Francesco, and T. Taleb, "Edge computing for the Internet of Things: a case study," IEEE Internet of Things Journal, vol. 6, no. 2, pp. 1276-1284, Apr. 2018.
  11. J.-B. Kim, D.-H. Kwon, Y.-G. Hong, H.-K. Lim, M.-S. Kim, and Y.-H. Han, "Deep Q-network based rotary inverted pendulum system and its monitoring on the EdgeX platform," in Proceeding of the 1st International Conference on Artificial Intelligence in Information and Communication, Okinawa, Japan, 2019.
  12. WebIOPi [Internet]. Available: https://webiopi.trouch.com/.
  13. I. Goodfellow, Y. Bengio and A. Courville, Deep Learning, MIT Press, 2016.