Journal of Computing and Natural Science

An Evaluation of Internet of Things and Cyber-Physical System Integration

Journal of Computing and Natural Science

Received On : 23 May 2022

Revised On : 18 June 2022

Accepted On : 25 July 2022

Published On : 05 October 2022

Volume 02, Issue 04

Pages : 143-152


In order to make physical systems run more efficiently and effectively at multiple levels of information processing, Cyber-Physical Systems (CPS) combine physical processes, Computing, Communication, and Control (the 3Cs) into a single system. There are many factors that make solving the problem of packet transmission in CPS difficult, including unforeseeable node mobility, low number of nodes, lack of global data, and intermittent network access. Currently, there is no good answer to this problem in the literature. The impact of the CPS on engineered systems is much greater in the present and future. Cyber-physical system integration often presents unique challenges in the fields of design, implementation, and application. One of the goals of this research is to better understand the various definitions of an integrated CPS, as well as the growth of new research areas in this field. The application of CPSs faces a number of difficulties, including those related to efficiency, reliability, controllability, and security. We are moving forward in technological innovation with the development of CPSs and the Internet of Things (IoT). It is possible for engineers to gain a better understanding of engineering systems and management modules by utilizing the CPS-IoT models.


Cyber-Physical Systems (CPS), Internet of Things (IoT), Computing, Communication, and Control (3Cs).

  1. D. Johnson, "Space-time stochastic processes", Stochastic Processes and their Applications, vol. 26, pp. 203-204, 1987. Doi: 10.1016/0304-4149(87)90108-6.
  2. K. Ding, S. Dey, D. Quevedo and L. Shi, "Stochastic Game in Remote Estimation Under DoS Attacks", IEEE Control Systems Letters, vol. 1, no. 1, pp. 146-151, 2017. Doi: 10.1109/lcsys.2017.2711044.
  3. T. Wu, C. Huang and H. Chao, "A survey of Mobile IP in cellular and Mobile Ad-Hoc Network environments", Ad Hoc Networks, vol. 3, no. 3, pp. 351-370, 2005. Doi: 10.1016/j.adhoc.2003.09.011.
  4. R. hanfi , and Y. rai, "Wireless Sensor Network", International Journal Of Engineering And Computer Science, 2016. Doi: 10.18535/ijecs/v5i1.16.
  5. M. Megat Mohamed Noor, "Cell-based intrusion detection using wireless mesh network", International Journal of Academic Research, vol. 5, no. 5, pp. 94-99, 2013. Doi: 10.7813/2075-4124.2013/5-5/a.12.
  6. "IEEE Journal of Radio Frequency Identification Publication Information", IEEE Journal of Radio Frequency Identification, vol. 6, pp. C2-C2, 2022. Doi: 10.1109/jrfid.2021.3136834.
  7. S. Yadav, "A resilient hierarchical distributed model of a cyber physical system", Cyber-Physical Systems, pp. 1-24, 2021. Doi: 10.1080/23335777.2021.1964101.
  8. T. Owens, "The Human Component", International Journal of Forensic Sciences, vol. 6, no. 1, 2021. Doi: 10.23880/ijfsc-16000216.
  9. A. Umunnakwe, A. Sahu, M. Narimani, K. Davis and S. Zonouz, "Cyber‐physical component ranking for risk sensitivity analysis using betweenness centrality", IET Cyber-Physical Systems: Theory & Applications, vol. 6, no. 3, pp. 139-150, 2021. Doi: 10.1049/cps2.12010.
  10. J. Criado, J. Asensio, N. Padilla and L. Iribarne, "Integrating Cyber-Physical Systems in a Component-Based Approach for Smart Homes", Sensors, vol. 18, no. 7, p. 2156, 2018. Doi: 10.3390/s18072156.
  11. "Call for Papers for Special Issue on Evaluation and Improvement of Software Dependability", IEEE Transactions on Software Engineering, vol. 34, no. 1, pp. 157-157, 2008. Doi: 10.1109/tse.2008.3.
  12. W. Kang and J. Chung, "DeepRT: predictable deep learning inference for cyber-physical systems", Real-Time Systems, vol. 55, no. 1, pp. 106-135, 2018. Doi: 10.1007/s11241-018-9314-y.
  13. Y. Song, F. Mao and Q. Liu, "Human Comfort in Indoor Environment: A Review on Assessment Criteria, Data Collection and Data Analysis Methods", IEEE Access, vol. 7, pp. 119774-119786, 2019. Doi: 10.1109/access.2019.2937320.
  14. P. Lo Giudice, A. Nocera, D. Ursino and L. Virgili, "Building Topic-Driven Virtual IoTs in a Multiple IoTs Scenario", Sensors, vol. 19, no. 13, p. 2956, 2019. Doi: 10.3390/s19132956.
  15. A. Martin, "Evidence Map of Cost-Benefit, Cost-Effectiveness and Cost-Utility Models In Dementia Published Since 1960", Value in Health, vol. 20, no. 9, pp. A724-A725, 2017. Doi: 10.1016/j.jval.2017.08.1955.


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Burova Margarita, “An Evaluation of Internet of Things and Cyber-Physical System Integration", vol.2, no.4, pp. 143-152, October 2022. doi: 10.53759/181X/JCNS202202017.


© 2022 Burova Margarita. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.