Journal of Computing and Natural Science


Definition, Challenges and Future Research for Internet of Things



Journal of Computing and Natural Science

Received On : 10 December 2022

Revised On : 02 March 2023

Accepted On : 06 June 2023

Published On : 05 October 2023

Volume 03, Issue 04

Pages : 216-226


Abstract


This article aims to provide a review of Internet of Things (IoT), analyzing its significant challenges within the framework of existing research on the topic. The IoT is a contemporary technology that encompasses wireless telecommunication networks. It can be conceptualized as a smart and interoperable node integrated within a vibrant global architectural system, with the objective of achieving ubiquitous and uninterrupted connectivity. The IoT landscape encompasses various challenges that significantly impact its operational efficacy. The challenges can be categorized into two main groups: i) General challenges integrating heterogeneity, security, virtualization, and communication; and ii) Unique challenges including Quality of Service (QoS), wireless sensor network (WSN), and Radio Frequency Identification (RFID), which is considered a shared factor between both groups. The report additionally outlines the primary applications of the IoT.


Keywords


Internet of Things, Ubiquitous Computing, Wireless Sensor Networks, Radio Frequency Identification, Quality of Service.


  1. O. Eris, J. L. Drury, and D. Ercolini, “A collaboration-centric taxonomy of the internet of things: Implications for awareness support,” Internet of Things, vol. 15, no. 100403, p. 100403, 2021.
  2. K. Ashok, M. Ashraf, J. Thimmia Raja, M. Z. Hussain, D. K. Singh, and A. Haldorai, “Collaborative analysis of audio-visual speech synthesis with sensor measurements for regulating human–robot interaction,” International Journal of System Assurance Engineering and Management, Aug. 2022, doi: 10.1007/s13198-022-01709-y.
  3. L. Zhao, P. Pop, and S. Steinhorst, “Quantitative performance comparison of various traffic shapers in time-sensitive networking,” IEEE Trans. Netw. Serv. Manag., vol. 19, no. 3, pp. 2899–2928, 2022.
  4. S. Misra, A. Gupta, P. V. Krishna, H. Agarwal, and M. S. Obaidat, “An adaptive learning approach for fault-tolerant routing in Internet of Things,” in 2012 IEEE Wireless Communications and Networking Conference (WCNC), 2012.
  5. Neha, P. Gupta, and M. A. Alam, “Challenges in the adaptation of IoT technology,” in A Fusion of Artificial Intelligence and Internet of Things for Emerging Cyber Systems, Cham: Springer International Publishing, 2022, pp. 347–369.
  6. S. Panja, A. K. Chattopadhyay, and A. Nag, “A review of risks and threats on IoT layers,” in Lecture Notes on Data Engineering and Communications Technologies, Singapore: Springer Singapore, 2021, pp. 735–747.
  7. B. Emruli, F. Sandin, and J. Delsing, “Vector space architecture for emergent interoperability of systems by learning from demonstration,” Biol. Inspired Cogn. Arch., vol. 11, pp. 53–64, 2015.
  8. H and A. R, “Artificial Intelligence and Machine Learning for Enterprise Management,” 2019 International Conference on Smart Systems and Inventive Technology (ICSSIT), Nov. 2019, doi: 10.1109/icssit46314.2019.8987964.
  9. Y. Masoudi-Sobhanzadeh, H. Motieghader, Y. Omidi, and A. Masoudi-Nejad, “A machine learning method based on the genetic and world competitive contests algorithms for selecting genes or features in biological applications,” Sci. Rep., vol. 11, no. 1, p. 3349, 2021.
  10. L. Bittencourt et al., “The Internet of Things, Fog and Cloud continuum: Integration and challenges,” Internet of Things, vol. 3–4, pp. 134–155, 2018.
  11. M. Alarbi and H. Lutfiyya, “Sensing as a Service Middleware Architecture,” in 2018 IEEE 6th International Conference on Future Internet of Things and Cloud (FiCloud), 2018.
  12. V. Joevivek et al., “Spatial and temporal correlation between beach and wave processes: implications for bar–berm sediment transition,” Frontiers of Earth Science, vol. 12, no. 2, pp. 349–360, Jun. 2017, doi: 10.1007/s11707-017-0655-y.
  13. K. A. Fararni, F. Nafis, B. Aghoutane, A. Yahyaouy, J. Riffi, and A. Sabri, “Hybrid recommender system for tourism based on big data and AI: A conceptual framework,” Big Data Min. Anal., vol. 4, no. 1, pp. 47–55, 2021.
  14. Haldorai, A. Ramu, and S. Murugan, “Computing and Communication Systems in Urban Development,” Urban Computing, 2019, doi: 10.1007/978-3-030-26013-2.
  15. J. Gomez-gualdron and M. Velez-Reyes, “Simulating a multi-agent based self-reconfigurable electric power distribution system,” in 2006 IEEE Workshops on Computers in Power Electronics, 2006.
  16. Haldorai and U. Kandaswamy, “Energy Efficient Network Selection for Cognitive Spectrum Handovers,” EAI/Springer Innovations in Communication and Computing, pp. 41–64, 2019, doi: 10.1007/978-3-030-15416-5_3.
  17. B. R. Ray, J. Abawajy, and M. Chowdhury, “Scalable RFID security framework and protocol supporting Internet of Things,” Comput. Netw., vol. 67, pp. 89–103, 2014.
  18. J. Bzai et al., “Machine learning-enabled Internet of Things (IoT): Data, applications, and industry perspective,” Electronics (Basel), vol. 11, no. 17, p. 2676, 2022.
  19. Y. Wang, H. Shibamura, K. Ng, and K. Inoue, “Implementation of edge-cloud cooperative CNN inference on an IoT platform,” in 2022 IEEE 15th International Symposium on Embedded Multicore/Many-core Systems-on-Chip (MCSoC), 2022.
  20. S. Pasricha and A. Veidenbaum, “Improving branch prediction accuracy in embedded processors in the presence of context switches,” in Proceedings 21st International Conference on Computer Design, 2004.
  21. H. Li, M. Jia, and Z. Mao, “Dynamic reconstruction principal component analysis for process monitoring and fault detection in the cold rolling industry,” J. Process Control, vol. 128, no. 103010, p. 103010, 2023.

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Authors thanks to Department of Modern Mechanics for this research support


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Cite this article


Li Hua Fang and Dong Yonggui, “Definition, Challenges and Future Research for Internet of Things”, Journal of Computing and Natural Science, vol.3, no.4, pp. 216-226, October 2023. doi: 10.53759//181X/JCNS/202303020.


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© 2023 Li Hua Fang and Dong Yonggui. 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.