IoT in Industry 4.0: Applications and challenges

  • Dua Noor
  • Abdul Basit
  • Sagheer Mirani
Keywords: IoT, IIoT, Sensors, Data acquisition and Security

Abstract

The Internet of Things (IoT) enabled devices involve different types of data. These devices named as sensors are responsible for generating real world data based on the physical properties they measure. For example, temperature sensor produced temperature readings. Sensor collects data continuously or periodically, providing a stream of information that reflects changes in environment or conditions. Relating to the IoT, data from sensors transmitted to the central system usually through wireless communication protocols. The collected data can be utilized for various purposes such as monitoring, analysis and decision making or triggering actions. This study provides a review of IoT and industrial IoT (IIoT). Further, this paper highlights Applications, challenges and tools in detail.

References

[1] H. Hua, Y. Li, T. Wang, N. Dong, W. Li, and J. Cao, “Edge Computing with Artificial Intelligence: A Machine Learning Perspective,” ACM Comput. Surv., vol. 55, no. 9, 2023, doi: 10.1145/3555802.
[2] L. A. Haibeh, M. C. E. Yagoub, and A. Jarray, “A Survey on Mobile Edge Computing Infrastructure: Design, Resource Management, and Optimization Approaches,” IEEE Access, vol. 10, pp. 27591–27610, 2022, doi: 10.1109/ACCESS.2022.3152787.
[3] R. Singh, A. Gehlot, S. Vaseem Akram, A. Kumar Thakur, D. Buddhi, and P. Kumar Das, “Forest 4.0: Digitalization of forest using the Internet of Things (IoT),” J. King Saud Univ. - Comput. Inf. Sci., vol. 34, no. 8, pp. 5587–5601, 2022, doi: 10.1016/j.jksuci.2021.02.009.
[4] R. Shukla et al., “Detecting crop health using machine learning techniques in smart agriculture system,” J. Sci. Ind. Res. (India)., vol. 80, no. 8, pp. 699–706, 2021.
[5] A. Goap, D. Sharma, A. K. Shukla, and C. Rama Krishna, “An IoT based smart irrigation management system using Machine learning and open source technologies,” Comput. Electron. Agric., vol. 155, no. September, pp. 41–49, 2018, doi: 10.1016/j.compag.2018.09.040.
[6] J. Wan et al., “Software-Defined Industrial Internet of Things in the Context of Industry 4 . 0,” vol. 16, no. 20, pp. 7373–7380, 2016.
[7] O. A. Alzubi, J. A. Alzubi, M. Alazab, A. Alrabea, A. Awajan, and I. Qiqieh, “Optimized Machine Learning-Based Intrusion Detection System for Fog and Edge Computing Environment,” Electron., vol. 11, no. 19, pp. 1–16, 2022, doi: 10.3390/electronics11193007.
[8] J. Xu, B. Gu, and G. Tian, “Review of agricultural IoT technology,” Artif. Intell. Agric., vol. 6, pp. 10–22, 2022, doi: 10.1016/j.aiia.2022.01.001.
[9] M. Haghi Kashani, M. Madanipour, M. Nikravan, P. Asghari, and E. Mahdipour, “A systematic review of IoT in healthcare: Applications, techniques, and trends,” J. Netw. Comput. Appl., vol. 192, no. May, p. 103164, 2021, doi: 10.1016/j.jnca.2021.103164.
[10] A. Ahamad, C. C. Sun, and W. K. Kuo, “Quantized Semantic Segmentation Deep Architecture for Deployment on an Edge Computing Device for Image Segmentation,” Electron., vol. 11, no. 21, 2022, doi: 10.3390/electronics11213561.
[11] M. Hartmann, U. S. Hashmi, and A. Imran, “Edge computing in smart health care systems: Review, challenges, and research directions,” Trans. Emerg. Telecommun. Technol., vol. 33, no. 3, pp. 1–25, 2022, doi: 10.1002/ett.3710.
[12] X. Hou, Z. Ren, J. Wang, S. Zheng, W. Cheng, and H. Zhang, “Distributed Fog Computing for Latency and Reliability Guaranteed Swarm of Drones,” IEEE Access, vol. 8, pp. 7117–7130, 2020, doi: 10.1109/ACCESS.2020.2964073.
[13] M. M. Kamruzzaman, B. Yan, M. N. I. Sarker, O. Alruwaili, M. Wu, and I. Alrashdi, “Blockchain and Fog Computing in IoT-Driven Healthcare Services for Smart Cities,” J. Healthc. Eng., vol. 2022, 2022, doi: 10.1155/2022/9957888.
[14] M. Maray and J. Shuja, “Computation Offloading in Mobile Cloud Computing and Mobile Edge Computing: Survey, Taxonomy, and Open Issues,” Mob. Inf. Syst., vol. 2022, 2022, doi: 10.1155/2022/1121822.
[15] R. Das and M. M. Inuwa, “A review on fog computing: Issues, characteristics, challenges, and potential applications,” Telemat. Informatics Reports, vol. 10, no. July 2022, 2023, doi: 10.1016/j.teler.2023.100049.
[16] R. Akhter and S. A. Sofi, “Precision agriculture using IoT data analytics and machine learning,” J. King Saud Univ. - Comput. Inf. Sci., vol. 34, no. 8, pp. 5602–5618, 2022, doi: 10.1016/j.jksuci.2021.05.013.
[17] H. Hua, Y. Li, T. Wang, N. Dong, W. Li, and J. Cao, “Edge Computing with Artificial Intelligence: A Machine Learning Perspective,” ACM Comput. Surv., vol. 55, no. 9, 2023, doi: 10.1145/3555802.
[18] L. A. Haibeh, M. C. E. Yagoub, and A. Jarray, “A Survey on Mobile Edge Computing Infrastructure: Design, Resource Management, and Optimization Approaches,” IEEE Access, vol. 10, pp. 27591–27610, 2022, doi: 10.1109/ACCESS.2022.3152787.
[19] R. Singh, A. Gehlot, S. Vaseem Akram, A. Kumar Thakur, D. Buddhi, and P. Kumar Das, “Forest 4.0: Digitalization of forest using the Internet of Things (IoT),” J. King Saud Univ. - Comput. Inf. Sci., vol. 34, no. 8, pp. 5587–5601, 2022, doi: 10.1016/j.jksuci.2021.02.009.
[20] R. Shukla et al., “Detecting crop health using machine learning techniques in smart agriculture system,” J. Sci. Ind. Res. (India)., vol. 80, no. 8, pp. 699–706, 2021.
[21] S. Salvi et al., “Cloud based data analysis and monitoring of smart multi-level irrigation system using IoT,” Proceedings of the International Conference on IoT in Social, Mobile, Analytics and Cloud, I-SMAC 2017. pp. 752–757, 2017. doi: 10.1109/I-SMAC.2017.8058279.
[22] K. Cao, Y. Liu, G. Meng, and Q. Sun, “An Overview on Edge Computing Research,” IEEE Access, vol. 8, pp. 85714–85728, 2020, doi: 10.1109/ACCESS.2020.2991734.
[23] M. H. Guo et al., “Attention mechanisms in computer vision: A survey,” Comput. Vis. Media, vol. 8, no. 3, pp. 331–368, 2022, doi: 10.1007/s41095-022-0271-y.
[24] S. Hamdan, M. Ayyash, and S. Almajali, “Edge-computing architectures for internet of things applications: A survey,” Sensors (Switzerland), vol. 20, no. 22, pp. 1–52, 2020, doi: 10.3390/s20226441.
[25] S. S. Esfahlani, H. Shirvani, J. Butt, I. Mirzaee, and K. S. Esfahlani, “Machine Learning role in clinical decision-making: Neuro-rehabilitation video game,” Expert Syst. Appl., vol. 201, no. June 2021, p. 117165, 2022, doi: 10.1016/j.eswa.2022.117165.
[26] T. Edition, “Book Review Python Machine Learning : Machine Learning and Deep Learning With Python ,” vol. 11, no. 1, pp. 67–70, 2021.
[27] L. Fischer et al., “AI System Engineering — Key Challenges and Lessons Learned †,” pp. 56–83, 2021.
[28] B. I. Akhigbe, K. Munir, O. Akinade, L. Akanbi, and L. O. Oyedele, “IoT Technologies for Livestock Management : A Review of Present Status , Opportunities , and Future Trends,” 2021.
[29] R. Majeed, N. A. Abdullah, I. Ashraf, Y. Bin Zikria, M. F. Mushtaq, and M. Umer, “An Intelligent , Secure , and Smart Home Automation System,” vol. 2020, 2020.
[30] J. Fan, Y. Zhang, W. Wen, S. Gu, X. Lu, and X. Guo, “The future of Internet of Things in agriculture: Plant high-throughput phenotypic platform,” J. Clean. Prod., vol. 280, p. 123651, 2021, doi: 10.1016/j.jclepro.2020.123651.
[31] A. Diez-Olivan, J. Del Ser, D. Galar, and B. Sierra, “Data fusion and machine learning for industrial prognosis: Trends and perspectives towards Industry 4.0,” Inf. Fusion, vol. 50, pp. 92–111, 2019, doi: 10.1016/j.inffus.2018.10.005.
[32] J. Woetzel et al., “Smart Cities: Digital Solutions for a More Livable Future,” McKinsey Co., 2018.
[33] M. Alkhatib, M. El Barachi, and K. Shaalan, “An Arabic social media based framework for incidents and events monitoring in smart cities,” J. Clean. Prod., vol. 220, pp. 771–785, 2019, doi: 10.1016/j.jclepro.2019.02.063.
[34] M. Ammar, G. Russello, and B. Crispo, “Journal of Information Security and Applications Internet of Things : A survey on the security of IoT frameworks,” J. Inf. Secur. Appl., vol. 38, pp. 8–27, 2018, doi: 10.1016/j.jisa.2017.11.002.
[35] N. Rajabli, F. Flammini, R. Nardone, and V. Vittorini, “Software Verification and Validation of Safe Autonomous Cars: A Systematic Literature Review,” IEEE Access, pp. 4797–4819, 2020, doi: 10.1109/ACCESS.2020.3048047.
[36] A. Cyril Jose and R. Malekian, “Smart Home Automation Security: A Literature Review,” Smart Comput. Rev., vol. 5, no. 4, pp. 269–285, 2015, doi: 10.6029/smartcr.2015.04.004.
[37] V. Bhatt and S. Chakraborty, “Improving service engagement in healthcare through internet of things based healthcare systems,” J. Sci. Technol. Policy Manag., vol. 14, no. 1, pp. 53–73, 2023, doi: 10.1108/JSTPM-03-2021-0040.
[38] L. Liu, C. Chen, Q. Pei, S. Maharjan, and Y. Zhang, “Vehicular Edge Computing and Networking: A Survey,” Mob. Networks Appl., vol. 26, no. 3, pp. 1145–1168, 2021, doi: 10.1007/s11036-020-01624-1.
[39] W. Peng and O. Karimi Sadaghiani, “A review on the applications of machine learning and deep learning in agriculture section for the production of crop biomass raw materials,” Energy Sources, Part A Recover. Util. Environ. Eff., vol. 45, no. 3, pp. 9178–9201, 2023, doi: 10.1080/15567036.2023.2232322.
[40] N. Tariq, A. Qamar, M. Asim, and F. A. Khan, “Blockchain and smart healthcare security: A survey,” Procedia Comput. Sci., vol. 175, no. 2019, pp. 615–620, 2020, doi: 10.1016/j.procs.2020.07.089.
[41] C. Zeng, F. Zhang, and M. Luo, “A deep neural network-based decision support system for intelligent geospatial data analysis in intelligent agriculture system,” Soft Comput., vol. 26, no. 20, pp. 10813–10826, 2022, doi: 10.1007/s00500-022-07018-7.
[42] H. Sabireen and V. Neelanarayanan, “A Review on Fog Computing: Architecture, Fog with IoT, Algorithms and Research Challenges,” ICT Express, vol. 7, no. 2, pp. 162–176, 2021, doi: 10.1016/j.icte.2021.05.004.
[43] D. Rajapaksha, C. Tantithamthavorn, J. Jiarpakdee, C. Bergmeir, J. Grundy, and W. Buntine, “SQAPlanner: Generating Data-Informed Software Quality Improvement Plans,” IEEE Trans. Softw. Eng., vol. 5589, no. c, pp. 1–24, 2021, doi: 10.1109/TSE.2021.3070559.
Published
2024-04-26
How to Cite
Noor, D., Basit, A., & Mirani, S. (2024). IoT in Industry 4.0: Applications and challenges. International Journal of Computing and Related Technologies, 4(2), 24-35. Retrieved from http://ijcrt.smiu.edu.pk/ijcrt/index.php/smiu/article/view/190