Open Access
Issue
ITM Web Conf.
Volume 46, 2022
International Conference on Engineering and Applied Sciences (ICEAS’22)
Article Number 03002
Number of page(s) 5
Section Artificial Intelligence in Supply Chain Management
DOI https://doi.org/10.1051/itmconf/20224603002
Published online 06 June 2022
  1. V. P. Vemuri, Priya, V. Ramesh Naik, V. Chaudhary, K. RameshBabu, M. Mengstie, Analyzing the use of internet of things (IoT) in artificial intelligence and its impact on business environment, Mat. Today. Proceedings. 51, 2194-2197, (2022). [Google Scholar]
  2. A. Ghosh, D. Chakraborty, A. Law, S. Nepal, Q. Z. Sheng, Artificial Intelligence in Internet of Things, CCAI. Transactions. Intelligence. Tech, (2018). [Google Scholar]
  3. A. H. Ngu, M. Gutierrez, V. Metsis, S. Nepal, Q. Z. Sheng, IoT middleware: A Survey on issues and enabling technologies, Inter. Conf. System. Reliability. Sci, 207-212, (2017). [Google Scholar]
  4. B. Safaei, A. M. H. Monazzah, M. B. Bafroei, A. Ejlali, Reliability Side-Effects in Internet of Things Application Layer Protocols, IEEE. Internet. Things. J. 7, 4543-4556, (2020). [CrossRef] [Google Scholar]
  5. Business Insider: THE INTERNET OF THINGS 2020, https://www.businessinsider.com/internet-of-things-report,last accessed2021/10/07. [Google Scholar]
  6. W. Rafique, X. Zhao, S. Yu, I. Yaqoob, M. Imran, W. Dou, An Application Development Framework for Internet-of-Things Service Orchestration, IEEE. Internet. Things. J. 7, 4543-4556, (2020). [CrossRef] [Google Scholar]
  7. Siemens press: Digitalized Manufacturing game- changer for Middle East industry 2017, https://press.siemens.com/middleeast/en/pressrelease/siemens-digitalized-manufacturing-game-changer-middle-east-industry [Google Scholar]
  8. R. Revalty, M.G. Raj, M. Selvi, J.K. Periasamy, Analysis of Artificial Intelligence of Things, Inter. J. Elect. Eng. Tech. 11, 275-280, (2021). [Google Scholar]
  9. Gartner Contributor, Chris Pemberton, Impact business outcomes with a focus on application integration and IoT, https://www.gartner.com/smarterwithgartner/3-ai-trends-for-enterprise-computing [Google Scholar]
  10. A. Ometov, V. Shubina, L. Klus, J. Skibińska, S. Saafi, P. Pascacio, L Flueratoru, D Q Gaibor, N Chukhno, O. Chukhno, Asad Ali, A. Channa, E. Svertoka, W. Bin Qaim, R. Casanova-Marqués, S. Holcer, J. Torres-Sospedra, S. Casteleyn, G. Ruggeri, G. Araniti, R. Burget, J. Hosek, E. S. Lohan, A Survey on Wearable Technology: History, State-of-the-Art and Current Challenges, Computer Science, 193, (2021) [Google Scholar]
  11. K. Christidis, M. Devetsiokiotis, IEEE Access 4, 2292–2303, (2016). [Google Scholar]
  12. D. Wu, J.L. Thames, D.W. Rosen, D. Schaefer, Enhancing the product realization process with cloud-based design and manufacturing systems, J. Comput.Inform. Sci. Eng. 13, 1–14, (2013). [Google Scholar]
  13. Y. Sompolinsky, A. Zohar, Accelerating Bitcoin’s Transaction Processing Fast Money Grows on Trees, Not Chains, 2013. [Google Scholar]
  14. N. Sharma, R. Sharma, N. Jindal, Machine Learning and Deep Learning Applications A- Vision, Global. Trans. Proceedings. 2, 24-28, (2021). [CrossRef] [Google Scholar]
  15. M. Merenda, C. Porcaco, D. Iero, Edge Machine Learning for AI-Enabled IoT Devices, Sensors. 20, 24-28, (2020). [Google Scholar]
  16. F. Farshad, F. Bahar, M. Alexander, The convergence and interplay of edge, fog, and cloud in the AI-driven Internet of Things (IoT), Inter. R. J. Eng. Tech. 107, (2022). [Google Scholar]
  17. Medium web article: M.Shams, Impact of Artificial Intelligence (AI) on industries 2020, https://medium.com/@muntahashams288/impact-of-artificial-intelligence-on-industries-6b0ff82063b6. [Google Scholar]
  18. H. Espinoza, G. Kling, F. McGroarty, X. Ziouvelou, Estimating the impact of the Internet of Things on productivity in Europe, Heliyon. 6, (2020). [Google Scholar]
  19. S. Pal, P.M. Chawan, Real-time object Detection using Deep Learning: A Survey, Inter. R. J. Eng. Tech. 6, 397-399, (2019). [Google Scholar]
  20. L. Szu-Yin, L. Hao-Yu, Integrated Circuit Board Object Detection and Image Augmentation Fusion Model Based on Yolo, Frontiers in Neurobotics. 15, (2021). [Google Scholar]
  21. J. Seojin, L. Wei, P. Sangun, C. Yongbeom, Automatic RTL Generation Tool of FPGAs for DNNs, Electronics. 11, 402, (2022). [Google Scholar]
  22. E. Meltem, M. Ana, B. Joao, P. I. Miguel, C. Antonio, A Systematic Review of Artificial Intelligence Applications Used for Inherited Retinal Disease Management, 58, (2022) [Google Scholar]

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