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References
Оглавление1. Gilchrist, A., Industry 4.0: the industrial internet of things, Springer Nature Switzerland AG., 2016, https://link.springer.com/book/10.1007%2F978-1-4842-2047-4
2. Vaidya, S., Ambad, P., Bhosle, S., Industry 4.0–a glimpse. Procedia Manuf., 20, 233–238, 2018.
3. Rojko, A., Industry 4.0 concept: background and overview. Int. J. Interact. Mob. Technol. (iJIM), 11, 5, 77–90, 2017.
4. Xu, L.D., Xu, E.L., Li, L., Industry 4.0: state of the art and future trends. Int. J. Prod. Res., 56, 8, 2941–2962, 2018.
5. Ardito, L. et al., Towards Industry 4.0. Bus. Process Manag. J., 2019.
6. Sanders, A., Elangeswaran, C., Wulfsberg, J.P., Industry 4.0 implies lean manufacturing: Research activities in industry 4.0 function as enablers for lean manufacturing. J. Ind. Eng. Manag. (JIEM), 9, 3, 811–833, 2016.
7. Gunal, M.M. (Ed.), Simulation for Industry 4.0: Past, Present, and Future, Springer Nature Switzerland AG., 2019, https://link.springer.com/chapter/10.1007/978-3-030-04137-3_16
8. Jaidka, H., Sharma, N., Singh, R., Evolution of IoT to IIoT: Applications and challenges. Proceedings of the International Conference on Innovative Computing & Communications (ICICC). 2020, https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3603739
9. Yu, X. and Guo, H., A Survey on IIoT Security. 2019 IEEE VTS Asia Pacific Wireless Communications Symposium (APWCS), IEEE, 2019.
10. Mathur, P., Overview of IoT and IIoT, in: IoT Machine Learning Applications in Telecom, Energy, and Agriculture, pp. 19–43, Apress, Berkeley, CA, 2020.
11. Leminen, S. et al., Industrial internet of things business models in the machine-to-machine context. Ind. Mark. Manag., 84, 298–311, 2020.
12. França, R.P. et al., Improvement of the Transmission of Information for ICT Techniques Through CBEDE Methodology, in: Utilizing Educational Data Mining Techniques for Improved Learning: Emerging Research and Opportunities, pp. 13–34, IGI Global, Pennsylvania, USA, 2020.
13. Franca, R.P. et al., Better Transmission of Information Focused on Green Computing Through Data Transmission Channels in Cloud Environments with Rayleigh Fading, in: Green Computing in Smart Cities: Simulation and Techniques, pp. 71–93, Springer, Cham, 2021.
14. Al-Gumaei, K. et al., A survey of internet of things and big data integrated solutions for industries 4.0. 2018 IEEE 23rd International Conference on Emerging Technologies and Factory Automation (ETFA), vol. 1, IEEE, 2018.
15. Monteiro, A.C.B. et al., Development of a laboratory medical algorithm for simultaneous detection and counting of erythrocytes and leukocytes in digital images of a blood smear, in: Deep Learning Techniques for Biomedical and Health Informatics, pp. 165–186, Academic Press, Cambridge, Massachusetts, EUA, 2020.
16. França, R.P. et al., Potential proposal to improve data transmission in healthcare systems, in: Deep Learning Techniques for Biomedical and Health Informatics, pp. 267–283, Academic Press, Cambridge, Massachusetts, EUA, 2020.
17. Al-Turjman, F. (Ed.), Artificial Intelligence in IoT, Springer Nature Switzerland AG., 2019, https://link.springer.com/book/10.1007%2F978-3-030-04110-6
18. Hosseinian-Far, A., Ramachandran, M., Slack, C.L., Emerging trends in cloud computing, big data, fog computing, IoT and smart living, in: Technology for Smart Futures, pp. 29–40, Springer, Cham, 2018.
19. França, R.P. et al., A Proposal Based on Discrete Events for Improvement of the Transmission Channels in Cloud Environments and Big Data, in: Big Data, IoT, and Machine Learning: Tools and Applications, p. 185, 2020.
20. Cielen, D., Meysman, A., Ali, M., Introducing data science: big data, machine learning, and more, using Python tools, 320 pp., Manning Publications Co., New York, USA, May 2016. ISBN 9781633430037, https://www.manning.com/books/introducing-data-science
21. Sangaiah, A.K., Thangavelu, A., Meenakshi Sundaram, V., Cognitive computing for Big Data systems over IoT. Gewerbestrasse, 11, 6330, Springer, 2018.
22. Deng, L. and Liu, Y. (Eds.), Deep learning in natural language processing, Springer Nature Switzerland AG., 2018.
23. Jackson, P.C., Introduction to artificial intelligence, Courier Dover Publications, Mineola, New York, USA, 2019.
24. Flasiński, M., Introduction to artificial intelligence, Springer Nature Switzerland AG., 2016.
25. Arrieta, A.B. et al., Explainable Artificial Intelligence (XAI): Concepts, taxonomies, opportunities and challenges toward responsible AI. Inf. Fusion, 58, 82–115, 2020.
26. Semmler, S. and Rose, Z., Artificial intelligence: Application today and implications tomorrow. Duke L. Tech. Rev., 16, 85, 2017.
27. Ardito, L., et al., Towards Industry 4.0: Mapping digital technologies for supply chain management-marketing integration. Bus. Process Manag. J., 2019, https://www.emerald.com/insight/content/doi/10.1108/BPMJ-04-2017-0088/full/html?journalCode=bpmj
28. Raj, M. and Seamans, R., Primer on artificial intelligence and robotics. J. Organ. Des., 8, 1, 1–14, 2019.
29. Zhu, L. and Jim Zheng, W., Informatics, data science, and artificial intelligence. Jama, 320, 11, 1103–1104, 2018.
30. Carlos, R.C., Kahn, C.E., Halabi, S., Data science: big data, machine learning, and artificial intelligence. J. Am. Coll. Radiol., 15, 3, 497–498, 2018.
31. Acemoglu, D. and Restrepo, P., Artificial intelligence, automation and work, National Bureau of Economic Research, Cambridge, MA, 2018.
32. Nadimpalli, M., Artificial intelligence risks and benefits. Int. J. Innov. Res. Sci. Eng. Technol., 6, 6, 2017.
33. Sola, D., Borioli, G.S., Quaglia, R., Predicting GPs’ engagement with artificial intelligence. Br. J. Health Care Manag., 24, 3, 134–140, 2018.
34. Delamater, N., A brief history of artificial intelligence and how it’s revolutionizing customer service today, SmartMax Software, Inc, Tulsa, OK, 2018. https://images.g2crowd.com/uploads/attachment/file/73099/expirable-direct-uploads_2F469f2619-a917-446d-b2b8-14cf8f8d2c4e_2FChatBotWhitePaper2017.pdf
35. Olson, N., The Internet of things. New Media Soc., 18, 4, 680–682, 2016, https://journals.sagepub.com/doi/abs/10.1177/1461444815621893a?journalCode=nmsa
36. França, R.P. et al., Improvement of the Transmission of Information for ICT Techniques Through CBEDE Methodology, in: Utilizing Educational Data Mining Techniques for Improved Learning: Emerging Research and Opportunities, pp. 13–34, IGI Global, Pennsylvania, USA, 2020.
37. Osuwa, A.A., Ekhoragbon, E.B., Fat, L.T., Application of artificial intelligence in Internet of Things. 2017 9th International Conference on Computational Intelligence and Communication Networks (CICN), IEEE, 2017.
38. Zeng, Xuezhi et al., IOTSim: A simulator for analysing IoT applications. J. Syst. Archit., 72, 93–107, 2017.
39. França, R.P. et al., Intelligent Applications of WSN in the World: A Technological and Literary Background, in: Handbook of Wireless Sensor Networks: Issues and Challenges in Current Scenario’s, pp. 13–34, Springer, Cham, 2020.
40. Erl, T., Khattak, W., Buhler, P., Big data fundamentals: concepts, drivers & techniques, Prentice-Hall Press, Hoboken, Nova Jersey, EUA, 2016.
41. Balali, F. et al., Internet of Things (IoT): Principles and Framework, in: Data-Intensive Industrial Asset Management, pp. 1–19, Springer, Cham, 2020.
42. Lakhwani, K. et al., Internet of Things (IoT): Principles, Paradigms and Applications of IoT, BPB Publications, New Delhi, India, 2020.
43. Tran, C. and Misra, S., The Technical Foundations of IoT. IEEE Wirel. Commun., 26, 3, 8–8, 2019.
44. Shovic, J.C., Introduction to IoT, in: Raspberry Pi IoT Projects, pp. 1–8, Apress, Berkeley, CA, 2016.
45. Peng, S.-L., Pal, S., Huang, L., Principles of Internet of Things (IoT) Ecosystem: Insight Paradigm, Springer Nature Switzerland AG., 2020.
46. Bröring, A. et al., NOVA: A Knowledge Base for the Node-RED IoT Ecosystem. European Semantic Web Conference, Springer, Cham, 2019.
47. Okano, M.T., IOT and industry 4.0: the industrial new revolution. International Conference on Management and Information Systems, vol. 25, 2017.
48. Kanagachidambaresan, G.R. et al., Internet of Things for Industry 4.0, Springer International Publishing, 2020.
49. Boyes, H. et al., The industrial internet of things (IIoT): An analysis framework. Comput. Ind., 101, 1–12, 2018.
50. Reddy, B.R. and Sujith, A.V.L.N., A comprehensive literature review on data analytics in IIoT (Industrial Internet of Things). HELIX, 8, 1, 2757–2764, 2018.
51. Jacob, J.J. and Thamba W., Meshach, Industrial Internet of Things (IIoT)– An IoT Integrated Services for Industry 4.0: A Review. Int. J. Appl. Sci. Eng., 8, 1, 37–42, 2020.
52. Mathur, P., Overview of IoT and IIoT, in: IoT Machine Learning Applications in Telecom, Energy, and Agriculture, pp. 19–43, Apress, Berkeley, CA, 2020.
53. Kim, D.-S. and Tran-Dang, H., An Overview on Industrial Internet of Things, in: Industrial Sensors and Controls in Communication Networks, pp. 207–216, Springer, Cham, 2019.
54. Nicolae, A., Korodi, A., Silea, I., An Overview of Industry 4.0 Development Directions in the Industrial Internet of Things Context. Rom. J. Inf. Sci. Tech., 22, 183–201, 2019.
55. Sternberg, R.J., A theory of adaptive intelligence and its relation to general intelligence. J. Intell., 7, 4, 23, 2019.
56. El Saddik, A., Digital twins: The convergence of multimedia technologies. IEEE Multimed., 25, 2, 87–92, 2018.
57. Müller, V.C. and Bostrom, N., Future progress in artificial intelligence: A survey of expert opinion, in: Fundamental issues of artificial intelligence, pp. 555–572, Springer, Cham, 2016.
58. Patel, P., Ali, M.I., Sheth, A., On using the intelligent edge for IoT analytics. IEEE Intelligent Syst., 32, 5, 64–69, 2017.
59. Mobley, R.K., An introduction to predictive maintenance, Elsevier, Amsterdam, Netherlands, 2002.
60. Selcuk, S., Predictive maintenance, its implementation and latest trends. Proc. Inst. Mech. Eng. Part B: J. Eng. Manuf., 231, 9, 1670–1679, 2017.
1 *Corresponding author: padilha@decom.fee.unicamp.br