Abstract
Today’s in 21st century, we require Digital Transformation everywhere and want to make human life easier and longer to live. Digital Transformation cannot be accomplished by companies/ industries without the use of artificial intelligence (AI, i.e., analytics process) and Internet of Things (IoTs) together. AI and IoTs are the necessity of next decade and of many nations. On another side, some other technology like Blockchain technology and edge computing make the integration these technologies simple and faster. In near future, Digital Transformation will require more than one technology, i.e., integration of technologies will be ion trend. The word 'Intelligent Automation,' which is essentially the automation of the processes of the business (including general corporate-level processes using BPM and unique task-level processes using RPA), is therefore assisted by Artificial Intelligence’s analytics and decisions. This work discusses about Intelligent Automation, its internal structure, evolution and importance (with future work) in many useful applications (for Industry 4.0). In last, Intelligent Automation Systems has been explained for e-healthcare applications and give a perspective “How it can change Healthcare Industry and can save millions of lives.
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References
Lee, I., Lee, K.: The Internet of Things (IoT): Applications, investments, and challenges for enterprises. Bus. Horizons 58(4), 431–440 (2015)
Marzegalli, M., Lunati, M., Landolina, M., Perego, G.B., Ricci, R.P., Guenzati, G., Schirru, M., Belvito, C., Brambilla, R., Masella, C., Di Stasi, F.: Remote monitoring of CRT-ICD: the multicenter Italian CareLink evaluation—Ease of use, acceptance, and organizational implications. Pacing Clin. Electrophysiol. 31(10), 1259–1264 (2008)
Joyia, G.J., Liaqat, R.M., Farooq, A., Rehman, S.: Internet of Medical Things (IoMT): applications, benefits and future challenges in healthcare domain. J. Commun. 12(4), 240–247 (2017)
Gilabert, E., Arnaiz, A.: Intelligent automation systems for predictive maintenance: a case study. Robot. Comput.-Integrated Manuf. 22(5–6), 543–549 (2006)
Vaidya, S., Ambad, P., Bhosle, S.: Industry 4.0–a glimpse. Procedia Manuf. 20, 233–238 (2018)
Willcocks, L., Lacity, M., Craig, A.: Robotic process automation: strategic transformation lever for global business services. J. Inf. Technol. Teach. Cases 7(1), 17–28 (2017)
Russell, S., Norvig, P.: Artificial intelligence: a modern approach (2002)
Gill, S.S., Tuli, S., Xu, M., Singh, I., Singh, K.V., Lindsay, D., Tuli, S., Smirnova, D., Singh, M., Jain, U., Pervaiz, H.: Transformative effects of IoT, Blockchain and Artificial Intelligence on cloud computing: evolution, vision, trends and open challenges. Internet Things 8, 100118 (2019)
Dirican, C.: The impacts of robotics, artificial intelligence on business and economics. Procedia-Soc. Behav. Sci. 195, 564–573 (2015)
Tyagi, A.K.: February. Machine Learning with Big Data. In Machine Learning with Big Data (March 20, 2019). Proceedings of International Conference on Sustainable Computing in Science, Technology and Management (SUSCOM), Amity University Rajasthan, Jaipur-India (2019)
Rekha, G., Tyagi, A.K., Anuradha, N.: Integration of fog computing and internet of things: an useful overview. In: Proceedings of ICRIC 2019, pp. 91–102. Springer, Cham (2020)
Empowering Industry 4.0 with Artificial Intelligence. dqindia.com
Erickson, B.J., et. al.: Machine learning for medical imaging. RadioGraphics 37(2)
Data Science Vs Artificial Intelligence – Eliminate your Doubts, data-flair.training
Aldowah, H.: Internet of Things in Higher Education: A Study on Future Learning, Article in Journal of Physics Conference Series, November 2017
Tyagi, A.K., Chahal, P.: Artificial Intelligence and Machine Learning Algorithms, Book: Challenges and Applications for Implementing Machine Learning in Computer Vision. IGI Global (2020). https://doi.org/10.4018/978-1-7998-0182-5.ch008
Tyagi, A.K., Rekha, G.: Challenges of applying deep learning in real-world applications. Book: Challenges and Applications for Implementing Machine Learning in Computer Vision, IGI Global 2020, pp. 92–118. https://doi.org/10.4018/978-1-7998-0182-5.ch004
Tyagi, A.K., Nair, M.M.: Internet of Everything (IoE) and Internet of Things (IoTs): Threat Analyses, Possible Opportunities for Future, 15(4) (2020)
Tyagi, A.K., Nair, M.M., Niladhuri, S., Abraham, A.: Security, privacy research issues in various computing platforms: a survey and the road ahead. J. Inf. Assurance Secur. 15(1), 1–16. 16p. (2020)
Pramod, A., Naicker, H.S., Tyagi, A.K.: Machine learning and deep learning: open issues and future research directions for next ten years. In: Computational Analysis and Understanding of Deep Learning for Medical Care: Principles, Methods, and Applications, 2020, Wiley Scrivener (2020)
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Tyagi, A.K., Fernandez, T.F., Mishra, S., Kumari, S. (2021). Intelligent Automation Systems at the Core of Industry 4.0. In: Abraham, A., Piuri, V., Gandhi, N., Siarry, P., Kaklauskas, A., Madureira, A. (eds) Intelligent Systems Design and Applications. ISDA 2020. Advances in Intelligent Systems and Computing, vol 1351. Springer, Cham. https://doi.org/10.1007/978-3-030-71187-0_1
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