Advancements in Intelligent Systems: Transforming Engineering Applications

Authors

  • Rudresh Shirwaikar, S. Shalini, Nithya A., M. A. Prasanna, Laith Abualigah, G. Umamahesh

Keywords:

Intelligent Systems, Transforming of Engineering, AI & ML

Abstract

Intelligent systems, powered by artificial intelligence and machine learning techniques, have revolutionized various domains, including engineering applications. This paper explores the significant advancements in intelligent systems and their transformative impact on engineering practices. It examines how these systems have enhanced efficiency, accuracy, and innovation across diverse engineering disciplines. Through case studies and examples, this paper illustrates the evolving landscape of intelligent systems and their profound implications for the future of engineering

Downloads

Download data is not yet available.

References

Chen, C., & Hao, Q. (2019). Predictive maintenance strategy for manufacturing systems: A review. Journal of Manufacturing Systems, 53, 241-261.

Wang, J., Ran, W., & Zhang, L. (2020). A review on structural health monitoring of civil infrastructure using fiber-optic sensing technology. Engineering Structures, 216, 110735.

Rajesh, R., & Latha, R. (2021). A review on applications of robotics and automation in manufacturing sector. Materials Today: Proceedings, 46(4), 3724-3727.

Wang, J., Qi, W., & Liu, Y. (2020). A comprehensive review on smart grid technology. International Journal of Electrical Power & Energy Systems, 123, 106157.

Bogue, R. (2019). Drones for good: How they’re being used to save lives. Engineering & Technology, 14(6), 68-71.

Green, S., & Press, A. (Eds.). (2020). AI and the Ethics of Engineering (Vol. 73). Springer.

National Academies of Sciences, Engineering, and Medicine. (2019). Artificial Intelligence and Privacy: A Scoping Report. National Academies Press.

Lee, J., & See, K. (2021). Human-robot collaboration in manufacturing: A review. Robotics and Computer-Integrated Manufacturing, 68, 102098.

F.H. Alqahtani, The application of the Internet of Things in healthcare. Int. J. Comput. Appl. 180(18), 0975–8887 (2018)

Aravantinos, V., Chatzi, E. N., Papadimitriou, C., & Ntotsios, E. (2020). A novel AI-based methodology for vibration-based structural health monitoring. Mechanical Systems and Signal Processing, 135, 2.

Farhan M, Jabbar S, Aslam M, Hammoudeh M, Ahmad M, Khalid S, et al. IoT-based students interaction framework using attention-scoring assessment in eLearning. Future Generation Computer Systems 2018;79:909–19.

Haque S, Zeba S, Alimul Haque Md, Kumar K, Ali Basha MP. An IoT model for securing examinations from malpractices. Materials Today: Proceedings 2021. https://doi.org/10.1016/j.matpr.2021.03.413.

Haque MdA, Sonal D, Haque S, Rahman M, Kumar K. Learning management system empowered by machine learning, 2022, p. 020085. https://doi.org/10.1063/5.0074278

Goksel N, Bozkurt A. Artificial intelligence in education: Current insights and future perspectives. Handbook of Research on Learning in the Age of Transhumanism, IGI Global; 2019, p. 224–36.

Holmes W, Porayska-Pomsta K, Holstein K, Sutherland E, Baker T, Shum SB, et al. Ethics of AI in education: Towards a community-wide framework. International Journal of Artificial Intelligence in Education 2021:1–23.

Selwyn N. The future of AI and education: Some cautionary notes. European Journal of Education 2022;57:620–31.

Shum SJB, Luckin R. Learning analytics and AI: Politics, pedagogy and practices. British Journal of Educational Technology 2019;50:2785–93.

Guleria P, Sood M. Explainable AI and machine learning: performance evaluation and explainability of classifiers on educational data mining inspired career counseling. Education and Information Technologies 2023;28:1081–116.

Sottilare R, VanLehn K. Intelligent tutoring systems swot analysis. Design Recommendations for Intelligent Tutoring Systems 2020.:27.

Zeba S, Haque MA, Alhazmi S, Haque S. Advanced Topics in Machine Learning. Machine Learning Methods for Engineering Application Development 2022:197.

Basnet RB, Johnson C, Doleck T. Dropout prediction in Moocs using deep learning and machine learning. Education and Information Technologies 2022;27:11499–513.

Downloads

Published

26.03.2024

How to Cite

Rudresh Shirwaikar,. (2024). Advancements in Intelligent Systems: Transforming Engineering Applications. International Journal of Intelligent Systems and Applications in Engineering, 12(21s), 3319–3325. Retrieved from https://ijisae.org/index.php/IJISAE/article/view/6023

Issue

Vol. 12 No. 21s (2024)

Section

Research Article

License

Creative Commons License

This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

All papers should be submitted electronically. All submitted manuscripts must be original work that is not under submission at another journal or under consideration for publication in another form, such as a monograph or chapter of a book. Authors of submitted papers are obligated not to submit their paper for publication elsewhere until an editorial decision is rendered on their submission. Further, authors of accepted papers are prohibited from publishing the results in other publications that appear before the paper is published in the Journal unless they receive approval for doing so from the Editor-In-Chief.

IJISAE open access articles are licensed under a Creative Commons Attribution-ShareAlike 4.0 International License. This license lets the audience to give appropriate credit, provide a link to the license, and indicate if changes were made and if they remix, transform, or build upon the material, they must distribute contributions under the same license as the original.