Computers in the Modern Era: Applications and Innovations
Keywords:
Computer Applications, Technological Advancements, Artificial Intelligence, Digital TransformationAbstract
Computers have become essential tools in the modern era, influencing every aspect of daily life and transforming industries such as education, healthcare, business, entertainment, and scientific research. This paper explores the evolution of computers from early mechanical devices to advanced digital systems, highlighting their pivotal role in reshaping how we work, communicate, and solve problems. Key applications across various fields demonstrate the versatile capabilities of computers, from enabling remote learning and improving patient care to revolutionizing e-commerce and digital content creation. Additionally, recent technological advancements, including Artificial Intelligence (AI), the Internet of Things (IoT), and cloud computing, have expanded the potential of computers, enhancing efficiency, connectivity, and data management. These innovations are driving future developments in fields like quantum computing, augmented reality, and Biocomputing, which promise to redefine possibilities in science, security, and sustainability. While computers have brought immense benefits, they also introduce challenges related to privacy, cybersecurity, and job displacement. The paper concludes by discussing the transformative power of computers and the importance of ethical considerations in ensuring their continued positive impact on society.
Downloads
References
Sriram, G.S. Edge computing vs. Cloud computing: An overview of big data challenges and opportunities for large enterprises. Int. Res. J. Mod. Eng. Technol. Sci. 2022, 4, 1331–1337.
Rosendo, D.; Costan, A.; Valduriez, P.; Antoniu, G. Distributed intelligence on the Edge-to-Cloud Continuum: A systematic literature review. J. Parallel Distrib. Comput. 2022, 166, 71–94.
Barbuto, V.; Savaglio, C.; Chen, M.; Fortino, G. Disclosing edge intelligence: A systematic meta-survey. Big Data Cogn. Comput. 2023, 7, 44.
Pujol, V.C.; Donta, P.K.; Morichetta, A.; Murturi, I.; Dustdar, S. Edge intelligence—Research opportunities for distributed computing continuum systems. IEEE Internet Comput. 2023, 27, 53–74.
Armbrust, M.; Fox, A.; Griffith, R.; Joseph, A.D.; Katz, R.; Konwinski, A.; Lee, G.; Patterson, D.; Rabkin, A.; Stoica, I.; et al. A view of cloud computing. Commun. ACM 2010, 53, 50–58.
García-Valls, M.; Cucinotta, T.; Lu, C. Challenges in real-time virtualization and predictable cloud computing. J. Syst. Archit. 2014, 60, 726–740.
Buyya, R.; Srirama, S.N. Fog and Edge Computing: Principles and Paradigms; John Wiley & Sons: Hoboken, NJ, USA, 2019.
Sowmya, S.K.; Deepika, P.; Naren, J. Layers of cloud–IaaS, PaaS and SaaS: A survey. Int. J. Comput. Sci. Inf. Technol. 2014, 5, 4477–4480.
Wittig, A.; Wittig, M. Amazon Web Services in Action: An In-Depth Guide to AWS; Simon and Schuster: New York, NY, USA, 2023.
Copeland, M.; Soh, J.; Puca, A.; Manning, M.; Gollob, D. Microsoft azure and cloud computing. In Microsoft Azure: Planning, Deploying, and Managing Your Data Center in the Cloud; Apress: Berkeley, CA, USA, 2015; pp. 3–26.
Bisong, E. Building Machine Learning and Deep Learning Models on Google Cloud Platform; Apress: Berkeley, CA, USA, 2019.
Mishra, S.; Tripathi, A.R. AI business model: An integrative business approach. J. Innov. Entrep. 2021, 10, 18.
Downloads
Published
Issue
Section
License
Copyright (c) 2024 International Journal of Scientific Research in Computer Science, Engineering and Information Technology
This work is licensed under a Creative Commons Attribution 4.0 International License.