Exploring a Pragmatic and Exponential Advancement in the Use of Machine Learning and Artificial Intelligence Systems

Mazi, Chinedu Chukwuemeka and Anichebe, Gregory and Anya, Ogechi Ifeoma and Nwanakwaugwu, Andrew Chinonso (2024) Exploring a Pragmatic and Exponential Advancement in the Use of Machine Learning and Artificial Intelligence Systems. Asian Journal of Research in Computer Science, 17 (5). pp. 201-211. ISSN 2581-8260

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Abstract

With the advent of the Internet of Things (IoT) with sensors and connected devices, data generation is increasingly peaking at an unprecedented pace. However, energy consumption is also on the rise based on traditional energy sources, such as fossil fuels. This is not sustainable and could hurt the environment while being quite expensive to run e.g., empowering irrigation systems using sensors. In this context, using data as an energy source for future machines could be a promising solution to mitigate the energy crisis and reduce the carbon footprint. The concept of data as a new form of energy will be discussed, examining the benefits and challenges associated with this method. This paper also proposes other potential applications for using data as an energy source, including powering self-driving cars, drones, and smart irrigation systems a data-driven approach.

Item Type: Article
Subjects: OA Open Library > Computer Science
Depositing User: Unnamed user with email support@oaopenlibrary.com
Date Deposited: 19 Mar 2024 08:18
Last Modified: 19 Mar 2024 08:18
URI: http://archive.sdpublishers.com/id/eprint/2570

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