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Research Article Open access CC BY 4.0

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

Chinedu Chukwuemeka Mazi, Gregory Anichebe, Ogechi Ifeoma Anya, Andrew Chinonso Nwanakwaugwu

Asian Journal of Research in Computer Science · pp. 201–211 · Published 18 Mar 2024

10.9734/ajrcos/2024/v17i5449

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.

Data energy consumption future machines IoT machine learning artificial intelligence energy source healthcare

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