Role of AI in reducing global Plastics use: Predictive analytics for global sustainability
1 Mathematics, Minnesota State University-Mankato, Minnesota, USA.
2 Cox School of Business, Southern Methodist University, Dallas, USA.
3 Mechanical Engineering, Jomo Kenyatta University of Agriculture and Technology, Nairobi Kenya
Review Article
Global Journal of Engineering and Technology Advances, 2024, 21(02), 057-069.
Article DOI: 10.30574/gjeta.2024.21.2.0204
Publication history:
Received on 24 September 2024; revised on 03 November 2024; accepted on 05 November 2024
Abstract:
The growth, from a global perspective, in plastic waste sees its necessary promise in Artificial Intelligence. The driving force of Machine Learning, Computer Vision, and Predictive Analytics, shapes each style of waste management and effective collection routes to recycling. In this paper, therefore, the discussion will be on how AI can ensure a reduction in plastic waste, focusing on developing countries such as Nigeria. The theoretical underpinning of this research is on AI adoption, the Technology Acceptance Model, a few real-world case studies in AI for waste reduction, and many challenges that need to be focused on due to issues of data sparsity, infrastructure limitations, and ethics. Using these challenges for unlocking the full potential of AI in the direction of a more sustainable future, with minimal plastic waste at the forefront of environmental well-being, could be better negotiated. As the global community faces the pressing need to tackle plastic pollution, especially in areas with inadequate waste management systems and severe environmental challenges AI technologies present groundbreaking solutions to improve waste management methods, eliminate environmental harm, and foster sustainable growth. A crucial factor influencing the future of AI-driven plastic waste reduction in developing countries is the ongoing progress and implementation of AI technologies.
Keywords:
Global Plastics; AI; plastic waste management; Pollution
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Copyright © 2024 Author(s) retain the copyright of this article. This article is published under the terms of the Creative Commons Attribution Liscense 4.0