To read this content please select one of the options below:

Predicting Household Plastic Level Consumption Using Machine Learning and Artificial Intelligence (AI)

aUniversity of Mauritius, Mauritius
bInternational Economics Ltd, Mauritius
cMini Factory Ltd, Mauritius

Artificial Intelligence, Engineering Systems and Sustainable Development

ISBN: 978-1-83753-541-5, eISBN: 978-1-83753-540-8

Publication date: 18 January 2024

Abstract

Mauritius is a Small Island Development State (SIDS) with limited resources, and it has been witnessed that many containers used for storing household and industrial products are made from plastic. When discarded as waste, those plastic containers pose a serious environmental and economic challenge for Mauritius. Moreover, landfill space is getting increasingly scarce, and plastic waste is contaminating both land and water. Therefore, it is of the utmost necessity to develop solutions for Mauritius' plastic wastes. Due to its abundance and accessibility, plastic waste is a promising material for recycling and energy production. One potential solution is the use of machine learning and artificial intelligence (AI) to predict household plastic consumption, allowing policymakers to design effective strategies and initiatives to reduce plastic waste. Such information is a critical component to be able to efficiently plan for the collection and routing of trucks when collecting recyclable plastics. The development of new strategies for the recycling of plastic waste and development of new industry can address the import and export potential of the country to achieve self-sustainability as well as contribute to reduction in plastic pollution and amount of waste landfilled. These plastics can thereafter be used effectively for recycling and for the making of 3D printing filaments which fall under the SDGs 9 (Industry, Innovation and Infrastructure) and 12 (Responsible consumption and production).

Keywords

Citation

Jeetah, P., Chuttur, Y.M., Hurry, N., Tahalooa, K. and Seebun, D. (2024), "Predicting Household Plastic Level Consumption Using Machine Learning and Artificial Intelligence (AI)", Fowdur, T.P., Rosunee, S., Ah King, R.T.F., Jeetah, P. and Gooroochurn, M. (Ed.) Artificial Intelligence, Engineering Systems and Sustainable Development, Emerald Publishing Limited, Leeds, pp. 43-53. https://doi.org/10.1108/978-1-83753-540-820241004

Publisher

:

Emerald Publishing Limited

Copyright © 2024 Pratima Jeetah, Yasser M Chuttur, Neetish Hurry, K Tahalooa and Danraz Seebun. Published under exclusive licence by Emerald Publishing Limited