Issue |
E3S Web Conf.
Volume 608, 2025
EU-CONEXUS EENVIRO Research Conference - The 9th Conference of the Sustainable Solutions for Energy and Environment (EENVIRO 2024)
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Article Number | 05013 | |
Number of page(s) | 8 | |
Section | Sustainable Development | |
DOI | https://doi.org/10.1051/e3sconf/202560805013 | |
Published online | 22 January 2025 |
AI-Powered Sustainable Environmental Practices using Laser-Induced Breakdown Spectroscopy (LIBS)
1 Dept. of Electronics Engineering and Communications, South East Technological University, Carlow, Ireland
2 Dept. of Physics and Chemistry, FAST, University Tun Hussein Onn Malaysia (UTHM), Johor, Malaysia
3 Department of Science and Mathematics, Universiti Tun Hussein Onn Malaysia, Johor, Malaysia
4 Department of Physics, Faculty of Science, Universiti Putra Malaysia, 43400, UPM Serdang, Malaysia
Technological advancements in artificial intelligence (AI) have the potential to lead the way in promoting sustainable environmental practices as well as support environmental sciences and biodiversity field studies and research. The research will focus on designing an innovative system architecture that integrates laser-induced breakdown spectroscopy (LIBS) with a robust machine learning (ML) framework, significantly advancing sustainable environmental practices, especially since LIBS offers rapid and precise multi-elemental analysis, while AI enhances data processing and predictive capabilities. As technological innovations advance, the integration of the suggested LIBS system and advanced AI will be pivotal in addressing environmental challenges and promoting sustainability. This paper presents LIBS analytical data used to qualitatively assess soil constituents as a case study.
Key words: laser-induced breakdown spectroscopy (LIBS) / LIBS for Environmental sciences / AI for sustainable environmental practices / elements identification in soil / environmental sustainability and digital technology
© The Authors, published by EDP Sciences, 2025
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