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.
Juboori et al. (2025) studied this question.