A review on control and abatement of soil pollution by heavy metals: Emphasis on artificial intelligence in recovery of contaminated soil

Abstract

"Save Soil Save Earth" is not just a catchphrase; it is a necessity to protect soil ecosystem from the unwanted and unregulated level of xenobiotic contamination. Numerous challenges such as type, lifespan, nature of pollutants and high cost of treatment has been associated with the treatment or remediation of contaminated soil, whether it be either on-site or off-site. Due to the food chain, the health of non-target soil species as well as human health were impacted by soil contaminants, both organic and inorganic. In this review, the use of microbial omics approaches and artificial intelligence or machine learning has been comprehensively explored with recent ad-vancements in order to identify the sources, characterize, quantify, and mitigate soil pollutants from the envi-ronment for increased sustainability. This will generate novel insights into methods for soil remediation that will reduce the time and expense of soil treatment.