Artificial intelligence in heavy metals detection: Methodological and ethical challenges

Abstract

Heavy metals (HMs) are metallic substances. They enter biotic and abiotic systems through natural and human activities. These HMs have an impact on the atmosphere, soil, and groundwater, and they also affect all living things, especially humans, when they enter the food chain. Therefore, monitoring and removing HMs from the environment and humans are crucial for maintaining HMs-based toxicity. The detection of HMs from environmental and human samples has been performed by techniques such as atomic adsorption spectrometry (AAS) and inductively coupled plasma mass spectrometry (ICP-MS). With the advancement of AI-based technology, HMs are now detected and removed from the environment and human systems. This review discusses the impact of HMs on the environment and human health, their detection and removal techniques, and the integration of recent advancements in AI-based technology for the detection and removal of HMs from environmental and human samples.

Keywords

• Heavy metals (HMS)
• Environment
• Human health
• Artificial intelligence (AI)