Abstract
Environmental pollution from heavy metals, plastics, and industrial waste severely threatens global ecosystems. Traditional remediation methods often fall short, being energy-intensive, expensive, and inefficient. Nanobioremediation—combining nanotechnology with biological cleanup—offers a sustainable, faster alternative. This paper explores its enhancement through advanced technologies like AI, Machine Learning, IoT, Digital Twins, and Big Data Analytics, creating intelligent and predictive remediation systems. Key applications include AI-optimized nanoparticles, smart biosensors, robotic cleanup, and predictive process modeling. While evaluating critical challenges such as nanoparticle toxicity, computational limits, and regulatory hurdles, the review highlights future prospects like autonomous ecosystems and synthetic biology to advance Sustainable Development Goals.
