International Journal For Multidisciplinary Research

E-ISSN: 2582-2160   •   Impact Factor: 9.24

A Widely Indexed Open Access Peer Reviewed Multidisciplinary Bi-monthly Scholarly International Journal

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Volume 8 Issue 5
September-October 2026

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AI-Enabled Nanotechnology for Environmental Risk Governance: Integrating Machine Learning, Pollution Mitigation, and Disaster Management

Author(s) Mr. Sumanta Bhattacharya, Dr Nirmal Sharma
Country India
Abstract The intersection of NANO+AI+ML is a novel approach for environmental risk governance, pollution control and disaster management. This study investigates the amalgamation of AI-enabled nanotechnology that unites extremely sensitive environmental sensing technology with predictive analytics to bolster detection, assessment, prevention and mitigation of environmental hazards. The research presents a conceptual framework that connects nano-enabled sensing and real-time data generation to AI -based risk prediction, early-warning mechanisms, human-centred decision-making, environmental intervention and regulatory feedback. We particularly focus on the practical applications of pollution monitoring, contaminant detection, environmental remediation, disaster prediction and smart emergency response. It also explores regulatory, ethical, technological and institutional challenges related to the toxicity of nanomaterials, data quality and algorithmic uncertainty, cybersecurity and explainability, lifecycle impacts as well as inadequate governance. It adopts a qualitative, inter-disciplinary research methodology analyzing peer-reviewed research, policy frameworks, technological developments and governance innovation. The study contends that a regulatory architecture for Nano–AI technologies must be risk-based, lifecycle-oriented, adaptive and accountable in order to ensure effective integration between Nanotechnology and AI. Exploiting the synergy between continuous environmental sensing, predictive intelligence and preventive intervention through AI-enabled nanotechnology will effectively lead us from predominantly reactive environmental management to more anticipative forms of environmental governance.
Keywords AI , Nanotechnology , Environmental governance , Nanomaterials , Disaster Management, Pollution control
Published In Volume 8, Issue 5, September-October 2026
Published On 2026-10-11
DOI https://doi.org/10.36948/ijfmr.2026.v08i05.89472
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