Blessing Allen-Adebayo, Olateru Kehinde
Department of Biological Sciences (Microbiology), College of Natural and Applied Sciences, Okada, Nigeria.
ZeroComplex AI, Lagos, Nigeria.
Front Microbiol. 2025 Apr 28;16:1504254. doi: 10.3389/fmicb.2025.1504254. eCollection 2025.
This narrative review explores the transformative potential of artificial intelligence (AI) in optimizing bioremediation systems for river pollution control while addressing the challenges and limitations associated with its implementation. The review begins by examining traditional and emerging bioremediation methods, highlighting their limitations and the pressing need for innovative solutions. It then delves into the application of AI technologies in pollution monitoring and bioremediation optimization, providing examples and success stories from existing studies. The challenges of AI-driven bioremediation, including ethical concerns, technological constraints, and the need for responsible deployment, are critically analyzed. Emphasis is placed on fostering interdisciplinary collaboration to overcome these barriers. The review also presents future directions and actionable recommendations, including integrating AI with traditional approaches, addressing technological and policy gaps, and ensuring sustainable management of river ecosystems. Ultimately, this review stresses the revolutionary potential of AI in enhancing bioremediation systems and advocates for urgent action to address the challenges involved, paving the way for sustainable and effective river pollution control strategies.
这篇叙述性综述探讨了人工智能（AI）在优化河流污染控制生物修复系统方面的变革潜力，同时阐述了其实施过程中所面临的挑战和局限。综述首先审视传统及新兴生物修复方法，突出其局限性以及对创新解决方案的迫切需求。接着深入探究人工智能技术在污染监测和生物修复优化中的应用，并列举现有研究中的示例和成功案例。对人工智能驱动的生物修复所面临的挑战，包括伦理问题、技术限制以及负责任部署的必要性，进行了批判性分析。强调促进跨学科合作以克服这些障碍。综述还提出了未来方向和可行建议，包括将人工智能与传统方法相结合、弥补技术和政策差距以及确保河流生态系统的可持续管理。最终，本综述强调了人工智能在增强生物修复系统方面的变革潜力，并倡导采取紧急行动应对相关挑战，为可持续且有效的河流污染控制策略铺平道路。
