Speaker
Description
Aliyu, Y.
Federal College of Education Technical Gusau Zamfara Stae
yahayaaliyumaradun@yahoo.com
Track: AI, Emerging Technologies and Future Learning
Environmental pollution remains one of the most significant threats to global public health and ecological sustainability. Rapid urbanization, industrialization, and unsustainable human activities have intensified air, water, and land pollution, as a result of which conventional pollution control approaches have often proved inadequate in addressing these growing environmental challenges. Artificial Intelligence (AI) has emerged as a transformative technology capable of enhancing pollution monitoring, prediction, prevention, and remediation through intelligent data analysis and automated decision-making. This paper reviews the prospects and challenges of AI-driven solutions for environmental pollution control across major environmental domains. It examines the application of AI in real-time pollution monitoring, hyper-local air quality forecasting, intelligent wastewater treatment, automated waste sorting, industrial emission control, and support for sustainable practices such as renewable energy integration, electric mobility, and green infrastructure. The review also highlights key challenges limiting the effective deployment of AI, including high energy and water consumption by data centers, electronic waste generation, environmental impacts associated with rare-earth mineral extraction, data quality concerns, ethical issues, and the shortage of AI professionals with environmental expertise. The paper concludes that while AI offers significant opportunities for improving environmental management and accelerating sustainable development, addressing these technical, environmental, and institutional challenges are essential to realize its full potential in pollution control.