Artificial Intelligence for Environmental Monitoring and Sustainable Development

Abstract

This paper explores the role of AI in environmental monitoring and sustainable development, with specific emphasis on the Nigerian context. Using systems theory as the conceptual framework, the study highlights the diverse applications of AI, including remote sensing, air and water quality assessment, waste management, biodiversity conservation, and disaster risk prediction. Artificial Intelligence (AI) has emerged as a transformative tool in addressing the pressing challenges of environmental monitoring and sustainable development. By leveraging advanced machine learning algorithms, computer vision, and data analytics, AI enables efficient collection, processing, and interpretation of large-scale environmental data. Applications span across climate modelling, air and water quality assessment, biodiversity conservation, precision agriculture, renewable energy optimisation, and disaster risk management. AI-powered systems enhance the accuracy of predictions, support real-time monitoring, and facilitate informed decision-making for policymakers and stakeholders. Despite its vast potential, challenges such as data privacy, high energy consumption, technological inequality, and ethical considerations remain critical concerns. Integrating AI into environmental management requires collaborative frameworks that balance technological innovation with ecological and social responsibility. Furthermore, the paper examines how AI contributes to the achievement of Sustainable Development Goals (SDGs), particularly Goals 6, 7, 11, and 13, fostering resilient ecosystems and promoting a greener, more sustainable future.