Leveraging AI and Machine Learning for Sustainable Development

Abstract : Global sustainability is increasingly challenged by climate change, resource depletion, and environmental degradation. This research investigates the application of Artificial Intelligence (AI) and Machine Learning (ML) methodologies as potent tools for addressing these critical issues. By optimizing resource utilization, minimizing waste, and facilitating data-driven decision-making, AI/ML offers significant potential for enhancing sustainability practices. This paper presents an integrated framework that leverages a suite of AI/ML techniques, including Deep Learning, Reinforcement Learning, and Random Forests, to improve sustainability outcomes across diverse sectors. The framework utilizes data acquired from Internet of Things (IoT) sensors, satellite imagery, and environmental monitoring systems to predict environmental patterns, optimize resource allocation, and promote sustainable behaviors. Performance evaluation, conducted using Performance such as accuracy, precision, and recall, demonstrates the efficacy of the proposed model in contributing to global sustainability objectives. This study aims to provide a scalable, data-driven solution seamlessly integrated into existing sustainability models, thereby fostering a reduced environmental impact and promoting a more sustainable future.

Keyword Artificial Intelligence, Machine Learning, Sustainable Practices, Climate Change Mitigation, Resource Efficiency, Environmental Surveillance.