AI-Driven Non-Invasive Carbon Emission Monitoring in Logistics: Advancing Sustainability and Operational Efficiency

This paper presents an in-depth exploration of innovative strategies for the sustainable integration of artificial intelligence (AI), emphasizing its transformative influence on non-invasive carbon emission monitoring in logistics, operational efficiency, and environmental accountability. The potential of AI to revolutionize sustainable practices is analysed through its application in the logistics and supply chain sectors, underscoring the emergence of models designed to optimize resource utilization and minimize carbon emissions. Specifically, we examine the deployment of AI-driven solutions for non-intrusive carbon emission monitoring and real-time data analytics, demonstrating their role in enhancing sustainability and operational excellence. Furthermore, this paper highlights how AI integration contributes to the evolution of compliance standards, the automation of customs processes, and predictive logistics, thereby fostering a synergy between technology, sustainability practices, and regulatory frameworks. The findings offer valuable insights for decision-makers, showcasing scalable, AI-powered solutions that align with and advance global sustainability objectives.