International Journal of Science, Engineering and TechnologyAuthors: Ms.Tincy Susan Baby
Abstract: Background- The aviation industry facilitates global mobility and trade and at the same time, it only accounts for 2-3 percent of the world’s carbon emissions. With the growing industry demand, aviation companies find themselves in a tight spot—striking a balance between operational efficiency and true sustainability. Objective- This review aims to address emissions and operational performance enhancement in aviation logistics with the help of Artificial Intelligence (AI) and automation technologies. Methods-This paper integrates the application of machine learning, computer vision, natural language processing, robotics, and industrial process automation in aviation industry with the help of case studies from India and the rest of the world alongside industry white papers and academic literature. It takes a systematic literature review of academic studies, white papers from the industry and documented implementations to assess the emerging role and impact of AI-driven technologies in aviation. Result- The findings indicate that AI applications can leverage predictive analytics, optimize resource utilization, enable autonomous operations, and usher in a new passenger experience. Qualitative evidence suggests significant improvements in operational efficiency, system resilience, and service consistency on the part of leading industry players. Conclusion- Collectively, these implementations help the aviation industry carbon reduction targets, including the IATA net zero 2050 emission target. Nonetheless, the more flexible AI systems face integration difficulty, high capital investment, and employee preparedness. The review determined that AI and automation could expedite the shift towards climate-friendly, intelligent aviation logistics, provided strong policies, quality data, and collaboration among all stakeholders is employed.
