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Autonomous Energy-Efficient Drone System for Intelligent Aircraft Inspection Using Hybrid Hydrogen Power and Multimodal AI Vision
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Author(s): R. Deepa (SRM Institute of Science and Technology, India), R. Chiranth (SRM Institute of Science and Technology, India), L. K. Shoba (SRM Institute of Science and Technology, India), V. K. Kishore (SRM Institute of Science and Technology, India)and A. Bennet Prabhu (Congruent Solutions - R&D Development, India)
Copyright: 2027
Pages: 34
Source title:
GIS Applications for Enhancing Sustainable Operational Performance of Manufacturing Industries
Source Author(s)/Editor(s): Kamalakanta Muduli (Papua New Guinea University of Technology, Papua New Guinea), Sujoy Kumar Jana (Papua New Guinea University of Technology, Papua New Guinea), Rashmi Prava Das (CV Raman Global University, Odisha, India)and Indrajit Pal (Asian Institute of Technology, Thailand)
DOI: 10.4018/979-8-3373-7941-8.ch002
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Abstract
This research proposes a self-sufficient, energy-efficient drone system for smart aviation inspection, integrating hybrid hydrogen-electric propulsion to achieve longer range with reduced carbon emissions. Equipped with a multimodal AI vision system combining infrared thermography, high-resolution RGB imagery, and 3D LiDAR sensing, the drone ensures robust defect detection under varying conditions. Onboard deep learning fusion, SLAM, and GPS-denied localization techniques enable seamless autonomous navigation in both indoor hangars and outdoor airfields. By combining sustainable propulsion with advanced AI-driven inspection capabilities, the system significantly improves inspection accuracy, reduces downtime, and enhances overall sustainability in aviation maintenance.
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