Windiford, Kristel Maud (2025) The use of Artificial Intelligence within aviation sustainability. Bachelorarbeit, IU.
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Kurzfassung
The aviation industry plays a critical role in global connectivity but also contributes significantly to climate change, accounting for 2–3% of global carbon emissions. This thesis explores the role of Artificial Intelligence (AI) in advancing aviation sustainability, particularly in reducing greenhouse gas (GHG) emissions. The research addresses the question: What AI technologies can be integrated into aviation operations to optimise performance while supporting sustainability goals? A qualitative, literature-based methodology was adopted to systematically analyse peer-reviewed studies, case reports, and industry white papers. The review focused on AI applications in predictive maintenance, flight management systems, contrail detection, and the challenges of AI adoption in the aviation sector. Findings reveal that AI enhances fuel efficiency, enables proactive maintenance, and improves decision-making through real-time analytics. However, widespread adoption is hindered by regulatory gaps, high costs, data fragmentation, and limited organisational readiness. The study concludes that AI can significantly accelerate aviation’s transition to a low-emissions future if supported by coordinated investment, governance, and trust-building efforts. This thesis provides practical insights and recommendations for policymakers, industry leaders, and researchers seeking to integrate AI into aviation’s sustainability strategy.
| elib-URL des Eintrags: | https://elib.dlr.de/216034/ | ||||||||
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| Dokumentart: | Hochschulschrift (Bachelorarbeit) | ||||||||
| Zusätzliche Informationen: | Betreuer: Dr. Sven Maertens | ||||||||
| Titel: | The use of Artificial Intelligence within aviation sustainability | ||||||||
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| DLR-Supervisor: |
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| Datum: | 9 Juni 2025 | ||||||||
| Open Access: | Nein | ||||||||
| Status: | veröffentlicht | ||||||||
| Stichwörter: | Carbon-offsetting, Sustainability, Artificial Intelligence, Flight trajectory, Predictive maintenance, Contrail | ||||||||
| Institution: | IU | ||||||||
| HGF - Forschungsbereich: | Luftfahrt, Raumfahrt und Verkehr | ||||||||
| HGF - Programm: | Luftfahrt | ||||||||
| HGF - Programmthema: | Luftverkehr und Auswirkungen | ||||||||
| DLR - Schwerpunkt: | Luftfahrt | ||||||||
| DLR - Forschungsgebiet: | L AI - Luftverkehr und Auswirkungen | ||||||||
| DLR - Teilgebiet (Projekt, Vorhaben): | L - Lufttransportbetrieb und Folgenabschätzung, V - VIMITRANS - VerkehrsInnovationen und MIgrationsmethoden für die TRANSformation des Verkehrs | ||||||||
| Standort: | Köln-Porz | ||||||||
| Institute & Einrichtungen: | Institut für Luftverkehr > Luftverkehrsökonomie | ||||||||
| Hinterlegt von: | Maertens, Dr. Sven | ||||||||
| Hinterlegt am: | 10 Dez 2025 09:03 | ||||||||
| Letzte Änderung: | 10 Dez 2025 09:03 |
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