AI-Driven FlightOps: Revolutionizing Airline Operations Control with Predictive Analytics and NLP

Abstract: Flight operations control centers (OCCs) are the nerve centers of airline operations, tasked with managing a wide range of activities such as flight scheduling, crew assignments, maintenance coordination, and dealing with disruptions. While traditional approaches have relied heavily on human decision-making and manual analysis of operational data, the increasing complexity of modern airline operations demands more efficient solutions. This paper presents FlightOps AI, a cutting-edge AIpowered system that integrates advanced natural language processing (NLP), deep neural networks (DNNs), reinforcement learning (RL), and computer vision to provide OCC staff with actionable insights and predictive capabilities. The system processes massive amounts of structured and unstructured data in real time, enabling smarter decision-making and automation of routine tasks. By adopting these technologies, FlightOps AI transforms the operational landscape, optimizing airline performance while minimizing human errors

Authors

Publication Details

Journal
International Journal for Research in Applied Science and Engineering Technology
Published
2024-09-15
DOI
https://doi.org/10.22214/ijraset.2024.64223
Citations
1
Primary Topic
Air Traffic Management and Optimization
Type
article
Field-Weighted Citation Impact
1.30
Controls
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article

AI-Driven FlightOps: Revolutionizing Airline Operations Control with Predictive Analytics and NLP

Sakshi Srivastava, Chandan Srinath
1 citations
International Journal for Research in Applied Science and Engineering Technology
Air Traffic Management and Optimization
1.30
article

AI-Driven FlightOps: Revolutionizing Airline Operations Control with Predictive Analytics and NLP

Sakshi Srivastava, Chandan Srinath
article en
1 citations

Abstract

Abstract: Flight operations control centers (OCCs) are the nerve centers of airline operations, tasked with managing a wide range of activities such as flight scheduling, crew assignments, maintenance coordination, and dealing with disruptions. While traditional approaches have relied heavily on human decision-making and manual analysis of operational data, the increasing complexity of modern airline operations demands more efficient solutions. This paper presents FlightOps AI, a cutting-edge AIpowered system that integrates advanced natural language processing (NLP), deep neural networks (DNNs), reinforcement learning (RL), and computer vision to provide OCC staff with actionable insights and predictive capabilities. The system processes massive amounts of structured and unstructured data in real time, enabling smarter decision-making and automation of routine tasks. By adopting these technologies, FlightOps AI transforms the operational landscape, optimizing airline performance while minimizing human errors

International Journal for Research in Applied Science and Engineering TechnologyVol. 12(9)
Openalex Percentile: Top 13%
Air Traffic Management and Optimization
1.30
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