A naukri.com initiative
Aviationfile
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Aviation Big Data Project: Turbulence Prediction and Flight Route Optimization
- The “Turbulence Prediction and Route Optimization using Big Data” project focuses on developing a system that uses weather data, in-flight sensor data, and historical flight patterns to predict turbulence and optimize flight routes.
- Integrating big data analytics and machine learning models will enhance passenger safety, minimize flight disruptions, and reduce fuel consumption.
- Seven teams with distinct roles, collectively, ensure the successful delivery of the project.
- The Chief Data Officer (CDO), Data Engineers, Data Scientists, Data Analysts, Software Developers, Cloud Architects, and Security Specialists form the project team.
- The System Development Life Cycle (SDLC) framework adopted in the project breaks the project into distinct, manageable phases.
- The Planning Phase includes identifying project objectives, defining scope, and conducting a feasibility study.
- The Requirement Gathering and Analysis phase includes collaboration with stakeholders, identification of critical data sources, and ensuring compliance with aviation regulations.
- The System Design phase includes high-level and detailed design, defining secure communication channels, and selecting cloud infrastructure.
- The Development Phase includes the machine learning model development, real-time data integration pipeline building, and application interface development.
- The Testing Phase includes unit, integration, and system testing, simulated real-world conditions, and security testing.
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