Type
Real-Time Flight Tracking and Management System
Objective
A global airline service provider hired Adorebits to develop a real-time tracking and management system for flights. The general idea was to integrate flight tracking,
real analytics, and operational data within one system able to handle massive scale data processing and provide predictive insights for optimizing all the operations.
Technologies
React.js, Node.js, Python, SQL, Hadoop, Spark, AWS, Docker, Jenkins
Country
Netherland
Project Attributes
Engagement Model
Dedicated Team Engagement
Duration
19 months
App Users
Flight operations managers, airline coordinators, ground staff, passenger service agents
Challenges
- Aggregation of flight information: The airline has faced the challenge of
agglomerating fragmented sources of flight data coming from airlines, airports, as
well as third-party providers. - Limitations of Real-Time Tracking: These earlier systems took more time to
deliver real-time flight updates, leading to customer dissatisfaction and
operational inefficiencies. - Operations showed high latencies: the number and rate of update require for
real-time tracking and control would not be possible with the existing
infrastructure. - Data Processing & Analysis: It was processing and analyzing millions of
amounts of flights and operational data but could not find actionable insights for
operational improvements. - Scalability issues: With the expansion of the airline, increasing more flights and
international operations, the current systems were unable to scale well.
Solutions
- Flight Data Collection with Node.js & React.js: In React.js, Adorebits built a
scalable, front-end flight tracking system that pulled live flight data via Node.js
from the various sources, including OpenSky and inner-source APIs of airlines. - Advanced Data Processing with Python, Hadoop and Spark: All the key data
pertaining to flight data was processed by having Hadoop and Spark clusters in
the team. - Real-time Data Storage and Retrieval with SQL: All critical data relating to
flight, passenger, and other operational matters was stored in SQL databases
optimized for maximum access speed and updates on the status of flights in
real-time. - Scalable Cloud Infrastructure on AWS: The entire system deployed on AWS
ensured its high availability and scalability in handling global flight tracking and
data-heavy processing. - Containerization with Docker and Continuous Integration with Jenkins: For
ensuring easy and effective deployment of the flight management application
across various environments, Docker was used for containerizing. Jenkins
automated CI/CD pipeline, enhancing efficiency in code updates and rollouts in
the system.
Results:
- Enhanced Real-Time Tracking: Latency for real-time flight data was reduced by the new system, hence up to 40% improvement in data update and operational decisions during a flight.
- Predictive Maintenance: Using machine learning models powered by Spark and Python, we decreased unscheduled maintenance from 30 percent to get up to 10 percent aircraft uptime.
- Optimized Flight Scheduling: Predictive analytics in the airline has optimized flight scheduling, which led to 20% on-time arrival and departure.
- Improved scalability: The infrastructure of AWS cloud and Docker containerization has meant easy scalable linear expansion of the system with growing international airports in new regions.
- Cost-Efficient Data Processing: Hadoop and Spark easily handled big data and reduced 25% of the operational expenses related to data processing and handling.
Conclusion:
Adorebits’ Real-Time Flight Tracking and Management System enabled the airline to gain better control over flight operations and increase visibility into all stages of the flight process through improved decision-making ability, making them a major player in the rapidly evolving aviation industry.