Intelligent Airlines Network

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Proposal

Poster

Application

Report

 


Intelligent Airlines Network

ISSS608 Visual Analytics and Applications - Group Project

Prepared by Group 18

Team Members:

  • Debasish Behera
  • Manish Mittal
  • Roger Ganga


Motivation

For a developing country like India, transportation infrastructure is one of the most important indicators for its economic growth. They form the backbone of tourism industry, support movement of goods and people across the country and hence drives the country’s economic growth. Roadways, railways and airways are the major means of transportation in India, however the contribution of airways is small as compared to that of the other two. With the coming of the Narendra Modi government, the civil aviation sector is growing at a rapid rate and with the shift in the govt policy there is expectation of addition of several low-cost private air service providers in the region. These players often offer competitive pricing and thereby driving the air traffic. Understanding of these transportation system is important for many reasons of policy, administration and efficiency. In the past, several studies have been purposed for WAN (worldwide airport network) where it was observed that the most connected nodes are not necessarily the most “central” nodes through which most of the shortest path goes. The reason for this was suggested as geo political constraints. India being a democratic country having 100's of political parties may follow this trend as far as airport network in India is concerned. Our project aims to find out whether this hypothesis is true.

Objective

Our main aim is to investigate the airport network infrastructure of India (ANI) to explore its various properties and its traffic dynamics. We propose to build a visual network exploration tool using R. This tool can be used not only to explore the airport network in India but also can be used to explore any kind of airport network.

Hypothesis

The airport network of India comprises of assortative mixing (high degree nodes tend to connect more to high degree nodes) which is same as that can be found in worldwide network.

Approach & Scope

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Challenges

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References

http://www.sciencedirect.com/science/article/pii/S0378437108001131