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Smart Aviation with Customized Route Discovery Using Urban Transportation Analytics

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Abstract

Adapting to the growing aviation traffic has become an immense challenge on a global scale. The aviation industry has become a crucial component of our society and is a major force behind global economic, social, and cultural advancement. Our research examines aviation connectivity using network centrality based on topological characteristics. The goal is to achieve urban sustainability by analyzing the airways transportation system, especially when some airports are not functioning due to epidemics or chaotic outbursts. For this purpose, this research has proposed an efficient model for recommending a set of convenient alternative routes between airports based on a number of connecting flights and customizing the route discovery. We have performed urban transportation analytics for India and generalized the approach for worldwide air routes. Our work will assist the passengers in selecting the best routes based on their preferences of cost, distance, and places to visit during the journey. Our country-specific as well as worldwide case studies are performed with geo-visualizations, along with the network centrality and optimal route statistics.

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Data Availability

Research data associated with this paper is acquired from OpenFlights, which is available on public domain.

Code Availability

The research code will be made available on-request from readers.

Abbreviations

ITS :

Intelligent Transportation System

IATA :

International Air Transport Association

ICAO :

International Civil Aviation Organization

LAT :

Latitude

LONG :

Longitude

ALT :

Altitude

Tz DT :

Timezone in “tz” (Olson) format in Database Time

DST :

Daylight Saving Time

GDP :

Gross Domestic

AAI :

Airport Authority of India

PPA :

Population per Unit

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Acknowledgements

The authors express gratitude to the institutional support provided in form of server and internetworking support for data analysis and visualization.

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The authors have not received any financial assistance or grant for research in this manuscript.

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Authors and Affiliations

  1. Department of Computer Science & Engineering and Information Technology, Jaypee Institute of Information Technology, Noida, Uttar Pradesh, 62, India

    Akansha Agarwal,  Shreeji & Ravi Jain

  2. Department of Computer Science & Information Technology, KIET Group of Instituitons, Ghaziabad, Uttar Pradesh, India

    Meeta Chaudhry

  3. Department of Natural & Applied Sciences, TERI School of Advanced Studies, Delhi, India

    Adwitiya Sinha

Authors
  1. Akansha Agarwal
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  2. Shreeji
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  3. Ravi Jain
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  4. Meeta Chaudhry
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Contributions

Conceptualization was done by S., A.A., R.J. and A.S.; methodology was proposed by S. and A.A.; literature suvey was conducted by M.G.; resources and data curation by R.J.; Code development and debugging by S., A.A., R.J.; formal analysis by A.S.; program validation by A.S., original draft preparation by S., A.A., R.J.; review and editing by A.S. and M.G.; supervision and project administration by A.S. All authors have read and agreed to the final version of the manuscript.

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Correspondence to Adwitiya Sinha.

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Agarwal, A., Shreeji, Jain, R. et al. Smart Aviation with Customized Route Discovery Using Urban Transportation Analytics. Int. J. ITS Res. 22, 229–244 (2024). https://doi.org/10.1007/s13177-024-00390-8

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