Space Apps Challenge 2017

The performed analysis considers correlation between local Particulate Matter (PM) concentration, average weather conditions and aviation statistics and impact growth in the vicinity of the airport. Airfleet and airport infrastructure itself is a significant source of environmental impact and PM. The research requires consideration of various parameters on longer time scales and more detailed datasets to understand the interdependencies between local air quality, meteorological conditions, economical activity and air traffic growth. This work serves as a minor upgrade to already developed Pollutant Automated Wireless Node (PAWN) on IoT platform. Potentially this project can provide transparent and clear service on monitoring and understanding aviation environmental impact and climate change.

Data collection – U.S. aviation transportation, PM and meteo statistics:

https://wonder.cdc.gov/EnvironmentalData.html

https://www.transportation.gov/policy/aviation-policy/us-international-air-passenger-and-freight-statistics-report

http://airlines.org/data/

https://www.transtats.bts.gov/TRAFFIC/

http://openflights.org/data.html

https://aspm.faa.gov/tfms/sys/OPSNET.asp

Data processing and analysis using Microsoft Power BI tool and Azure ML.