The transportation industry helps connects us to our loved ones, our jobs, food needs, building materials and practically every aspect of our economy. Over the last 100 years, the transportation system that connects our cities, regions and countries along with substantial population growth has led to what many believe is unsustainable for our planet both from a utilization of available fuels and the emissions produced during transportation. Among the modes of transportation available, air travel (both manned and unmanned) allows the most expeditious means of movement. However, the complexity involved in the systems-of-systems to ensure safe and efficient flight is among the most complex on planet Earth. Even straightforward changes to this complex network of aviation solutions are difficult. Often new ideas that work well in high fidelity simulation do not translate well into actual air traffic operational situations. The most common cause for this is the high expense of creating simulation platforms and omitting key operational factors that were not known to the innovators when performing their analysis.
So what is the solution?
Modern predictive analytics techniques, including machine learning and cross industry standard platform for data mining (CRISP-DM) practices, provide a great opportunity for rapid advancement to the aviation industry. However, one of major blockers to rapid progress utilizing techniques is the lack of open sharing required for these data hungry approaches. The current day U.S. aviation system and the data it produces is separated by domain (surface, terminal, enroute) as well as governance (local, regional, national). The consumers in this environment (airlines, airports, GA/BA, newer entrants) can also be hesitant to share data, processes and other information that would help lead to substantial breakthroughs for the entire community. To this end, an unbiased and facts driven organization can serve as an ambassador to the stakeholders of the aviation community and help provide recommendations for substantial positive changes. Aviation Data Science imagines an environment in which scientifically based organizations that do not receive financial support from any of the current system stakeholders allows for the most independent and unbiased platform from which to make its recommendations. This was the motivation for formulating a non-profit organization.
All aviation system stakeholders benefit from greater conservation of energy. Fuel savings help generate profit which leads to employment opportunities, while also reducing the burden on limited natural resources, reducing emissions and encouraging sustainable practices. Progress toward energy efficiency is key to obtain and retain stakeholder confidence. Many can create new ideas and simulate them, but thus far very few have demonstrated the ability to integrate these ideas into the complex aviation system. Actual evidence of progress in the operational environment is the gold standard that contributors seek to make.
If you are a like-minded individual, reach out to info@aviationdatascience.org to contribute to great mission that will help generations to come.