AVIATION ANALYTICS AND THE INTERNET OF THINGS

This paper describes a series of short experiments collecting and analyzing ADS B data using IoT (Internet of Things) devices. The collection is performed using a Raspberry Pi single board computer, an RTL-SDR radio, custom software written for the project, and the open source dump1090 software program. This Raspberry Pi/RTL-SDR/dump1090 combination is used to collect ADS-B data. The data is captured and archived using a software program that reads the ADS-B data in real time as it is received by the RTL-SDR radio and subsequently output by the dump1090 program. The captured data is written to a series of flat files. Subsequent analytics and analysis is performed using the R programming language and the R Studio environment. The paper describes a subset of the R code that that was used in the analysis. All of the custom software used in this project is freely available at GitHub (see References section). An exhaustive analysis is not performed as part of this work. The intent of the limited analysis in this work is to provide a proof of concept for the kinds of analyses that could be done, if aviation data, such as ADS, was widely and freely available. The analysis that is performed is an initial top level analysis, designed to assess the feasibility of using this low cost combination of hardware, software, and analysis tools for use in advisory air traffic applications such as airspace monitoring and traffic monitoring. Suggestions and recommendations for additional work appear in the Observations and Continuing Work sections of this paper.