WHY AVIATION ANALYTICS?
The aviation industry is undergoing a revolution with the adoption of GPS-based navigation and the integration of unmanned air traffic. These technological advances bring tremendous opportunities, but at the same time put many new challenges on the table for Air Traffic Management (ATM) and Air Traffic Control (ATC). These include for example the risk of spoofing and jamming, as well as (drone) penetrations in restricted airspaces or near incidents and even collisions.
Analysts now have access to a vast amount of location based data from ADS-B and other protocols broadcasting the location of both manned and unmanned air traffic. This data is available not only to ATC, but also for analysis, including throughput analysis, separation analysis, incident analysis, etc. Given the vast amount of data, a scalable tool such as xyzt.ai is required to allow analysts to focus on their job and avoid going down the pitfall of having to spend numerous hours in reducing the data, implementing algorithms etc.
Researchers in the field of wireless communication and signal processing, are finding ways to counter spoofing and jamming, to increase the safety of our airspace. For example, the KU Leuven wireless research group of Dr. Pollin, is doing state-of-the-art research in detecting spoofing of ADS-B signals. Using AI-based algorithms, they develop robust methods that can tell whether the reported GPS location of an aircraft, is with high confidence a true location or a faked one. Researching such algorithms requires quick iteration to tune and tweak the parameters, and having a tool such as xyzt.ai that allows quick API-based data ingestion and validation greatly improves their workflow.
CUSTOMER CASE KU LEUVEN
The KU Leuven wireless communication group is using xyzt.ai for quick data visualization and analysis in researching ADS-B anti-spoofing algorithms.
xyzt.ai platform to analyze the accuracy of ADS-B location spoofing detection algorithm.
HOW IT WORKS
The xyzt.ai platform provides REST APIs for data ingestion and data querying, allowing the analysts and researchers to optimize their workflow. Instead of relying on manual drag’n’drop uploads, they can now automate model and data validation iteration.
Why choose xyzt.ai?
With the xyzt.ai platform, data analysts and researchers can optimize their workflow and use the APIs for data ingestion and data querying. At the same time they get access to a highly performant visual analysis interface that does not crumble with increasing data sizes.
Data connection – in a first step, the user creates a project and defines the data sources and data sinks. Data sources can be simple CSV files with columns defining the data attributes. Each column is defined by a data type that can be used during analysis and visualization. Data upload is then performed through a simple REST call, or drag’n’drop upload for quick validation. The entire pipeline from project creation, data ingestion, to visual dashboard generation can be automated through REST APIs.
Data analysis – the location data can then be analysed in the xyzt.ai platform or through extracting insights using API calls. Analysis is facilitated by a highly interactive and scalable Visual Analytics interface that allows hotspot analysis, deviation analysis, split screen analysis, filtering based on space, time, and attributes.
Collaboration – being a cloud solution, the xyzt.ai platform allows you to invite coworkers to join your projects and see your data and analysis insights from the comfort of their browser. This is especially powerful in times where remote work is increasing.
Insight reporting – reports with maps, timelines, dashboards can be created using the data and parameters set. These reports are interactive and allow further exploration and sharing with coworkers.
ROI FOR THE ANALYST/RESEARCHER
No more hassles with slow and unresponsive scientific plotting libraries. Instead, view and analyze the data in a fully interactive 2D/3D/4D Visual Analytics view.
Automate location data analysis workflows by scripting data ingestion and data analysis. Increasing your efficiency and model iteration throughput.
Disseminate your research results and analysis work with your team and audience in one common cloud-based platform.