Optimize Airport Operations with Machine Learning and Artificial IntelligenceUsing Artificial Intelligence and Machine learning to optimize Aiport operations and to enable all Airport types to benefit from the Airport Collaborative Decision Making (A-CDM) concept. Solutions tailored to Airport Operators' requirements and Airport size.
The Advanced ATC TWR concept is a scalable solution that enables all types of airports to improve throughput and predictability, and manage resource allocation efficiently by implementing 4 Airport Collaborative Decision Making (A-CDM) steps. This is done by sharing information between stakeholders and taking shared decisions to manage potential disruptions.
The Full Airport CDM is a solution that enables all types of airports to improve throughput and predictability, and manage resource allocation efficiently. Going beyond the A-CDM steps and ICAO guidance on A-CDM and ASBU recommendations with a real operator’s perspective, AirportKeeper® enables information sharing and taking shared decisions to manage potential disruptions. AirportKeeper® Full Airport CDM provides aggregated views of the status of the operational activities based on real-time data and estimation of timing through Artificial Intelligence and Machine learning algorithms.
AirportKeeper® Total Airport Management (TAM) brings together Airport operators along with all stakeholders, including aircraft operators, airport authority, the ANSP and ground handling agents in order to monitor and guide landside and airside operations jointly to ensure convergence. Using the right demand and capacity DCB tools and data to develop an Airport Operations Plan (AOP), stakeholders use proactive management methods and are able to work together to deal with emerging situations before they become problems.
Harnessing ML for Advanced Accuracy and Operational Savings: Innov’ATM Garners Additional Predictive Times Using FlightAware Foresight
1 - The A-CDM concept...
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