Advanced Air Mobility (AAM) is set to scale rapidly across dense, urban airspace, but this shift hinges on a critical foundation: effective digital data management. Autonomous flight systems require continuous access to high-fidelity, real-time data for predictive and adaptive capabilities. Without robust data infrastructure, safe and scalable AAM operations cannot exist.
Specialized Data Requirements for AAM
AAM relies on a large volume and wide variety of real-time, high-integrity data to operate safely, making effective data management a central component of its success. Instead of relying on human pilots to make real-time decisions and voice coordination with Air Traffic Control (ATC), autonomous systems must process this constant flow of high-quality data to maintain the same situational awareness. Delegating routine and monotonous tasks to these data-driven systems will allow humans to focus on overall oversight and reduce the likelihood of errors when AAM scales.
Beyond traditional aviation data like NOTAMs, weather, surveillance, and airspace constraints, AAM requires specialized information including microweather, turbulence predictions, infrastructure status, and vertiport availability. For example, an eVTOL flying above downtown needs precise data on wind conditions between buildings. If low-level wind shear is detected, the aircraft needs to autonomously reroute without human intervention. These kinds of capabilities are essential for high-tempo operations where decision quality directly correlates with data quality.
Principles of Effective Data Management
To create a truly safe and scalable ecosystem, digital data management should adhere to key principles:
- Standardization: Standardized data format and exchange protocols enable ecosystem-wide interoperability and cohesion.
- Governance: Clear rules must dictate data ownership, access, retention, update frequency, and quality assurance to ensure all entities maintain system reliability.
- Security: Operational decision-making systems require protection through encryption and zero-trust architecture.
- Performance-Based Approach: Setting clear expectations for data safety, reliability, and integrity encourages innovation in meeting thresholds without compromising safety.
Orchestrating Data Exchange Across the AAM Ecosystem
The future of autonomous flight hinges on a robust, standardized, and secure data foundation. As a Third-Party Service Provider (TSP), SkyGrid delivers an interoperable system that manages complex low-altitude operations at scale.
Our platform ingests diverse data types and makes them usable at a single point for multiple stakeholders. Through secure exchanges, SkyGrid enhances situational awareness, supports automated decision-making, and improves coordination among aircraft, operators, vertiports, and ANSPs.
SkyGrid’s algorithms interface with changing data sources while maintaining consistent outputs, regardless of the supplier. All data is protected through transit and within internal systems, enabling the assurance levels required for late-stage IFR operations and Automated Flight Rules (AFR) operations.
By developing APIs and data service frameworks collaboratively, ecosystem-wide visibility into emerging standards is prioritized. SkyGrid is leading the way in building the essential digital infrastructure for data management and interoperability—foundations that make autonomy safe, scalable, and real.