Assaia has launched StandManager, an AI-based resource management platform designed to automate aircraft stand and gate allocation using real-time operational data. The system aims to improve airport capacity utilization and operational efficiency as global passenger traffic grows and infrastructure constraints intensify.
Assaia has unveiled StandManager, a new artificial intelligence-based Resource Management System designed to optimize aircraft parking and gate allocation at airports. The platform uses continuously updated operational data to determine where aircraft should be positioned and how long they should occupy stands, replacing traditional planning methods that rely on fixed buffers and static schedules. According to the company, the system evaluates real-time flight conditions and operational signals to predict variations such as early arrivals or delays. By dynamically recalculating stand allocations and time buffers, the technology allows airports to adapt gate assignments automatically as circumstances change.
Assaia, a technology company specializing in AI-powered turnaround optimization for airports and airlines, focuses on improving ground operations through data analytics and computer vision systems. StandManager has been designed to complement the company’s ApronAI platform, which monitors aircraft turnaround activities and forecasts milestones including off-block departure times.
The solution is being developed in collaboration with Transformers Group, a technology provider known for open-architecture resource management systems used in aviation infrastructure. As passenger traffic increases and airport infrastructure remains constrained in many regions, more airports are exploring digital tools to manage ground operations more efficiently. Systems that integrate predictive analytics with operational planning can reduce delays, improve stand utilization, and enhance coordination between airlines, airport operators, and ground handling services. For airport operators and aviation investors, the adoption of AI-enabled resource management platforms signals a broader shift toward automation and data-driven infrastructure management across the global aviation sector.
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