Optimal turnarounds are based on time-sensitive indicators that ApronAI helps monitor and predict deviations, read more about them in our Glossary

A turnaround is a complex operation that involves several airport stakeholders working together to have the aircraft ready on time. The calibrated process behind the art of the turnaround is based on time-sensitive indicators. Arriving late ultimately affects the entire operations, leading to increased costs, delays, grounded flights, and unhappy passengers. Thankfully, technology allows continuous monitoring of turnarounds and detection of anomalies, contributing to increased efficiency.

We’ve compiled a glossary of the most important indicators for an optimal turnaround. Find out how Assaia considers them when using computer vision, machine learning, and predictors to help airports, airlines, and ground handlers achieve faster turnaround times.


Estimated In-Block Time (EIBT) is the estimated time that an aircraft will arrive in-blocks. EIBT is equivalent to ETA (Estimated Time of Arrival), used by airlines and ground handlers. When knowing the Estimated Taxi-In Time (EXIT), added to the Estimated/Actual Landing Time (ELDT), operations can calculate an accurate EIBT. Pre-departure sequencing, ground handling resource management, and stand and gate planning are all dependent on it.

EIBT is used in ApronAI as a parameter for customizable alerts, allowing operations to look beyond the turn and ensure the clearness of the stand before the turnaround time.


Scheduled Off-Block Time. The time that an aircraft is scheduled to depart from its parking position, to taxi-out, or to be pushed back. It is the main indicator for an airport slot and also marks the final stages of the turnaround for the stand to clear up for the succeeding turn. Without the allocated and approved SOBT, the value of TOBT cannot be determined, meaning the flight will not appear in the departure sequence of the A-CDM (collaborative decision-making at airports).

For ApronAI, SOBT is an important indicator that lies in all efficiency calculations and helps in predicting possible delays.


Estimated Off-Block Time. This indicator is taken into consideration once the aircraft has parked at the gate. As an estimate of when the push-back or taxi-out will be commenced, it helps to plan the time the aircraft will be on ground and use the airport infrastructure for the turnaround. Added to the Estimated Taxi-out Time (EXOT), the Estimated Take-off Time (ETOT) can be calculated to optimize the flow and capacity management of air traffic. Any change of more than 15 minutes to the EOBT of a filed flight plan has to be communicated.

Assaia records the initial EOBT together with the changing EOBT parameter in case of delays or adjustments, allowing to track discrepancies and get notified at an early stage.


TOBT (Target Off-Block Time) represents the estimated time for the aircraft to be ready, with doors closed, jetbridge removed and push-back available. TOBT is mostly used for airlines to calculate the TSAT (Target Start-up Approval Time) as TOBT-30 minutes onwards. Once the aircraft is ready to start-up (ASRT, Actual Start-up Request Time) and has received clearance to do so, the push-back will start. If the tolerance of ± 5 minutes is not met, the TOBT will be updated and will affect the EOBT.


POBT (Predicted Off-Block Time) is an AI-powered prediction of when the aircraft is going to leave the stand. Applied in all of Assaia’s solutions, it analyzes various available sources, such as real-time and historical flight data, video streams, weather conditions, and internal airport operations, to determine an accurate prediction for the off-block time. POBT is compared to SOBT at every stage of the turnaround. As soon as a deviation in expected procedures is detected, the Ops are alerted to proactively take measures. This makes it possible to anticipate the AOBT (Actual Off-Block Time) and conduct operations that are better organized.


TTOT (Target Take-off Time) defines the time at which the aircraft will be ready to take off, based on the TOBT or TSAT and the variable taxi time to the assigned runway. With an accurate TTOT, airports monitor departure queues and clear outbound flights for take-off.

Being informed about the scheduled and actual time indicators, necessary for both airport and flight operations, helps Assaia’s clients optimize their turnaround times. Get in touch with us to  empower your airside operations with cutting-edge technology.


We are pleased to partner with Assaia to implement the ApronAI Turnaround Control solution at T4. This new solution will not only optimize operations and our work with our business partners, but will also help us to ensure a first-class customer experience at T4.

Roel Huinink
President and CEO, JFKIAT

For most airports, the apron is a a black box. Assaia finally gives our ground staff full insight into every turnaround. This allows them to focus on what really matters, while simultaneously making the work environment safer.

Jason Aspelund
Former Manager Strategic Performance, Alaska Airlines

The real-time and historical insights that can inform both airport and airline operations make this solution a clear winner for everyone.

Craig Paul
Director of Technology & Innovation , Halifax Stanfield International

Assaia's product allows airports and airlines to collect, track, and analyze data in real time; this innovation removes inefficiencies and optimizes performance.

Jim Lockheed
JetBlue Ventures

We’re creating the airport of the future, and innovation in apron operations will directly improve the passenger experience. We are laser focused on innovations that will make Pearson and its whole apron ecosystem more efficient while reducing our carbon footprint.

Deborah Flint
President and CEO GTAA

This data provides the single source of truth covering all turnaround operations. It is, therefore, an integral part of our Airport Collaborative Decision-Making initiative.

Darin Juby
Program Director, Digitalization, GTAA

SEA needed an innovative solution to our capacity problem and have worked with Assaia to optimize the turnaround process resulting in reduced taxi times and increased passenger satisfaction. Assaia has exceeded our expectations, consistently delivering on-time & on-budget.

Samer Tirhi
Airline Scheduling Coordinator, Seattle-Tacoma International Airport

With the help of Predicted Off Block Time from Assaia. JFKIAT Operations can be proactive to reduce or eliminate any delays and gate holds

Stephen Tukavkin
VP IT & Digital, JFKIAT

I had mentioned before, great innovation on your part. With these types of improvements, T4 is always leading at JFK. Thank you

COPA Station Manager

We are proud to be partnering with the Assaia team in our mission to use technology to improve the efficiency and safety of the airport environment.

Raghbir S. Pattar
Director of Airports Transformation, IAG

We’re working hard on becoming an airport of the future, and this involves rethinking every part of our ground operations. Assaia’s ApronAI is an integral component of our vision for the ramp of the future.

Abhi Chacko
Head of Innovation & Commercial IT Services, Gatwick Airport

Assaia’s technology adds critical data points to CVG’s early-stage neural network for operational advancements. Structured data generated by artificial intelligence will provide information to make decisions, optimize airside processes, and improve efficiency and safety.

Brian Cobb
CIO, CVG Airport


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