The road to operational excellence:
As per Boeing, if you were to reduce the average turn-time of a point-to-point carrier from 40 to 30 minutes, it would increase aircraft utilization by 8.1%, scaling from 2,304 trips per year to 2,491 trips annually.
Metamorphosis of aircraft turnaround operations: Harnessing AI-enabled video analytics
AI-enabled video analytics is a major breakthrough in the aviation sector. By converting valuable ground-time to air-time, video analytics can help stakeholders maximize aircraft utilization, amplifying profits for airlines.
The roadmap to optimizing aircraft turnaround time
When considering actual operations, the turnaround schedule is more dynamic in nature. It needs to be adjusted based on the factors such as delay in aircraft arrival that may cause deviation from the original schedule.
A turnaround chart must feature a clearly outlined predefined critical path, which may be change over time based on the status of activities. For instance, the addition of a pit stop for fuelling to an aircraft’s original critical path due to the unavailability of the fuel track within a set time period.
Often times, airlines are unaware of the activities going on at the gate during the turnaround opertaions. Complete awareness of the tasks being performed at the gate and their status helps potential errors, and prevent delays via proactive actions – optimizing turnaround operations.
The role of AI-enabled video analytics in optimizing aircraft turnaround process
Unlike manually collected data, video analytics captures all turnaround activities in real-time, turning video stream into valuable structured data, facilitating proactive mitigation of potential delays. AI-enabled video analytics leverages existing CCTV infrastructure and ML algorithms to optimize turnaround operations.
- First, video feeds from the ramp area are captured for continuously monitoring activities like fuelling, jet bridge positioning, pushback, unloading baggage or cargo, etc.
- Then different activities are captured using video analytics with timestamps and are passed on to the decision engine
- The feed from the video analytics engine and the pre-defined turnaround schedule are compared, and then alerts or notifications are sent based on the situation
- These alerts/notifications are monitored to take preventive actions against potential delays
Maximize aircraft utilization, minimize turnaround time: Embrace video analytics
We at TCG Digital take care of everything with our end-to-end AI platform tcgmcube, helping you optimize aircraft turnaround operations and maximize profits. With a next-gen video analytics solution, we are delivering excellence and experience for all – airports, passengers, and ground handlers.
To know more about our AI-powered video analytics solution, write to us at email@example.com