Artificial Intelligence for Apron Operations - Miami - Florida March 2021

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Artificial Intelligence for Apron Operations - Miami - Florida March 2021
Artificial Intelligence for Apron Operations
Miami - Florida
March 2021
Artificial Intelligence for Apron Operations - Miami - Florida March 2021
Arrival readiness

Before the pandemic impacted flight volumes, our customer was reporting industry-leading dependability statistics to the DOT; in 2019, 79.5% of the flights
arrived on-time (system-wide) while at one of the company’s primary airports, Fort Lauderdale (FLL), the arrival performance was 79.9% for the same
period. “Air carrier delay”, and “Aircraft arriving late” were the major contributors to on-time deterioration, and these two are controllable by the carrier.

                        Synaptic Aviation Customer – All flights system-wide     Synaptic Aviation Customer –

Placing focus on what the teams can control, increases the probability of reducing avoidable delays. An effective way to positively impact performance is by
eliminating arrival disruptions. According to the Bureau of Transportation Statistics, in the month of February of 2020, 61 of our customer’s flights landed in
FLL well ahead of schedule, however they still arrived late to the gate incurring in a DOT reportable delay (A+14). These flights fall in the “Aircraft arriving
late” category however a late gate assignment, safety envelope obstructions, ground crew readiness, etc. could be the real cause of the delay, and these
steps are in control of the airline. Not coincidentally, the Ai system issued 37 aircraft hold alerts (gate crew not ready) in that same month at just one gate.

Synaptic Aviation installed its ROOT platform (AI based Ramp Operations Optimization Tool) at Gate G13 in February of 2020 and by mid-year it rolled out
the system to two additional gates (currently expanding to 10). The impact on arrival readiness was immediate and it has been sustainable:
Artificial Intelligence for Apron Operations - Miami - Florida March 2021
As previously mentioned, gate G13 was experiencing 37 aircraft hold events per month or 17% of the total arrivals when the system was first installed. A
June-December analysis demonstrates that hold events have stabilized at 3% (holds/flights) and total idle time has been cut by 78%. Most events are
avoidable, with crews not ready to receive the aircraft, safety envelope obstacles present, and not fully retracted PLBs as the primary drivers. The system’s
aircraft hold detection combined with the real-time alerts have played a critical role in keeping the front-line teams focused.

Synaptic Aviation’s aircraft hold mitigation produces $46K in savings per gate per year when applying DOT form 41 calculated cost per minute of block,
$74.24/minute (please refer to Appendix 3). Total annual benefit is calculated at a rate of 7 arrivals per day per gate. This calculation excludes other
collateral impact like crew duty time expiration, misconnecting passenger expenses, etc.
Artificial Intelligence for Apron Operations - Miami - Florida March 2021
Passenger loading bridge attachment delays (PLB A+3).

Another area of improvement is the timely connection of the passenger loading bridge upon arrival. After installing the Ai ROOT solution, Synaptic Aviation
detected numerous flight arrivals where an aircraft was on hold for several minutes before the telescopic bridge approached and attached to the airplane. In
collaboration with our customer’s airport leadership teams, real-time alerts were set at A+3 (three minutes post-arrival) to alert the passenger service team
of arriving flights that were parked at the gate waiting more than 3 minutes for the PLB to connect. The results have been remarkable when compared to
the PLB connection performance observed prior to the alerts being sent. The alerts were activated on December 28th.

Gate G12 PLB A+3 performance improvement - December 2020 – February 2021

                                                                                                                                       Gate G12
                                                                                                                                  PLB A+3 Delay Trend
                                                                                                               30
                                                                                                                                                  31                          30
                                                                                                               25            30

                                                                                                               20                                                             25

                                                                                                               15
                                                                                                                                                                              20
                                                                                                               10
                                                                                                                                                                              15
                                                                                                                        24                   13                       5
                                                                                                                5

                                                                                                                0                                             10              10

                                                                                                                     December          January                     February

                                                                                                                                    Delays             Idle time

Mitigation of PLB A+3 delays have also resulted in improved customer service. In repeated occassions a passenger loading bridge delay is also associated to
an aircraft hold delay, stealing valuable minutes from the turnaround time.

Hundreds of PLB attachment observations demonstrate that skilled and ready PLB agent-drivers can attach the bridge in 1.1 minutes post-arrival. An A+2
mark may be a more suitable benchmark which yields additional savings if alerts are set at 2 minutes post arrival. This can also highlight agent training
needs and potentially avoid a future aircraft damage.
Artificial Intelligence for Apron Operations - Miami - Florida March 2021
Gate G13 PLB A+3 performance improvement - December 2020 – February 2021

Gate G14PLB A+3 performance improvement - December 2020 – February 2021
Artificial Intelligence for Apron Operations - Miami - Florida March 2021
Savings calculated using DOT Form 41, cost per minute of Block time at $74.24 (See Appendix 3)

Pic.1 – Aircraft blocking-in at 7:37pm                                      Pic.2 – Aircraft awaiting PLB at 7:43pm (6mins – one engine running)
Artificial Intelligence for Apron Operations - Miami - Florida March 2021
Ground Services GPU – PCA (Ground Power and Air Conditioning)

Added capabilities to the Ai system include the ability to track GPU and PCA connections. Not only does the system help with improving the response time of
the crews on the ground but it also creates a renewed emphasis in turning off APU units.

Chart 1. G14                                      Chart 2. G13                                        Chart 3. G14

Charts 1 through 3 reflect how the ground crew’s response time has been reduced across all gates as a result of increased awareness, and in response to
the PLB A+3 alerts, since the gate provided GPU/PCA units are connected to the aircraft until the PLB has been fully attached. When combined, the three
gates show an 18% improvement in response time, shortening the average connection time from A+4.3 minutes in November to A+3.6 minutes in February.

Another area of improvement is the percentage of ground time that the aircraft is supported by ground services, which improved consistently from 75% in
November to 82% in February. This implies that the aircraft’s APU can be turned off earlier and stay off for a longer period, saving jet fuel and equipment
hours. By releasing transparent operational statistics that are available in real-time the crews can have a sense of achievement while monitoring
performance.

Airport Fees for GPU and PCA provided are also an area of substantial benefit with the use of Ai. The system quickly identifies when the services are not
connected and can help with determining when airport provided services are not available. The searchable video database immediately provides evidence of
those instances so that the invoices for airport charges can be audited to make sure that the airline only pays for services rendered.

The overall benefit of GPU-PCA monitoring is estimated to be at $30K per gate per year considering APU fuel burn and APU maintenance-usage under a
power by the hour agreement (according to Honeywell’s APU statistics for A320 type aircraft).
Artificial Intelligence for Apron Operations - Miami - Florida March 2021
Automated timestamps are helpful to monitor GPU and PCA connections and to cross-reference against APU usage from the ACARs reports; they can also
facilitate the task of identifying airport equipment failures to seek reimbursement of airport charges that have been invoiced but not provided.

Chart 3. Automated timestamps - extracted from Ai system                       Chart 4. OAG flight information - flight tracker.com
Artificial Intelligence for Apron Operations - Miami - Florida March 2021
Picture 3. GPU connection – Flight 425 – Feb 16                                     Picture 4. PCA connection – Flight 425 Feb 16

Searchable video database:

Often an image can help with resolving a dispute or provide insight into an ongoing investigation. The system’s ability to provide video clips in real-time
expands the possibilities of what can be accomplished. Our customer has benefited from this capability; Synaptic Aviation’s prompt response to Ad Hoc
requests providing real-time videos that are relevant to every situation helped eliminating ambiguity by providing a single source of truth. The searchable
database is accessible in seconds and the ability to search by keyword speeds up the results in a way not available before.

Picture 5. Key word search for “GPU connection” on February 16th – Gate G14.
Artificial Intelligence for Apron Operations - Miami - Florida March 2021
Timestamps to measure turnaround performance in real-time.

The automated detection and tracking of key objects allow the Ai system to create a real-time log of events as ground services are being provided. Synaptic
Aviation’s ROOT system posts activity timestamps and collects data which can provide insightful information about the operation. Our customer is
empowered now at FLL to find the root cause of delays, prevent events from repeating or help front-line teams identify systemic disruptions in a way that is
unbiased and objective.

Chart 5. Turnaround timestamps at Gate G12

Synaptic Aviation can work with the airline customer to provide a data feed from logged Ai timestamps to existing airline systems or create dashboards that
support decision making in the moment as the airline operates. The volume of data generated can easily be used to develop predictive models and prevent
or mitigate common operational disruptions.

To increase the versatility and efficacy of the data generated by the Ai, we can obtain flight information data from the airline’s systems and add flight
number, aircraft tail number, etc., so that various groups within the company can benefit from the information.
Summary of economic benefits

*Summary of additional benefits

   •   24/7 unbiased Ai monitored operations      - Elevated awareness. Deliver on-time arrivals and departures.
   •   Real-time video database                   - Auditing, safety, and security.
   •   System alerts with real-time images        - Safety, training, improved vendor performance (SLAs).
   •   Turnaround automatic timestamps            - Turnaround performance and delay root cause identification.
   •   Raw activity metadata                      - Build insightful dashboards and develop predictive models.
   •   Invoice accuracy – auditing                - Automatic auditing of airport charges to eliminate errors and overbilling.
   •   Reduce CO2 emissions                       - Meet CORSIA goals faster with the help of tracking of efficiencies.
   •   Reduced incidents – injuries and SK time   - Ai monitoring of cameras produce sustainable behavior change.
   •   Potential insurance premium reductions     - The system can demonstrate increased operational safety and risk mitigation.
Appendix 1 – Additional benefits
Elevated safety and ground crew awareness

Synaptic Aviation has incorporated several safety enhancing features into its ROOT system including the identification and warning about obstacles inside
the safety envelope and alerting about a passenger loading bridge not fully retracted (protruding into the safety envelope). This feature is already saving our
customer from potential aircraft damage and employee injuries. Routine ground operations lead experienced ramp workers to get overconfident about
aircraft servicing procedures. Complacency and deviating from established safety protocols often result in aircraft damages and employee injuries. The
Flight Safety Foundation estimates aircraft damage on the ground to exceed $10 billion a year for the airline industry.

Picture 6. Actual safety envelope alert on January 18th-2021 at Gate G13.
Environmental leadership

ICAO and the large international carriers jointly embarked on an initiative to reduce CO2 emissions under the Carbon Offsetting and Reduction Scheme or
CORSIA. Under CORSIA, international flights are required to monitor, report, and verify (MRV) CO2 emissions, with its pilot phase starting in 2021. Synaptic
Aviation’s ability to accurately monitor efficiencies versus a baseline can be used as an effective tool for reporting the airline’s progress towards the goal.

From the time Synaptic Aviation started monitoring ground operations at FLL we have calculated a reduction of Carbon emissions by 135 Tons. This figure is
calculated from the combined benefit of aircraft hold mitigation, PLB hold event reductions and the APU / GPU usage optimization over a 6-month period
for gates G12 and G14 and 12 months for gate G13.

Picture 7. ICAO CORSIA initiative for international aviation.
Appendix 2 – System capabilities

                                                            Ramp Operations Optimization Tool

                 Object ID                    Core   Plus       Object tracking with time-stamps            Core Plus                Alerts              Core Plus
Safety envelope perimeter                      X            Safety envelope large obstacle tracking          X          Envelope clear                    X
Aircraft detection                             X            Aircraft Approaching - stationary - departing    X          Aircraft holding short of gate    X
Ground personnel                               X            Ground crew present - absent                          X     Ground crew present*                   X
Passenger loading bridge (PLB)                 X            PLB extending - attached - retracting            X          PLB A+x connect time              X
Belt loader                                    X            Beltloader attached - detached                   X          Off-load delay                         X
Pushback truck                                 X            Pushback truck arriving - present - departing    X          Pushback truck alert                   X
High-lift truck (catering - cabin cleaning)    X            High-lift truck attached - detached              X          Catering truck presence alert          X
Tow-bar                                        X            Towbar attached - detached                            X     Towbar connected                       X
PCA hose                                       X            PCA hose connected - diconnected                 X          PCA connected - disconnected           X
GPU cable                                      X            GPU cable connected - disconnected               X          GPU connected - disconnected           X
Aicraft chocks                                 X            Chocks on / off                                  X          Chocks on / off
Tugs and service vehicles                      X            Service vehicle presence                              X     Service vehicle alerts                 X

Baggage                                        X            Bagage loading - offloading                           X     Off-load delay                         X
Jet engine                                     X            Jet engine                                            X     Jet engine                             X
Fueler                                                X     Fueling servce started - finished                     X     Fueling service                        X

* Requires gate assignment feed and FLIFO
Appendix 3 – Cost per minute of block time – A4A (DOT Form 41)
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