THIS SBIR SYSTEM IS A MACHINE LEARNING SYSTEM THAT USES A VERY LARGE DATABASE OF AIRSIDE AND LANDSIDE DATA…
Award details are derived from public USAspending.gov records. Not a bid recommendation.
Award details
- Award ID
- 80NSSC18C0167
- Contractor
- THE INNOVATION LABORATORY, INC.
- Awarding agency
- National Aeronautics and Space Administration
- Sub-agency / office
- National Aeronautics and Space Administration
- Award amount
- $750,000
- Period of performance
- May 18, 2018 – May 17, 2020
- NAICS
- 541715 — Research and Development in the Physical, Engineering, and Life Sciences (except Nanotechnology and Biotechnology)
- PSC
- PSC AR11
Public award description
THIS SBIR SYSTEM IS A MACHINE LEARNING SYSTEM THAT USES A VERY LARGE DATABASE OF AIRSIDE AND LANDSIDE DATA TO PREDICT PUSHBACK AND TAKEOFF TIMES OF AIRCRAFT AT A GIVEN AIRPORT. AIRSIDE DATA SOURCES DESCRIBE THE STATE OF THE SYSTEM AFTER TSA SECURITY SCREENING IS COMPLETE, AND INCLUDES INFORMATION ABOUT THE CREW AND PASSENGERS ARRIVING AT THE DEPARTURE GATE, TURNAROUND AND PUSHBACK PREPARATION, RAMP AND TAXIWAY MOVEMENT, AND AIRCRAFT ARRIVAL TO AND DEPARTURE FROM THE GATES. LANDSIDE DATA SOURCES DESCRIBE THE STATE OF THE AIRPORT PRIOR TO TSA SCREENING, INCLUDING TSA QUEUE LINE DELAYS, PASSENGER MOVEMENT THROUGH THE AIRPORT VIA CAMERAS, PARKING AVAILABILITY, ROAD TRANSIT DELAYS, CONGESTION, AND ACCIDENTS, AND WEATHER CONDITIONS. THESE DATA ARE USED TO CLASSIFY THE CURRENT DAY DATA USING CLUSTER ANALYSIS, AND TAKE OFF TIME AND PUSHBACK TIME PREDICTIONS ARE MADE BASED ON THE CLUSTER ANALYSIS RESULTS.
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