NASA SBIR 2017 Solicitation

FORM B - PROPOSAL SUMMARY


PROPOSAL NUMBER: 17-2 A3.02-9118
PHASE 1 CONTRACT NUMBER: NNX17CA58P
SUBTOPIC TITLE: Autonomy of the National Airspace Systems (NAS)
PROPOSAL TITLE: Machine Learning of Multi-Modal Influences on Airport Delays

SMALL BUSINESS CONCERN (Firm Name, Mail Address, City/State/Zip, Phone)
The Innovation Laboratory, Inc.
2360 Southwest Chelmsford Avenue
Portland, OR 97201 - 2265
(503) 242-1761

PRINCIPAL INVESTIGATOR/PROJECT MANAGER (Name, E-mail, Mail Address, City/State/Zip, Phone)
Dr. Jimmy Krozel
Jimmy.Krozel@gmail.com
2360 SW Chelmsford Ave.
Portland, OR 97201 - 2265
(503) 224-5856

CORPORATE/BUSINESS OFFICIAL (Name, E-mail, Mail Address, City/State/Zip, Phone)
Michelle Camarda
Michelle.Camarda@gmail.com
2360 Southwest Chelmsford Avenue
Portland, OR 97201 - 2265
(503) 242-1761

Estimated Technology Readiness Level (TRL) at beginning and end of contract:
Begin: 2
End: 3

Technology Available (TAV) Subtopics
Autonomy of the National Airspace Systems (NAS) is a Technology Available (TAV) subtopic that includes NASA Intellectual Property (IP). Do you plan to use the NASA IP under the award?
No

TECHNICAL ABSTRACT (Limit 2000 characters, approximately 200 words)

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.

POTENTIAL NASA COMMERCIAL APPLICATIONS (Limit 1500 characters, approximately 150 words)
This work is fundamental to Air Traffic Management (ATM), and will naturally fit into ATM research being performed at NASA Ames and NASA Langley. It will likely be used in ATM research efforts, Trajectory-Based Operations (TBO) research, and in the SMART NAS system under development at NASA.

POTENTIAL NON-NASA COMMERCIAL APPLICATIONS (Limit 1500 characters, approximately 150 words)
Based on a partnership with Metron Aviation, plans are to include this SBIR software into products and services that Metron Aviation sells in the National Airspace System (NAS) as well as throughout the world.

TECHNOLOGY TAXONOMY MAPPING (NASA's technology taxonomy has been developed by the SBIR-STTR program to disseminate awareness of proposed and awarded R/R&D in the agency. It is a listing of over 100 technologies, sorted into broad categories, of interest to NASA.)
Air Transportation & Safety
Algorithms/Control Software & Systems (see also Autonomous Systems)
Analytical Methods
Condition Monitoring (see also Sensors)

Form Generated on 04-26-18 12:25