SBIR-STTR Award

Intelligent Information Processing for Enhanced Safety in the NAS
Award last edited on: 2/20/2018

Sponsored Program
SBIR
Awarding Agency
NASA : ARC
Total Award Amount
$841,774
Award Phase
2
Solicitation Topic Code
A3.03
Principal Investigator
Richard Jessop

Company Information

Metis Technology Solutions Inc

2309 Renard Place Se Unit 200
Albuquerque, NM 87106
   (505) 299-1509
   info@metis-tech.com
   www.metis-tech.com
Location: Single
Congr. District: 01
County: Bernalillo

Phase I

Contract Number: ----------
Start Date: ----    Completed: ----
Phase I year
2016
Phase I Amount
$94,264
We propose a system that focuses on how improved information flow between agents acting in a flight deck environment can improve safety performance. Agents are defined as either human, computational, or hardware that can act on information. Information that can flow to an agent is filtered based on priority. This protects human agents from information glut and information overload and reduces bandwidth requirements on communications channels. Agents react to the presented information by accepting it, discounting it, or querying the system for more information. All decisions and actions are recorded and modeled by the system in order to verify correct and efficient processing of information.The proposed system will operate independently of flight deck systems but will have access to required information sources. It will not impose an additional monitoring responsibility on the flight crew except for when safety issues surface. At that point, the flight crew's attention is captured and then predefined, prioritized information is presented in a selected format.The proposed system consists of the major software components: the Metadata Workbench, the Condition Monitor, and the Notification Terminal. The Metadata Workbench is used to identify all agents, roles, conditions of interest which trigger information flows, and information with associated context and priority. The notification mechanism, the information flow's destination, and the format for reporting information along with justification is also defined by the workbench. Condition monitors serve as the interface between information-producing systems and notification terminals. Conditions of interest along with all information metadata are deployed to the condition monitors. The notification terminal receives prioritized information and presents the information in the predefined format.

Phase II

Contract Number: ----------
Start Date: ----    Completed: ----
Phase II year
2017
Phase II Amount
$747,510
Our Phase I work focused on how improved information flow between actors in a flight deck environment can improve safety performance. An operational prototype was developed demonstrating how the Intelligent Information Processing System (IIPS) will operate in actual accidents/incidents.For Phase II, we propose the following operating environment extensions from the flight deck environment: NextGen scenarios emphasizing interactions with air traffic controllers operating in fast paced, increased volume of manned and autonomous traffic; UAV operations emphasizing introduction of UAVs into the NAS, transition to autonomy and fully autonomous operations; and IIPS in flight training environments both simulated and airborne. We also propose an extension to the manner in which conditions were developed in Phase I. Conditions were developed using post analysis of accidents and incidents. The error chain of events was identified, information necessary to prevent the event was identified, and finally, a condition developed that detected the circumstances for a possible safety failure so that a notification could be transmitted to the actor who would then take the appropriate action to break the error chain. This paradigm of condition development can be characterized as reactive. With the NAS moving into a state of flux with the integration of UAVs and general increased traffic volume, reactive safety may not be acceptable. In order to continue the steadily improving safety record of aviation, a more proactive approach must be considered. We propose the use of a classical rule-based expert system and other artificial intelligence approaches that can make inferences of possible unsafe conditions using a temporal knowledge base populated by propositional statements generated by IIPS information sources.