AI-Enhanced Mission Operations Reporting & Decision Support System
Description
NASA's Mission Control currently relies on a manual CHIT (Mission Action Request) system for real-time operational decisions, a process that places a high cognitive load on flight controllers who must complete forms, identify all stakeholders, and search historical data with basic tools, making it difficult to spot subtle trends. This use case proposes transforming this system by integrating an AI engine to streamline operations.
Detailed example
context-aware smart search results
AI / analytics pattern
Natural Language Processing: AI that processes, interprets, and shares information in human language.
Automation level / stage
a) Pre-deployment – The use case is in a development or acquisition status.
Expected benefit
The proposed solution would leverage Natural Language Processing (NLP) to enable controllers to initiate CHITs using plain language, while machine learning models would proactively analyze data to identify emerging trends and provide context-aware smart search results from historical mission data. Additionally, the AI would perform an initial automated impact assessment on new requests, flagging potential risks to enhance the speed and safety of decision-making.
Controls / human review
ATO: Not reported; PIA: Not published