Hybrid On-Board and Ground-Based Processing of Massive Sensor Data (HyspIRI IPM)
National Aeronautics and Space Administration · JPL: Jet Propulsion Laboratory
Overview
- Development stage
- In development or acquisitionSource: a) Pre-deployment – The use case is in a development or acquisition status.
- High-impact designation
- Not high-impactSource: c) Not high-impact
- Impact justification
- Not reported
- Start date
- Not reported
- Withheld from public reporting
- NoSource: a) No
Mission
- Topic area
- Science
- Operational functions
- No function tag matched Derived by keyword rules; see methodology
Problem the AI is intended to solve
Future space missions will enable unprecedented monitoring of the Earth's environment and will generate immense volumes of science data. Getting this data to ground communications stations, through science processing, and delivered to end users is a tremendous challenge. On the ground, the spacecraft's orbit is projected, and automated mission-planning tools determine which onboard-processing mode the spacecraft should use. The orbit determines the type of terrain that the spacecraft would be overflying—land, ice, coast, or ocean, for instance. Each terrain mask implies a set of requested modes and priorities.
Expected benefits
Future space missions will enable unprecedented monitoring of the Earth's environment and will generate immense volumes of science data. Getting this data to ground communications stations, through science processing, and delivered to end users is a tremendous challenge. On the ground, the spacecraft's orbit is projected, and automated mission-planning tools determine which onboard-processing mode the spacecraft should use. The orbit determines the type of terrain that the spacecraft would be overflying—land, ice, coast, or ocean, for instance. Each terrain mask implies a set of requested modes and priorities.
System outputs
onboard-processing mode the spacecraft should use
Technology
- AI classification
- Agentic AISource: Agentic AI: AI systems that perform tasks or make decisions autonomously with minimal human intervention.
- System name(s)
- Not reported
- Custom-developed code
- Not reported
- Public source code
- Not reported
Sourcing
- How it was built
- Not reported
- Vendor (as reported)
- Not reported
- Vendors (standardized)
- None on the standard list
A vendor is the supplier named by the agency. It does not identify the underlying model or AI technology.
Data and privacy
- Involves PII
- Not reported
- Privacy Impact Assessment
- Not reported
- Authorization to Operate
- Not reported
- Demographic features
- Not reported
- Training and evaluation data
- Not reported
- Federal Data Catalog
- Not reported
Governance
0 of 8 minimum-practice questions answered. A blank answer means the agency reported nothing; it does not mean the practice is absent.
Potential impacts and how they were identified
Not reported