Minimum Viable Orbital Intelligence Nodes (MVOIN): A Framework for Economically Viable Space-Based Artificial Intelligence Infrastructure

This paper introduces the concept of the Minimum Viable Orbital Intelligence Node (MVOIN), a framework for evaluating the smallest economically and operationally viable artificial intelligence infrastructure that can be deployed in space. As artificial intelligence systems continue to scale, computational infrastructure is increasingly constrained by terrestrial limitations including power availability, thermal management, land usage, and infrastructure concentration. At the same time, advances in launch systems, orbital manufacturing concepts, autonomous operations, and space resource utilization are creating new possibilities for relocating portions of computational infrastructure beyond Earth. Rather than focusing on speculative civilization-scale orbital data centers, this work investigates a more fundamental question: What is the smallest orbital intelligence system capable of generating meaningful economic value while supporting future expansion? To address this question, the paper develops a systems-engineering framework that integrates artificial intelligence infrastructure, orbital mechanics, thermodynamics, power generation, radiative cooling, communications architecture, launch economics, and autonomous operations. The study introduces a classification system for orbital intelligence nodes ranging from Micro Nodes to Industrial Nodes and evaluates their mass, power, thermal, and economic characteristics. The paper further explores potential applications including satellite fleet operations, Earth observation intelligence, autonomous orbital maintenance, asteroid prospecting, space resource utilization, autonomous mining systems, and distributed orbital intelligence networks. Building upon these foundations, the work examines recursive growth pathways through which intelligence infrastructure may support industrial expansion, while expanding infrastructure increases available intelligence capacity. A central contribution of the paper is the concept of recursive infrastructure growth, where intelligence, infrastructure, resources, and economic value participate in mutually reinforcing feedback loops. This framework provides a pathway for understanding how relatively modest orbital intelligence systems could evolve into increasingly sophisticated industrial ecosystems and, eventually, components of future orbital economies. The study concludes with long-term horizon analyses exploring the evolution of orbital intelligence infrastructure over five-year, ten-year, twenty-year, and fifty-year timescales, as well as broader implications for planetary resilience, distributed economic systems, autonomous space industries, and interplanetary infrastructure development. The MVOIN framework is intended as a foundational research program and conceptual roadmap for researchers, engineers, entrepreneurs, policymakers, and space infrastructure developers interested in the future convergence of artificial intelligence and space-based industrial systems. -JSR

Authors

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-06-14
DOI
https://doi.org/10.5281/zenodo.20690829
Primary Topic
Space exploration and regulation
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Minimum Viable Orbital Intelligence Nodes (MVOIN): A Framework for Economically Viable Space-Based Artificial Intelligence Infrastructure

Prashant Prakash
Zenodo (CERN European Organization for Nuclear Research)
Space exploration and regulation
article

Minimum Viable Orbital Intelligence Nodes (MVOIN): A Framework for Economically Viable Space-Based Artificial Intelligence Infrastructure

Prashant Prakash
article en

Abstract

This paper introduces the concept of the Minimum Viable Orbital Intelligence Node (MVOIN), a framework for evaluating the smallest economically and operationally viable artificial intelligence infrastructure that can be deployed in space. As artificial intelligence systems continue to scale, computational infrastructure is increasingly constrained by terrestrial limitations including power availability, thermal management, land usage, and infrastructure concentration. At the same time, advances in launch systems, orbital manufacturing concepts, autonomous operations, and space resource utilization are creating new possibilities for relocating portions of computational infrastructure beyond Earth. Rather than focusing on speculative civilization-scale orbital data centers, this work investigates a more fundamental question: What is the smallest orbital intelligence system capable of generating meaningful economic value while supporting future expansion? To address this question, the paper develops a systems-engineering framework that integrates artificial intelligence infrastructure, orbital mechanics, thermodynamics, power generation, radiative cooling, communications architecture, launch economics, and autonomous operations. The study introduces a classification system for orbital intelligence nodes ranging from Micro Nodes to Industrial Nodes and evaluates their mass, power, thermal, and economic characteristics. The paper further explores potential applications including satellite fleet operations, Earth observation intelligence, autonomous orbital maintenance, asteroid prospecting, space resource utilization, autonomous mining systems, and distributed orbital intelligence networks. Building upon these foundations, the work examines recursive growth pathways through which intelligence infrastructure may support industrial expansion, while expanding infrastructure increases available intelligence capacity. A central contribution of the paper is the concept of recursive infrastructure growth, where intelligence, infrastructure, resources, and economic value participate in mutually reinforcing feedback loops. This framework provides a pathway for understanding how relatively modest orbital intelligence systems could evolve into increasingly sophisticated industrial ecosystems and, eventually, components of future orbital economies. The study concludes with long-term horizon analyses exploring the evolution of orbital intelligence infrastructure over five-year, ten-year, twenty-year, and fifty-year timescales, as well as broader implications for planetary resilience, distributed economic systems, autonomous space industries, and interplanetary infrastructure development. The MVOIN framework is intended as a foundational research program and conceptual roadmap for researchers, engineers, entrepreneurs, policymakers, and space infrastructure developers interested in the future convergence of artificial intelligence and space-based industrial systems. -JSR

Zenodo (CERN European Organization for Nuclear Research)
Industry, innovation and infrastructure
Openalex Percentile: Top 6%
Space exploration and regulation
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.