EUROPE’S LARGEST SMALLSAT CONFERENCE

May 26-28, 2026 | RAI, Amsterdam

Register Here!

Paper Category: AI/ML in Satellite Data Missions

  • Enabling Software-Defined Satellites with Edge AI

    Software-Defined Satellites (SDSs) enable spacecraft to evolve on orbit through software, moving beyond fixed-function architectures toward adaptable, multi-mission platforms. Software-defined radios and reconfigurable sensors and onboard compute systems provide foundational flexibility, while the integration of artificial intelligence at the edge is critical to achieving true operational autonomy. This presentation examines how AI-enabled onboard processing allows…

  • Evaluation of Heterogeneous Data Fusion for Real-Time Agricultural Stress Monitoring in Small-Scale Farming Ecosystems

    Smallholder agricultural systems represent a critical frontier for climate resilience strategies, yet they are often underserved by traditional remote sensing frameworks due to fragmented land parcels and low-frequency reporting. This research investigates an autonomous geospatial framework designed to synthesize multi-source satellite data, specifically Sentinel-2 MSI optical imagery and CHIRPS precipitation datasets, to detect and characterize…

  • Semi-Autonomous Reconnaissance Satellite: A Laboratory Demonstration of End-to-End On-Board Mission Autonomy

    Real-time satellite responsiveness to user requests from the field remains largely unavailable in current space systems. Such capabilities are typically restricted to low-altitude airborne platforms, primarily due to limited satellite communication bandwidth, intermittent ground contact, and the reliance on ground-based mission planning. Enabling true responsiveness requires a paradigm shift toward highly autonomous satellites, in which…

  • Quantized AI Inference on Constrained Embedded Platforms for Small-Satellite Settings

    In resource-constrained small-satellite settings, AI inference can operate under tight size, power, and payload budgets, which tend to limit onboard compute capability and data handling. These conditions motivate establishing a clear baseline for quantized AI inference under bounded compute and memory resources. To instantiate this baseline, a representative embedded-vision neural-network workload serves as the reference…

  • In-Orbit Experimental Validation of Autonomous Operations within the AIX Satellite-as-a-Service Framework

    As Low Earth Orbit (LEO) constellations continue to scale, traditional ground-centric operational paradigms struggle to meet increasing demands in latency, flexibility, and operational cost. The AIX (AI-eXpress) mission series addresses these limitations by introducing a service-oriented satellite architecture that enables dynamic in-orbit resource usage and application deployment. This paper presents the in-orbit experimental activities performed…

  • Catalysing Next Generation Solutions with Scalable Model-Based Software

    Small satellite missions increasingly rely on software-defined payloads, onboard data processing, and automated mission operations, to meet performance, responsiveness, and cost constraints. In practice, payload software development, integration and test (I&T) and operations are often supported by fragmented toolchains spanning flight, ground, and payload domains, leading to duplicated effort, reduced reusability and increased operational risk.…

  • Intelligent Orchestration for Hosted Payload Architectures in Satellite-as-a-Service Missions

    The rapid growth of the “Satellite-as-a-Service” market and the rise of In-Orbit Demonstration/Validation (IOD/IOV) missions have accelerated the demand for flexible hosted-payload architectures. Integration of third‑party payloads onto a host bus introduces complex challenges in resource contention, interface standardization, and operational risk management. Traditional integration of third‑party payloads onto a host bus suffers from resource…

  • An ML-Driven Mission Planning Pipeline for SmallSat Radiation Mitigation

    As the democratization of space increases the number of amateur and university-led SmallSat missions, there is a growing need for accessible mission planning tools that simplify complex orbital mechanics and the impact of space weather on spacecraft. A critical parameter for mission longevity is the Earth’s magnetotail; a region on the night-side of the Earth…

  • AI-Based Navigation for Lunar Satellites in VLLO

    This paper presents the design and preliminary validation of the Lunar Intelligent Navigation via Neural Architecture (LINNA) payload, a technology demonstration integrated into the SelenITA mission—Brazil’s first lunar CubeSat. The experiment is motivated by the future needs for autonomous state estimation in the Very Low Lunar Orbit (VLLO) regime, where Mascon-induced gravitational anomalies challenge traditional…

  • Low SWaP Flight Board for High-Speed On-Board Data Handling, Processing and AI Inference

    The continuous increase in payload data volume and mission autonomy requirements is driving the need for increasingly advanced on-board data handling and processing technologies in satellite systems. In particular, next-generation Earth observation, telecommunications, and distributed space architectures require high-performance processing capabilities to enable real-time data reduction, intelligent decision-making, and efficient use of downlink resources. Within…