π€ Latest Submissions
LHADA - Lunar Habitat Anomaly Diagnosis Agent
Space habitats are unforgiving environments where a failing pump or a drifting CO2 scrubber can escalate from a warning to a catastrophe. LHADA - Lunar Habitat Anomaly Diagnosis Agent - is an AI-powered diagnostic system built to close that gap. LHADA ingests continuous telemetry from habitat life-support systems and runs it through a multi-method anomaly detection pipeline, combining threshold-based monitors, matrix-profile analysis (DAMP/MDI via STUMPY), and statistical drift detectors operating in parallel. When an anomaly is flagged, the system doesn't just raise an alert: it hands the signal to a reasoning agent powered by Qwen 2.5 32B, served on AMD MI300X hardware via vLLM, which cross-references a structured knowledge base to generate a human-readable diagnosis, likely root cause, and recommended action. The system was validated against the EDEN ISS 2020 dataset - a closed-loop Antarctic greenhouse and the closest publicly available analog to a space habitat life-support system. The implemented scenario is a thermal-loop coolant leak, inspired by ISS operational history, where gradual temperature deviations across the coolant circuit must be caught and diagnosed before they compromise habitat integrity. The full stack can run on-premises with no cloud dependency, making it viable for the high-latency, air-gapped reality of lunar operations. A real-time Gradio frontend streams live sensor data, anomaly annotations, and LLM diagnostic reasoning via WebSocket. A FastAPI backend exposes REST and streaming endpoints for integration with broader mission-control systems. LHADA demonstrates that AMD GPU infrastructure combined with open-weight LLMs can deliver mission-critical, explainable AI at the edge, where astronaut safety depends on fast, trustworthy answers.
10 May 2026
Cairn β Nanopayment Environmental Oracle
Community sensor networks generate enormous amounts of valuable data. +200k personal weather stations, +10k air quality sensors, seismic, radiation networks, run by hobbyists worldwide. Today, commercial platforms like Weather Underground and PurpleAir paywall this data while paying contributors zero. Open networks like Sensor.Community share data freely but have no sustainability model. Autonomous agents across parametric insurance, climate risk monitoring, supply chain management, automated research, and weather derivative pricing need granular, hyperlocal, real-time environmental data that neither system serves. Cairn is the payment layer that resolves both failure modes. Sensor operators register on-chain with a USDC stake and publish x402-gated reading endpoints. Autonomous customer agents discover sensors near a target location, buy verified readings per query through Circle Nanopayments, and act on the results. Operators keep 100% of their quoted rate; the Cairn aggregator charges a transparent 2% service fee for discovery, cross-reference verification, and on-chain attestation. Verification is structural. Each query selects a quorum of three sensors, compares readings via median plus median absolute deviation, and posts an immutable attestation to Arc. Operators that consistently disagree with the consensus see their reputation drop and their stake slashed automatically. The demo features a parametric weather insurance contract (one of many possible customer agents) continuously buying verified temperature readings from 5 operators around a coverage zone. The market cannot exist on any other rail. Per-query value is fractions of a cent. Stripe, L1 gas, and enterprise oracle pricing are all off by orders of magnitude. Circle Nanopayments on Arc is the only infrastructure where this market clears.
26 Apr 2026
