A Lightweight, Transferable, and Self-Adaptive Framework for Intelligent DC Arc-Fault Detection in Photovoltaic Systems
2026-03-30T08:51:40Z•8cfe8a56d13f9e5080bfbe4363261ac733889965f658457978f9b04e51249fa8
ELAAMIMONOMAOFDMRISV2Iarc-fault-detectioncovert-communicationsedge-cloud-adaptationfluid-antennaindex-modulationlocalizationmachine-learningmmWavemovable-antennaphotovoltaic-safetypilot-designradar-sensingrepeaterwireless-communications
What happened
This silver document is an arXiv feed (multiple new submissions) focused on wireless communications, sensing, and a photovoltaic (PV) safety application. Key papers include: a lightweight, transferable, and self-adaptive learning framework for DC arc-fault detection in PV systems (high accuracy claims and field adaptation mechanisms); occlusion-aware multimodal beam prediction and pose estimation for mmWave V2I using camera/LiDAR/radar/GNSS/mmWave history; near-field/full-motion localization with extra-large aperture arrays (ELAA); repeater-assisted MIMO frequency-diversity analysis; RIS‑NOMA/
Why it matters
A reviewed impact interpretation has not been published for this record.
Evidence and limitations
- Source ID
- arxiv_eess_sp
- Record identifier
- 8cfe8a56d13f9e5080bfbe4363261ac733889965f658457978f9b04e51249fa8
- Enrichment time
- 2026-03-30T08:51:40Z
- AI-assisted enrichment
- Yes
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