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Edge-AI Vision Defense Architecture for Unmanned Commercial Facilities: Real-Time Anomaly Detection of Consecutive Currency Exchange Fraud, Physical Interlocks, and Deterministic Threat Severing 無人店舗・両替機における連続不正両替・枯渇攻撃に対するエッジAI防犯カメラ自律防衛アーキテクチャ:時系列骨格行動解析・滞在異常検知・確定性物理インターロック

Oct 2026 · Zenodo (CERN European Organization for Nuclear Research)

Abstract

Executive Abstract (English) Unmanned commercial facilities (e.g., 24-hour laundromats, automated storage units, and self-service currency exchange kiosks) suffer from an acute systemic vulnerability: conventional passive video surveillance (CCTV) records crime retroactively but fails to prevent active financial or physical asset destruction. Recently, automated "change-machine depletion attacks"—wherein perpetrators systematically drain coin/bill hoppers via fraudulent high-frequency micro-exchanges or mechanical feed exploitation—have escalated globally. This paper introduces a fully autonomous, edge-native computer vision defense architecture designed to detect and physically terminate ongoing currency exchange fraud within milliseconds. Operating entirely on low-power, air-gapped edge vision compute nodes, the system combines real-time spatiotemporal pose estimation (YOLOv8-Pose tuned for skeletal keypoint tracking), a spatial bounded-dwell state estimator, a high-frequency transaction gesture counter, and a specialized bag-filling vector field model. When an anomalous behavioral sequence breaches a deterministic risk threshold, the edge node triggers direct hardware GPIO solid-state relays (SSRs), hard-cutting the internal power rail of the bill acceptor/dispenser in under 50 milliseconds while activating local acoustic warnings, high-intensity strobes, and tamper-resistant telemetry alerts. 要旨(日本語) 24時間営業のコインランドリー等の無人商業インフラは、従来の防犯カメラ(CCTV)が「事後録画」に留まり、進行中の金銭・物理資産破壊を阻止できないという構造的脆弱性を抱えている。特に近年、投入口への機械的介入や高頻度小額両替による自動両替機の硬貨・紙幣枯渇攻撃(Depletion Attack)が深刻化している。 本論文では、このような連続不正両替および店舗荒らしをリアルタイムで検知し、確定的な物理制御によって被害をミリ秒単位で遮断する「エッジAIカメラ自律防衛アーキテクチャ」を提案する。低消費電力のエッジ推論ノード上で完全ローカル動作し、時系列骨格点推定(YOLOv8-Pose)、空間滞留判定、腕部反復運動ベクトル解析、および袋詰め行動領域ベクトル場モデルを統合処理する。異常行動リスク指標が臨界値を超えた瞬間、内蔵ハードウェアGPIOを介してソリッドステートリレー(SSR)を直接駆動し、50ミリ秒未満で両替機の識別機・払出機電源を機械的に遮断(Hard Power Cutoff)する。同時に大音量音声威嚇、高輝度ストロボ発光、および暗号化シグネチャ付き所有者通知を全自動で実行する。

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