Validated Adaptation for Aerial Crowd Monitoring at Mass Gathering Scale: A Deployment Protocol, a Severity Law, and a Diagnostic for Label-Free Drone Crowd Counting, Toward the FIFA World Cup 2034 (Saudi Arabia)
Read the original on arXiv AI →The paper presents a validated protocol for adapting drone‑based crowd‑counting models to the extreme conditions expected at the 2034 FIFA World Cup in Saudi Arabia. Using 525 controlled runs and a full‑resolution corpus, the authors demonstrate that label‑free adaptation can recover 31‑49% of shift‑induced error across multiple corruptions and severities, achieving a 41.8 MAE improvement over a frozen source model. They also introduce a severity law, a stability budget, and a flux‑based risk module that detects real congestion episodes, culminating in a six‑point deployment protocol for safe aerial crowd monitoring.
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