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This study explores the evolution from crowd counting to predictive intelligence, focusing on real-time crowd behaviour analysis through a review of 79 studies from 2015 to 2026. It synthesizes existing methods in density and crowd counting, while addressing gaps in temporal modelling and anomaly detection. The proposed framework emphasizes privacy-aware multi-camera acquisition, integrating density, flow, tracks, and scene context to enhance prediction of future states using graph transformers.