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This article presents real-time edge video analytics for multicamera privacy-aware pedestrian tracking (REVAMP ² T), as an integrated end-to-end Internet of Things (IoT) system for privacy built-in decentralized situational awareness. REVAMP ² T presents novel algorithmic and system constructs to push deep learning and video analytics next to IoT devices (i.e., video cameras). On the algorithm side, REVAMP ² T proposes a unified integrated computer vision pipeline for detection, reidentification, and tracking across multiple cameras without the need for storing the streaming data. At the same time, it avoids facial recognition and tracks and reidentifies the pedestrians based on their key features at runtime. On the IoT system side, REVAMP ² T provides an infrastructure to maximize the hardware utilization on the edge, orchestrates global communications, and provides system-wide reidentification, without the use …