STROOBnet Optimization via GPU-Accelerated Proximal Recurrence Strategies

arXiv:2404.14388v1 Announce Type: new
Abstract: Spatiotemporal networks' observational capabilities are crucial for accurate data gathering and informed decisions across multiple sectors. This study focuses on the Spatiotemporal Ranged Observer-Observable Bipartite Network (STROOBnet), linking observational nodes (e.g., surveillance cameras) to events within defined geographical regions, enabling efficient monitoring. Using data from Real-Time Crime Camera (RTCC) systems and Calls for Service (CFS) in New Orleans, where RTCC combats rising crime amidst reduced police presence, we address the network's initial observational imbalances. Aiming …

abstract arxiv cameras capabilities crime cs.cv cs.lg cs.ma data decisions enabling events gpu monitoring multiple network networks nodes observable optimization real-time strategies study surveillance type via