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AI is Watching Me on CCTV! But I Guess I'm Safer...

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Manage episode 446419042 series 3605861
Konten disediakan oleh Brian Carter. Semua konten podcast termasuk episode, grafik, dan deskripsi podcast diunggah dan disediakan langsung oleh Brian Carter atau mitra platform podcast mereka. Jika Anda yakin seseorang menggunakan karya berhak cipta Anda tanpa izin, Anda dapat mengikuti proses yang diuraikan di sini https://id.player.fm/legal.

This research paper presents the development and evaluation of an AI-driven Smart Video Solution (SVS) designed to enhance community safety. The SVS utilizes existing CCTV infrastructure and leverages recent advancements in AI for anomaly detection, leveraging pose-based data to ensure privacy. The system provides real-time alerts to stakeholders through a cloud-based infrastructure and mobile app, utilizing various data visualization techniques such as occupancy indicators, statistical anomaly detection, bird's eye view, and heatmaps. The paper includes a comprehensive real-world evaluation of the SVS, implemented in a community college setting, demonstrating its effectiveness, scalability, and privacy-preserving capabilities. The evaluation also examines the system's performance under increasing workloads and crowd densities, highlighting the impact of these factors on latency and throughput.

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56 episode

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Manage episode 446419042 series 3605861
Konten disediakan oleh Brian Carter. Semua konten podcast termasuk episode, grafik, dan deskripsi podcast diunggah dan disediakan langsung oleh Brian Carter atau mitra platform podcast mereka. Jika Anda yakin seseorang menggunakan karya berhak cipta Anda tanpa izin, Anda dapat mengikuti proses yang diuraikan di sini https://id.player.fm/legal.

This research paper presents the development and evaluation of an AI-driven Smart Video Solution (SVS) designed to enhance community safety. The SVS utilizes existing CCTV infrastructure and leverages recent advancements in AI for anomaly detection, leveraging pose-based data to ensure privacy. The system provides real-time alerts to stakeholders through a cloud-based infrastructure and mobile app, utilizing various data visualization techniques such as occupancy indicators, statistical anomaly detection, bird's eye view, and heatmaps. The paper includes a comprehensive real-world evaluation of the SVS, implemented in a community college setting, demonstrating its effectiveness, scalability, and privacy-preserving capabilities. The evaluation also examines the system's performance under increasing workloads and crowd densities, highlighting the impact of these factors on latency and throughput.

Read more:

  continue reading

56 episode

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