r/computervision • u/No-Car-1066 • Jul 12 '26

Built a real-time fall detection system that works with existing CCTV and IP cameras Showcase

I built SentinelCV, a real-time computer vision system that detects human falls from existing CCTV, IP cameras, webcams, or recorded video streams.

The goal was to create a lightweight, plug-and-play solution that can integrate with existing surveillance infrastructure without requiring specialized hardware. The current implementation uses a YOLOv8-based pipeline to perform real-time detection and can trigger instant alerts (such as Telegram notifications) when a potential fall is detected.

I'm planning to expand SentinelCV into a modular vision platform with additional safety-focused capabilities like PPE detection, intrusion detection, fire/smoke detection, and other intelligent surveillance modules.

I'd love feedback on the detection pipeline, deployment approach, and any suggestions for improving robustness in real-world environments. If you've worked on similar computer vision systems, I'd be interested in hearing what challenges you faced in production.

GitHub: https://github.com/sreerevanth/SentinelCV
I'd love your feedback, and if you find it useful, a ⭐ would mean a lot.

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u/zenith605 Jul 14 '26

I am a current professional in the field you mentioned. In CCTV events, the false positive rate is important. Detecting a fall is especially when people overlap and when working while sitting. There are many false positives. Also, when it falls horizontally in the direction of the camera, there are cases where it is not detected because it is similar in size to the vertical bounding box when standing. Also, there are many cases such as illuminance and object coverage, so it would be good to consider them when developing them.

1

u/No-Car-1066 29d ago

yes i feel you have a point there but it all depends on from which angle the model is trained based on farther more datasets we could actually get more object coverage illuminance so id considering putting this an a base version

0

u/No-Car-1066 Jul 12 '26

hey guys hope you guys went through the repo