Slip & Fall Detection System
Enhance safety and prevent accidents with real-time AI monitoring
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FAQ
No, the Slip & Fall detection system is specifically designed to detect the action of a person falling. It does not recognize static postures like lying down or sleeping.
Yes, but detection depends on several factors, including the visibility of the incident within the camera’s field of view, the angle of the fall, and any obstructions that may block the detection. Optimal camera placement improves accuracy for such scenarios.
While the primary focus is on detecting slipping and falling accidents, the system can typically pick up sit-and-fall and jump-and-fall events as well, depending on camera visibility and movement patterns.
The system accumulates several consecutive frames and analyses the whole batch as a unit. The duration of this batch is different for different submodules but on average the chunk duration is 3-5 seconds.
The maximal distance will depend on the camera characteristics. More specifically, on the lens. Typically, for proper illumination (400 lx and higher) the requirement is that the person height should take up 1/6th of the frame height. For most cameras this results in maximal detection distances of up to 15 meters (with the optimal distance of not more than 6-7 meters). If optical or digital zoom is used or the camera doesn't have a standard aperture/focal range, the maximal distance can vary. Also depending on the distance the sensitivity thresholds might require environment specific adjustments.
An alert containing all the crucial information is compiled and delivered to assigned endpoints. There are several customizable alerting pathways: Scylla Platform, Scylla mobile alerting application, access point relay boards, and VMS alerting API, to name a few.
Absolutely. After all, what Scylla Slip & Fall detection system needs is the video feed from CCTV which is provided by most CCTV networks and video management systems.
Scylla's anomaly detection modules are trained on footage from static cameras, meaning that for optimal accuracy, the camera should remain stationary. However, slow-moving PTZ cameras can still be used, though any movement — especially abrupt changes — may increase the risk of false alerts. Proper calibration and strategic camera positioning can help mitigate this issue.
The preferred aspect ratio is 16:9 for optimal performance. However, the module supports all aspect ratios and can function across different video formats.
Yes, Scylla AI’s video analytics can operate on drone-mounted cameras; however, accuracy may be reduced compared to static setups. For optimal performance, the drone should remain as close to the event as possible and minimize movement to reduce false detections.