Slip & fall detection

Research has shown that accidental falls are among the most reported incidents in healthcare facilities, leading to patient injury, slipped discs and broken bones. With a proven accuracy of up to 99.1%, Scylla can detect slips and falls, either in real time or forensically from video footage. It detects an event right on time, and reacts immediately, helping you reduce the possibility of severe consequences.

Slip & fall prevention

One of the major concerns for healthcare institutions is the safety of patients in intensive care units. Scylla has developed a smart solution specifically for such cases. Nurses are alerted in real-time as soon as a patient is trying to leave their bed, so that immediate help and support can be provided. The solution doesn’t require facial recognition or any other technology that may be associated with breaching privacy of the patient.

Aggressive behavior detection

Violence against staff is placed at the top of the most common security challenges in healthcare facilities. With an accuracy of up to 95.9%, Scylla can help hospital security personnel detect fights and other types of aggressive behavior across multiple camera streams simultaneously.

Best-in-class AI-powered gun detection system

Gun violence puts healthcare workers and everyone else who is seeking care at that hospital at tremendous risk. With the impressive 0.1 false-positive rate per day per camera, Scylla AI is trained to detect a wide variety of firearms, both in real-time and forensically. What’s more, the gunman can be traced across the connected cameras in real-time even when the weapon has been hidden. So that you could be proactive, rather than reactive when seconds matter.