Automatically analyze video from your existing camera network to take action in real-time and unlock insights to create a smart, safe environment.
Intelligent Video Analytics leverages Computer Vision and Deep Learning technologies to automatically process visual data, e. g. surveillance footages, security videos or aerial imagery, and differentiate between objects, people, conditions, and events in real time. This information is used to provide advanced warnings in forms of e-mails, notifications or direct police/ambulance calls. Aggregated over time, Intelligent Video Analytics helps to uncover insights invaluable for ensuring personal and public safety.
Our Computer Vision engineers have developed a video analytics module that manages slip and fall accidents in real-time. The solution generates an alert when someone falls down within the monitored area and sends the alert together with the video feed to the designated person – it can be an elderly caretaker, a police officer, a security staff member or a location administrator.
Employing Deep Learning models together with advanced image processing techniques allowed us to reach 95%+ accident detection accuracy while maintaining real-time video stream processing.
Slip and fall accidents are reported in real-time while the system works continuously without disruption or downtime.
Each accident is written into the database and displayed on the web-accessible dashboard with easily configurable views giving the administrator at a glance awareness of the current safety status in the monitored facility. This information can be automatically exported to the 3rd party reporting or data management systems via API or other methods.
The fall detection system does not rely on or utilize in any way facial recognition or person identification technologies. It does not collect any sensitive or personal data and is fully GDPR compliant.
Both patients and caregivers are vulnerable to falling on hospital premises as medical staff often face work fatigue while patients can be at risk because of their age or medication effects.
Early fall detection ensures quick response of the health professionals and minimizes the negative outcome of the accident.
Fake slip and fall claims cause shopping malls substantial financial losses. Collecting video evidence through camera-based fall detection is one of the most effective ways of discovering staged accidents and preventing fraudulent insurance payouts.
Slip, trip and fall accidents account for 28% of all fatal and 23% of all nonfatal occupational injuries in construction and manufacturing industries. With an automatic fall detection system, employers can identify and eliminate fall hazards to build a safer workplace for their employees.
It is vital to choose appropriate technologies and programming languages for project implementation as it influences project development duration, its cost, and lifespan.