The accommodation industry deals with large volumes of clients at once and for hotel owners, airlines and other companies, it is a priority to deal with them efficiently, without compromising security. As a result, it is an ideal field to implement facial recognition technology.
What are guest databases using facial recognition?
Facial recognition systems can be used to automate certain verification or authorization processes along the customer’s journey, as well as to enhance their own experience. Additionally, the ability to identify specific people, even in large groups, can be extremely advantageous, helping to make security systems more robust.
A customer database within the hospitality industry makes it possible to provide a higher level of customer service. For example, facial recognition can allow employees to quickly identify guests, perhaps even before they check in, and deliver a more personalized welcome and service.
Matches faces appearing on live video feeds in real-time with 98.87% accuracy so registered individuals are always spotted despite challenging real-world conditions. More accurate and faster than manual monitoring.
24/7 Monitoring, Centralized Knowledge Bank
Provides a central knowledge bank of known faces and monitoring activity that’s always up to date. Consistent across distributed locations, simple to update to ensure records are correct, and easy to search to perform post-event analysis.
Custom Real-Time Alerts & Notifications
Get instant notifications when persons of interest are spotted. Customize notifications and alarms based on a variety of detection or recognition events and program automated security response workflows and SMS and email notifications.
Request a demo
Why choose Facial Recognition - SAFR?
Not all facial recognition systems are created equal: Facial Recognition – SAFR can instantly detect and accurately match millions of faces in real time — even in challenging real-world conditions where faces are in motion, at difficult angles, under poor lighting conditions or partially obscured.
Fast & Accurate: Facial Recognition – SAFR is 99.87% accurate and can detect and match a face in a live video feed in under 100 milliseconds — 3-5 times faster than competing facial recognition algorithms.
Actionable: Facial Recognition – SAFR provides live security analytics with rich metadata. View traffic volumes, demographic composition, dwell times and more. Configure custom reports, alerts and auto-actions based on detection and recognition events — from sending a message to security guards to initiating a building lockdown.
Secure & Private: Facial Recognition – SAFR uses bank-level encryption on all face signatures and images in transit or at rest. If run on premises or embedded on device, Facial Recognition – SAFR passes no data over the internet. Built with privacy by design principles, Facial Recognition – SAFR makes it easy to configure data retention settings and manage opt-in/opt-out lists.
Deployment Neutral: Facial Recognition – SAFR can be deployed on a single computer to monitor a handful of video feeds, or scaled to thousands of cameras. The software can be hosted on premises or in the cloud, or deployed on even the most constrained camera-equipped devices with Facial Recognition – SAFR SDKs.
Distributed & Flexible: Facial Recognition – SAFR uses a distributed architecture to consume bandwidth more efficiently than many facial recognition providers. With the Facial Recognition – SAFR system’s edge intelligence for detection, recognition on the server, compatibility with off-the-shelf hardware and ability to leverage inexpensive GPUs, adding face recognition to your security tools is easier and more cost effective than you might think.
No more spending hundreds of hours searching your VMS. With Ava Smart Search you can search by event and similarity and perform appearance and image detection powered by machine learning capabilities to comb through countless hours of video throughout your entire deployment. Reduce forensic investigation time from days to minutes, and gain more efficiency and […]