The World's Most Advanced People Counter
Accurately count people in real time, without infringing on occupant privacy
Density is not a camera
Raw depth data captured by Density’s sensors—contains no personally identifiable information (PII). Density’s algorithms are trained to detect human movement and ignore all other objects.
Raw Data
Deep Learning
Raw Data
Deep Learning
Designed for Enterprise Deployment
Easy Network Connectivity
Ethernet Cat5e – Connect one end of a Cat 5e ethernet cable to a PoE+ network switch capable of providing 30W per port. Plug the other end of the ethernet cable into the sensor.
WiFi – Connect a 30W PoE+ injector in to the sensor for power, then configure the sensor to your WiFi network using the Setup App.
Easy to Install and Configure
We provide full installation guides for Hardware mounting.
We also offer an installation service for clients who would prefer a turn key solution. Please contact us for details.
No Additional Gateway Required
Some firewall changes may need to be made to allow communication with our cloud controllers, however no device spercific network gateway or router is required.
UK Support
UK technical support is avaliable Monday to Friday in business hours.
24/7 Support avaliable if required. Please contact us for details.
Scaleable
Density is highley scalable – multi-devices / multi-site.
Accessories
Low Profile Wall Mount
For mounting the sensor in areas with limited space above the entryway (requires minimum 3.75” clearance).
Ceiling Mount
For mounting the sensor to the ceiling in front of the entryway.
Requires additional 1/2″-13″ rod, not included.
Door Frame Mount
For mounting the sensor to the top or bottom surface of a wood or metal door frame.
Glass/Metal Mount
For mounting the sensor to a smooth glass or metal surface with semi-permanent adhesive.
Junction Box Mount
For mounting the sensor directly to a single gang junction box.
Cutting-Edge Hardware
To achieve unparalleled accuracy, the Density DPU pairs Class 1 infrared lasers with onboard compute power for running proprietary machine learning algorithms.
