FootfallCam 3D Pro2™
FootfallCam 3D Pro2™ is specially designed to support low ceiling height (as low as 2.1m) counting. Embedded with a powerful 1.2GHz Quadcore processor, it is packed with feature upgrades while maintaining performances of its predecessors. Specifically designed to run complex video processing algorithms, the GPU runs our AI-based algorithms which utilizes depth, colour and texture pattern to identify a person, producing superior accuracy compared to using colour pattern alone. The built-in sensor further improves accuracy in low-light, indoors and high noise environments. Delivered in Splash proof case, the overall form factor is more compact and inconspicuous than ever.
3D-Spacing Mapping Video Tracking Technology and AI Video Analytics.
Camera Lens Spec
Depth Field of View
Minimum 1 lux
Ideal Mounting Height
2.1 metres – 4.5 metres
Aluminum oxide alloy
Power Over Ethernet
6W (max. 8W)
Supports a network of up to 250 IoT devices via RF
3D Stereovision Video Counting with 25 FPS, 8MP | AI Analytics On Object Classification
Combining 3D stereoscopic image processing and AI video analytics together with advanced tracking algorithms, FootfallCam 3D Pro2™ People Counter is optimised to achieve up to 99.5% accuracy, even in environmentally challenging conditions. Embedded with a powerful 1.2GHz Quadcore processor, it is designed specifically to run complex video processing and AI-based algorithms with superior processing power.
One Device, Multiple Applications
Offers deployment flexibility for both short term and long term use
Supports multiple counting functions in a single device, in which users can use interchangeably or relocate to use for other functions.
Returning Customers | Visit Duration | Outside Traffic
With the Wi-Fi capturing technology, the people counter is able to detect the number of smart devices within the range of Wi-Fi detection. With this, the people counter is capable of providing in depth Wi-Fi analytics and business metrics such as zone analytics, dwell time, passerbys, turn in rate, traffic flow, returning customers and cross shopping.
FootfallCam uses a series of advanced video processing algorithm to count human traffic bi-directionally. With the ability to count in two direction, users will not be required to perform manual calculation to determine the actual count of visitors.
U-turn not counted
Through an advanced filtration system in the algorithm for processing, FootfallCam can intelligently distinguish when a person is not truly entering the store.
Distinguish random movement
As customer tracks can vary significantly and certain behaviours will skew data and create false counts. To counteract this issue and enhance the accuracy of footfall and dramatically reduce false counts, IN and OUT are only counted if a person’s behaviour are indicative of an entrance or exit.
Eliminate shadow counts
By using stereoscopic lens and advance algorithm to recreate a field of depth after a visitor enters the store, the counter does not rely on background image processing to count the visitor. As such, changes in the color pattern or saturation of background have no bearing on the accuracies of the counter.
Exclude children and trolleys
Advanced height filtering is automatically configured for children and shopping carts from being counted. As both children and shopping carts are not the direct purchaser or consumer, they have no purchasing power and will only falsified conversion rates when they are counted.