Bitterne Community Pre-School

FootfallCam, a privately held firm that was founded in 2002, is the top provider of solutions for counting people worldwide.
We have a team of highly skilled engineers who produce all of the hardware and software in-house at our U.K. headquarters, using their specialties to address business problems over time.
We have tirelessly serviced organisations all over the world in industries ranging from retail, fast food restaurants, and museums to smart buildings and airports, for more than ten years, with the help of a global network of reseller partners and ongoing effort in research and development.
Research and development (R&D) is important to our business and is a key component of our core strategy.
We have an internal R&D team devoted to the creation of FootfallCam's hardware and software.
FootfallCam is able to maintain its position at the forefront of the people counting market through constant product development.
Our main product, FootfallCam 3D Max, was successfully created because to our creative approach to product development.
We are the first company in the world to integrate Wi-Fi analytics and people counts into a single device.
We are dedicated to upholding our position as the industry leader by providing the level of strategic insight that our clients demand.
By opening sales offices in a number of nations, including the United Kingdom, the United States, Hong Kong, and Malaysia, FootfallCam increases its footprint across the globe.
FootfallCam has established sales offices in more than 100 nations, including Ireland, France, Italy, Spain, the United Arab Emirates, South Africa, Thailand, Singapore, Indonesia, Germany, Australia, and others. In addition, it has built up a solid partner network.
We have created hardware and software for solutions involving people counting for more than 100 years.
Stereoscopic (3D image processing) being able to discern intelligently between a human and non-human objects and follow a walking human's course of travel.
Support Vector Machine (SVM) neural network modelling is used in artificial intelligence to train our machines to recognise objects.