Augmented Reality for 5G
Struggling with dead zones and bad wifi? Struggle no longer! Using the power of augmented reality, SeeSignal lets you visualize and interact with layers of digital signal data via holograms that precisely model the radio frequency signals coming from cell phones, home routers, and wireless devices.
BadVR created ‘SeeSignal’ as a way to demonstrate the potential of immersive data visualization and analytics. We are constantly surrounded by invisible layers of important digital signal data - wifi, bluetooth, and cellular data that ultimately determines our connection to society. We can currently only see this data in single slices as we move about a room, gathering individual readings. We can then model out and conceive of these data layers as flat ‘coverage zones’ on 2D maps, but in reality, these digital signal layers are as multi-dimensional and complex as the humans who interact with them. Within any given space, coverage widely varies in strength and intensity based on altitude, building materials, and other factors.
‘SeeSignal’ gives everyone the opportunity - for the first time in history - to actually see and interact with digital data layers in real time, and in-situ. Their full scale and complexity can finally be seen, empowering users of all skill levels to understand and control the previously unseen digital world around them.
Using complex data spatialization, sampling algorithms, and a touch of machine learning, SeeSignal gathers signal data from phones, routers, or bluetooth devices, then displays it back to users via fully an interactive, completely immersive augmented reality environment. Break new frontiers by visualizing the data driving the connectivity of the digital world around you for the first time with SeeSignal!
Be the first company to see the world’s new 5G networks. Our business class application revolutionizes telecom tower planning with additional features for handling cellular signal data at scale. Get more accurate signal readings indoors and out with SeeSignal.
A great early example of what could be useful in spatial computing - very cool— Rony Abovitz (@rabovitz) November 18, 2018