See Through Walls with WiFi

Tracking Multiple Humans

The figures below show the Wi-Vi screen when there are one, two, and three persons moving in a room respectively. Each of the graphs always has a line at "zero" which corresponds to the residual DC (static objects). In addition to the zero line, the left-most window tracks one moving human indicated by the bright curved line other than the zero line. In contrast, the middle window tracks two moving humans; and the third tracks three moving humans indicated by the disconnected bright curves.

One Moving Person	Two Moving Persons	Three Moving Persons

Automatically Detecting the Number of Moving Objects

Wi-Vi uses the fact that a person cannot be in more than one location at any given point in time to automatically detect the number of moving objects. This is the underlying intution behind a metric it uses called spatial variance to determine this number. The table below shows that Wi-Vi can detect with 100% accuracy the presence or absence of a moving human. The accuracy of the current version of Wi-Vi drops to 85% and 90% in detecting two and three persons respectively.

	Detected
Actual		0	1	2	3
	0	100%	0%	0%	0%
	1	0%	100%	0%	0%
	2	0%	0%	85%	15%
	3	0%	0%	10%	90%

Gesture Detection Accuracy

For a human to transmit a message to a computer wirelessly, she typically has to carry a wireless device. In contrast, Wi-Vi can enable a human who does not carry any wireless device to communicate commands or short messages to a receiver using simple gestures. Wi-Vi designates a pair of gestures as a '0' bit and a '1' bit. A human can compose these gestures to create messages that have different interpretations.

The left and right figures below show the accuracy of Wi-Vi in decoding these gestures (bits) at different distances and through different building materials.

Gesture Decoding with Distance	Gesture Decoding in Different Building Materials