We demonstrate a mote-scale, human-animal classifier based on a micropower radar. Our classifier is automatically learned from diverse data, using features in the joint time-frequency domain. It is being used as part of a wireless sensor network in a forest to create a virtual fence for human and wildlife protection.
Realizing delay-capacity in intermittently connected mobile networks remains a largely open question, with state-of-the-art routing schemes typically focusing either on delay or on capacity. We show the feasibility of routing with both high goodput and desired delay constraints, with REAPER (for Reliable, Efficient, and Predictive Routing), a fully… (More)