Recent advances in deep learning motivate the use of deep neutral networks in sensing
applications, but their excessive resource needs on constrained embedded devices remain …

Many existing indoor localization systems have achieved applaudable performance through
comprehensive modeling of its envisioned working scenario. However their real life …

We consider the scenario of multiple RFID-tagged objects that simultaneously move across
an indoor space where several RFID antennas are placed. We assume that a logical …

With a network architecture selected and before elaborating other inference challenges in a
book on Edge AI, it behooves us to consider the question of training neural networks for …

We study the problem of separating interleaved sequences from discrete-time finite Markov
chains. Previous work has considered the setting where the Markov chains participating in …

Recent developments in deep learning have motivated the use of deep neural networks in
Internet-of-Things (IoT) applications. But the performance of the deep neural network models …

In this paper, we consider the problem of distributing patrol officers inside a building to
maximize the probability of catching multiple intruders while minimizing the distance the …

The field of personal informatics has become progressively mainstream recently with the rise
of groups such as Quantified Self and the introduction of commercially available user …

Ambient sensors are a category of sensing technologies designed to be embedded in an
environment for the purposes of monitoring changes to that environment from either internal …