The problem of identifying regions of spatially interesting, different or adversarial behavior is
inherent to many practical applications involving distributed multisensor systems. In this …

A wireless sensor network performs spatial inference on a physical phenomenon of interest.
The areas in which this phenomenon exhibits interesting or anomalous behavior are …

This paper studies the problem of the quickest change-point detection by a sensor powered
by randomly available energy harvested from the environment under a Bayesian framework …

In this paper, we formulate and solve a two-stage Bayesian sequential change diagnosis
(SCD) problem. Different from the one-stage sequential change diagnosis problem …

We recently proposed a novel approach to perform spatial inference using large-scale
sensor networks and multiple hypothesis testing [1]. It identifies the regions in which a …

A spatial signal is monitored by a large-scale sensor network. We propose a novel method
to identify areas where the signal behaves interestingly, anomalously, or simply differently …

Wireless communication systems have to be designed in order to cope with timefrequency-
space varying channel conditions and a variety of interference sources. In cellular wireless …

Detection of multiple spatial events in parallel is of wide interest in many modern
applications, such as Internet of Things, environmental monitoring, and wireless …

Spatial inference is an important task in large-scale wireless sensor networks, the Internet of
Things, radio spectrum monitoring, and smart cities. In this paper, we extend and adopt our …

Prescriptive analytics is a major advancement in the field of IoT analytics which enhances
decision-making and increases the effectiveness of processes. IoT data is referred to as …