Multimodal Artificial Intelligence (Multimodal AI), in general, involves various types of data
(eg, images, texts, or data collected from different sensors), feature engineering (eg …

This paper reviews the classical decentralized decision theory in the light of new constraints
and requirements. The central theme that transcends various aspects of signal processing …

Situation-aware technologies enabled by multitarget tracking will lead to new services and
applications in fields such as autonomous driving, indoor localization, robotic networks, and …

The formalism of probabilistic graphical models provides a unifying framework for capturing
complex dependencies among random variables, and building large-scale multivariate …

Location awareness is vital for emerging Internet-of-Things applications and opens a new
era for Localization-of-Things. This paper first reviews the classical localization techniques …

Gossip algorithms are attractive for in-network processing in sensor networks because they
do not require any specialized routing, there is no bottleneck or single point of failure, and …

Two fundamental approaches to information averaging are based on linear and logarithmic
combination, yielding the arithmetic average (AA) and geometric average (GA) of the fusing …

This paper discusses nonparametric distributed learning. After reviewing the classical
learning model and highlighting the success of machine learning in centralized settings, the …

When choosing the technology options to develop a wireless sensor network (WSN), it is
vital that their performance levels can be assessed for the type of application intended. This …

In this paper, various positioning algorithms for range-based TOA and TDOA localization
have been analyzed, which include the Analytical method, Least Square method …