193 citations · 526 across the 12 of their papers we have counts for
12 papers
Aerial Vehicles Tracking Using Noncoherent Crowdsourced Wireless Networks
Hazem Sallouha, Alessandro Chiumento, Sofie Pollin
Air traffic management (ATM) of manned and unmanned aerial vehicles (AVs) relies critically on ubiquitous location tracking. While technologies exist for AVs to broadcast their loc…
Stateless Reinforcement Learning for Multi-Agent Systems: the Case of Spectrum Allocation in Dynamic Channel Bonding WLANs
Sergio Barrachina-Muñoz, Alessandro Chiumento, Boris Bellalta
Spectrum allocation in the form of primary channel and bandwidth selection is a key factor for dynamic channel bonding (DCB) wireless local area networks (WLANs). To cope with vary…
Energy Aware Deep Reinforcement Learning Scheduling for Sensors Correlated in Time and Space
Jernej Hribar, Andrei Marinescu, Alessandro Chiumento +1
Millions of battery-powered sensors deployed for monitoring purposes in a multitude of scenarios, e.g., agriculture, smart cities, industry, etc., require energy-efficient solution…
Three-layer Approach to Detect Anomalies in Industrial Environments based on Machine Learning
Daniel Gutierrez-Rojas, Mehar Ullah, Ioannis T. Christou +8
This paper introduces a general approach to design a tailored solution to detect rare events in different industrial applications based on Internet of Things (IoT) networks and mac…
Localization in Ultra Narrow Band IoT Networks: Design Guidelines and Trade-Offs
Hazem Sallouha, Alessandro Chiumento, Sreeraj Rajendran +1
Localization in long-range Internet of Things networks is a challenging task, mainly due to the long distances and low bandwidth used. Moreover, the cost, power, and size limitatio…
Energy Efficient WSN: a Cross-layer Graph Signal Processing Solution to Information Redundancy
Alessandro Chiumento, Nicola Marchetti, Irene Macaluso
In this work an iterative solution to build a network lifetime-preserving sampling strategy for WSNs is presented. The paper describes the necessary steps to reconstruct a graph fr…