Wind Storm Estimation using a Heterogeneous ...
Document type :
Communication dans un congrès avec actes
Title :
Wind Storm Estimation using a Heterogeneous Sensor Network with High and Low Resolution Sensors
Author(s) :
Nevat, Ido [Auteur]
Institute for Infocomm Research - I²R [Singapore]
Peters, Gareth W. [Auteur]
University College of London [London] [UCL]
Septier, Francois [Auteur]
Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 [CRIStAL]
Laboratoire d'Automatique, Génie Informatique et Signal [LAGIS]
Institut TELECOM/TELECOM Lille1
Matsui, Tomoko [Auteur]
Institute for Infocomm Research - I²R [Singapore]
Peters, Gareth W. [Auteur]
University College of London [London] [UCL]
Septier, Francois [Auteur]
Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 [CRIStAL]
Laboratoire d'Automatique, Génie Informatique et Signal [LAGIS]
Institut TELECOM/TELECOM Lille1
Matsui, Tomoko [Auteur]
Conference title :
IEEE International Conference on Communications (ICC)
City :
London
Country :
Royaume-Uni
Start date of the conference :
2015-06-08
Publication date :
2015-06-08
English keyword(s) :
Kernel methods
imperfect communication channels.
Gaussian processes
Wireless sensor networks
Detection
imperfect communication channels.
Gaussian processes
Wireless sensor networks
Detection
HAL domain(s) :
Sciences de l'ingénieur [physics]/Traitement du signal et de l'image [eess.SP]
English abstract : [en]
We develop a new algorithm for spatial field reconstruction in heterogeneous (mixed analog & digital sen- sors) wireless sensor networks (WSNs). We consider spatial physical phenomena which are observed by a heterogeneous ...
Show more >We develop a new algorithm for spatial field reconstruction in heterogeneous (mixed analog & digital sen- sors) wireless sensor networks (WSNs). We consider spatial physical phenomena which are observed by a heterogeneous WSN, meaning that it is partially consists of sparsely deployed high-quality sensors and partially of low-quality sensors. The high-quality sensors transmit their (continuous) noisy observations to the Fusion Centre (FC), while the low- quality sensors first perform a simple thresholding operation and then transmit their binary values over imperfect wireless channels to the FC. We develop a novel algorithm that is based on a multivariate series expansion approach resulting in a Saddle-point type approximation. We then present comprehensive study of the performance gain that can be obtained by augmenting the high-quality sensors with low- quality sensors using real data of insurance storm surge database known as the Extreme Wind Storms Catalogue.Show less >
Show more >We develop a new algorithm for spatial field reconstruction in heterogeneous (mixed analog & digital sen- sors) wireless sensor networks (WSNs). We consider spatial physical phenomena which are observed by a heterogeneous WSN, meaning that it is partially consists of sparsely deployed high-quality sensors and partially of low-quality sensors. The high-quality sensors transmit their (continuous) noisy observations to the Fusion Centre (FC), while the low- quality sensors first perform a simple thresholding operation and then transmit their binary values over imperfect wireless channels to the FC. We develop a novel algorithm that is based on a multivariate series expansion approach resulting in a Saddle-point type approximation. We then present comprehensive study of the performance gain that can be obtained by augmenting the high-quality sensors with low- quality sensors using real data of insurance storm surge database known as the Extreme Wind Storms Catalogue.Show less >
Language :
Anglais
Peer reviewed article :
Oui
Audience :
Internationale
Popular science :
Non
Collections :
Source :