A Radar-Enabled Collaborative Sensor Networking Integrating COTS Technology for Surveillance and Tracking

The feasibility of using Commercial Off-The-Shelf (COTS) sensor nodes is studied in a distributed network, aiming at dynamic surveillance and tracking of ground targets. Data acquisition by low-cost (\u3c$50 US) miniature low-power radar through a wireless mote is described. We demonstrate the detection, ranging and velocity estimation, classification and tracking capabilities of the mini-radar, and compare results to simulations and manual measurements. Furthermore, we supplement the radar output with other sensor modalities, such as acoustic and vibration sensors. This method provides innovative solutions for detecting, identifying, and tracking vehicles and dismounts over a wide area in noisy conditions. This study presents a step towards distributed intelligent decision support and demonstrates effectiveness of small cheap sensors, which can complement advanced technologies in certain real-life scenarios

Pratos e mais pratos: louças domésticas, divisões culturais e limites sociais no Rio de Janeiro, século XIX

Reply to ten comments on a paper published in the last issue of this journal. The discussion follows along six main lines: History museums, identity, ideology and the category of nation; the need of material collections and their modalities: patrimonial, operational, virtual; theater versus laboratory; visitors and their ambiguities; Public History: the museum and the academy.Resposta aos comentários de dez especialistas que contribuíram no debate de texto publicado no último número desta revista. A discussão orientou-se segundo seis tópicos principais: museus históricos, identidade, ideologia e a categoria de nação; a necessidade de acervos materiais e suas modalidades: acervo patrimonial, operacional, virtual; teatro versus laboratório; o público e suas ambigüidades; História Pública: o museu e a Academia

Autonomous wireless radar sensor mote integrating a doppler radar into a sensor mote and its application in surveillance and target material classification

An autonomous wireless sensor network that consists of different types of sensor modalities is a topic of intense research due to its versatility and portability of applications. Typical autonomous sensor networks commonly include passive sensor nodes such as infrared, acoustic, seismic, and magnetic. However, fusion of another active sensor such as Doppler radar in the integrated sensor network may offer powerful capabilities for many different sensing and classification tasks. In this work, we demonstrate the design and implementation of an autonomous wireless sensor network integrating a Doppler sensor into wireless sensor node with commercial off the shelf components. Then we demonstrate two applications of the newly integrated radar mote in a wireless sensor network environment where other sensor motes are supporting the integrated radar mote for autonomous triggering and data collection. At first we use the integrated system to detect the range and velocity of a toy train effectively to demonstrate its capability as a surveillance tool. Then we classify different types of non-conducting target materials based on their reflected signal response to newly built radar mote. Different types of materials can usually affect the amount of energy reflected back to the source of an electromagnetic wave. For investigating this observation we simulate models for the reflectivity of different homogeneous non-conducting materials using a mathematical model and later classify the types of target materials using real experimental data collected through our autonomous radar-mote sensor network. © 2011 SPIE

Multi-modal sensor system integrating COTS technology for surveillance and tracking

The feasibility of low-cost, Commercial Off-The-Shelf (COTS) sensor nodes is studied in a distributed network, aiming at dynamic surveillance and tracking of ground targets. Data acquisition by the low-cost (\u3c $50 US) miniature radar is described. We demonstrate the detection, ranging and velocity estimation capabilities of the mini-radar, and compare results to simulations. Furthermore, we integrate the radar output with supplementary sensor modalities, such as acoustic and vibration transducers, and infrared sensors. The method provides innovative solutions for detecting, identifying, and tracking vehicles and dismounts over a wide area in noisy conditions. This study presents a step towards distributed intelligent decision support and demonstrates effectiveness of small cheap sensors in identifying unique but similar events. Our work supports a pervasive sensor implementation relevant to the affordable open system architecture attribute of the U.S. Air Force Layered Sensing paradigm. © 2010 IEEE

A radar-enabled collaborative sensor network integrating COTS technology for surveillance and tracking

The feasibility of using Commercial Off-The-Shelf (COTS) sensor nodes is studied in a distributed network, aiming at dynamic surveillance and tracking of ground targets. Data acquisition by low-cost (\u3c$50 US) miniature low-power radar through a wireless mote is described. We demonstrate the detection, ranging and velocity estimation, classification and tracking capabilities of the mini-radar, and compare results to simulations and manual measurements. Furthermore, we supplement the radar output with other sensor modalities, such as acoustic and vibration sensors. This method provides innovative solutions for detecting, identifying, and tracking vehicles and dismounts over a wide area in noisy conditions. This study presents a step towards distributed intelligent decision support and demonstrates effectiveness of small cheap sensors, which can complement advanced technologies in certain real-life scenarios. © 2012 by the authors; licensee MDPI, Basel, Switzerland

Autonomous wireless radar sensor mote for target material classification

Autonomous wireless sensor networks consisting of different types of sensor modalities have been receiving greater attention from researchers due to their versatility and portability. These autonomous sensor networks commonly include passive sensors such as infrared, acoustic, vibration, and magnetic nodes. However, fusion of active sensors in the integrated sensor network, such as Doppler radars, may offer powerful capabilities for many different sensing and classification tasks. In this work, we demonstrate the design and implementation of an autonomous wireless sensor network integrating a Doppler sensor with commercial off-the-shelf components. We investigate the effect of various types of target materials on the measured radar signal as one of the applications of the newly designed radar-mote network. Different types of materials affect the amount of energy reflected back to the source of an electromagnetic wave. We obtain mathematical and simulation models for the reflectivity of different homogeneous non-conducting materials and study the effect of such reflectivity on the classification of targets. We validate our simulation results using real experimental data collected through our autonomous radar-mote sensor network using various types of targets. © 2012 Elsevier Inc

Studies in forestry resources in Florida,

Volume II by A. Stuart Campbell, assisted by Robert C. Unkrich; vol. III by A. Stuart Campbell, assisted by Robert C. Unkrich and Albert C. Blanchard.Contains bibliographies.I. Timber conservation.--II. The lumber industry.--III. The naval stores industry.Mode of access: Internet

A Radar-Enabled Collaborative Sensor Network Integrating COTS Technology for Surveillance and Tracking

The feasibility of using Commercial Off-The-Shelf (COTS) sensor nodes is studied in a distributed network, aiming at dynamic surveillance and tracking of ground targets. Data acquisition by low-cost ( < $50 US) miniature low-power radar through a wireless mote is described. We demonstrate the detection, ranging and velocity estimation, classification and tracking capabilities of the mini-radar, and compare results to simulations and manual measurements. Furthermore, we supplement the radar output with other sensor modalities, such as acoustic and vibration sensors. This method provides innovative solutions for detecting, identifying, and tracking vehicles and dismounts over a wide area in noisy conditions. This study presents a step towards distributed intelligent decision support and demonstrates effectiveness of small cheap sensors, which can complement advanced technologies in certain real-life scenarios