Name
Abstract | ||
|---|---|---|
In this paper, our goal is to develop approaches to reduce the energy consumption in Radio Tomographic Imaging (RTI)-based methods for device free localization without giving up localization accuracy. Our key idea is to only measure those links that are near the current location of the moving object being tracked. We propose two approaches to find the most effective links near the tracked object. In our first approach, we only consider links that are in an ellipse around the current velocity vector of the moving object. In our second approach, we only consider links that cross through a circle with radius r from the current position of the moving object. Thus, rather than creating an attenuation image of the whole area in RTI, we only create the attenuation image for effective links in a small area close to the current location of the moving object. We also develop an adaptive algorithm for determining r. We evaluate the proposed approaches in terms of energy consumption and localization error in three different test areas. Our experimental results show that using our approach, we are able to save 50% to 80% of energy. Interestingly, we find that our radius-based approach actually increases the accuracy of localization. |
Year | DOI | Venue |
|---|---|---|
2014 | 10.1109/SAHCN.2014.6990401 | Sensing, Communication, and Networking |
Keywords | Field | DocType |
energy consumption,imaging,tomography,wireless sensor networks,RTI-based methods,attenuation image,device free localization,energy consumption,energy efficient radio tomographic imaging,localization error,radio frequency sensor networks,radius-based approach | Computer science,Artificial intelligence,Ellipse,Distributed computing,Computer vision,Tomographic reconstruction,Efficient energy use,Simulation,Tomography,Radio frequency,Adaptive algorithm,Attenuation,Energy consumption | Conference |
ISSN | Citations | PageRank |
2473-0440 | 2 | 0.36 |
References | Authors | |
21 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Mojgan Khaledi | 1 | 6 | 1.15 |
| Sneha Kumar Kasera | 2 | 326 | 18.78 |
| Neal Patwari | 3 | 3805 | 241.58 |
| Maurizio Bocca | 4 | 274 | 16.62 |