Name
Abstract | ||
|---|---|---|
To improve localization accuracy, device-free passive localization studies usually deploy a number of sensor nodes in indoor environments, which causes redundant features and produces large data volumes and high deployment costs. This paper proposes the concept of a two-level redundancy and formulates the node reduction problem as a redundancy control problem. With the goal of using fewer nodes while maintaining high localization accuracy, a method is proposed to control the two-level redundancy efficiently and reduce the number of nodes greatly. Experiments are performed in two completely different environments. The proposed method is able to maintain accuracy levels above 90% and can efficiently reduce the total number of nodes by 59.09% in a large room (150 $${\\mathrm{m}}^2$$m2) and by 68.75% in a small room (25 $${\\mathrm{m}}^2$$m2). Furthermore, due to reduced nodes the proposed method can drastically reduce the needed amount of localization data and the hardware costs. |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1007/s00779-016-0979-8 | Personal and Ubiquitous Computing |
Keywords | Field | DocType |
Indoor passive localization, Redundancy reduction, Node optimization, Node reduction, Reducing the amount of data | Software deployment,Computer science,Device free localization,Real-time computing,Redundancy (engineering) | Journal |
Volume | Issue | ISSN |
21 | 1 | 1617-4917 |
Citations | PageRank | References |
1 | 0.38 | 16 |
Authors | ||
6 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Jinjun Liu | 1 | 2 | 3.18 |
| Ning An | 2 | 398 | 36.33 |
| Md. Tanbir Hassan | 3 | 1 | 0.72 |
| Min Peng | 4 | 24 | 4.94 |
| Zheng Cui | 5 | 1 | 0.38 |
| Shenghui Zhao | 6 | 33 | 14.29 |