Name
Abstract | ||
|---|---|---|
Indoor localization is becoming critical to empower Internet of Things for various applications, such as asset tracking, geolocation, and smart cities. Wi-Fi-based indoor localization using received signal strength (RSS) has drawn much attention over the past decade because it does not require extra infrastructure and specialized hardware. It is well known that the localization accuracy using RSS ... |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1109/JIOT.2017.2787594 | IEEE Internet of Things Journal |
Keywords | Field | DocType |
Wireless fidelity,Internet of Things,Testing,Robustness,Databases,Training,Adaptation models | Complementarity (molecular biology),Data mining,Computer science,Geolocation,Fusion,Fingerprint,Exploit,Robustness (computer science),Asset tracking,RSS,Distributed computing | Journal |
Volume | Issue | ISSN |
5 | 2 | 2327-4662 |
Citations | PageRank | References |
3 | 0.37 | 0 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Xiansheng Guo | 1 | 21 | 4.89 |
| Lin Li | 2 | 14 | 2.64 |
| Nirwan Ansari | 3 | 4667 | 357.64 |
| Bin Liao | 4 | 196 | 32.33 |