Name
Abstract | ||
|---|---|---|
This work investigates a method to monitor safety and wellbeing of living-alone older adults based on a reuse of the WiFi data. The Received Signal Strength Indication (RSSI) signal readily available at any WiFi receiver has a great advantage of extremely low cost. However, the accuracy of indoor localization using RSSI has been a significant concern. A study is performed in an urban environment to localize specific rooms in a multi-room complex. RSSI data are collected by a smartphone app providing information about WiFi radio signal distributions of a number of Internet access points. Three classifiers, including the support vector machine, k-nearest neighbors and distance to mean, are tested and compared. Our result shows that the RSSI signal alone is sufficient to achieve indoor localization at least in an accuracy of the room level. This result, when combined with the motion data acquired by the smartphone, allows the use of a simple app to monitor safety and wellbeing of living-alone senior persons. |
Year | DOI | Venue |
|---|---|---|
2016 | 10.1109/IRI.2016.41 | 2016 IEEE 17th International Conference on Information Reuse and Integration (IRI) |
Keywords | Field | DocType |
Indoor Localization,Support Vector Machine,k-Nearest Neighbors,WiFi,RSSI,Smartphone | Data mining,Data collection,Received signal strength indication,Reuse,Computer science,Urban environment,Support vector machine,Real-time computing,Simultaneous localization and mapping,Internet access,Radio signal,Embedded system | Conference |
ISBN | Citations | PageRank |
978-1-5090-3208-2 | 0 | 0.34 |
References | Authors | |
0 | 6 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Xuan Xie | 1 | 11 | 7.24 |
| Xu Hongze | 2 | 6 | 3.66 |
| Guang Yang | 3 | 0 | 0.34 |
| Zhi-Hong Mao | 4 | 281 | 41.82 |
| W. Jia | 5 | 228 | 39.20 |
| M. Sun | 6 | 356 | 65.69 |