Name
Abstract | ||
|---|---|---|
Indoor positioning and navigation systems are getting popular nowadays. There are different types of products in the way of accuracy, cost and power consumption in the field. Especially in the last couple of years, RSSI (Received Signal Strength Indicator) based positioning algorithms have studied but the results are not sufficient and there is no exact way decided to overcome this problem. In this paper, we will explain a method that combines Deep Learning and BLE (Bluetooth Low Energy) Fingerprinting method to get better accurate results. |
Year | Venue | Keywords |
|---|---|---|
2018 | Signal Processing and Communications Applications Conference | Deep Learninng,Indoor Positioning,BLE,Fingerprinting,Artificial Neural Network |
Field | DocType | ISSN |
Computer vision,Wireless,Fingerprint recognition,Computer science,Real-time computing,Signal strength,Artificial intelligence,Deep learning,Wireless sensor network,Bluetooth Low Energy,Bluetooth,Power consumption | Conference | 2165-0608 |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Kamuran Dogus Yuksel | 1 | 0 | 0.34 |
| Behcet Ugur Töreyin | 2 | 1 | 1.72 |