Open AccessDL-IPS: Deep Learning Based Indoor Positioning System for Improved Accuracy
Author(s) -
Bhulakshmi Bonthu,
M. Subaji
Publication year - 2019
Publication title -
international journal of recent technology and engineering
Language(s) - English
Resource type - Journals
ISSN - 2277-3878
DOI - 10.35940/ijrte.d4351.118419
Subject(s) - leverage (statistics) , computer science , bluetooth low energy , deep learning , artificial intelligence , real time computing , bluetooth , indoor positioning system , signal strength , field (mathematics) , machine learning , telecommunications , wireless , mathematics , accelerometer , pure mathematics , operating system
Indoor tracking has evolved with various methods and well known these days. There are diverse types of solutions that concentrate on exactness, low cost, and control utilization within the field. Particularly in recent years, Received Signal Strength Indicator based positioning estimation have been getting popular. Still, the accuracy are not adequate, and there's no correct way chosen to overcome this issue. In this paper, we propose a strategy that leverage Deep Learning and Wi-Fi/BLE (Bluetooth Low Energy) Fingerprinting strategy to produce superior precise accuracy.