IMPROVED INDOOR LOCALIZATION WITH MACHINE LEARNING TECHNIQUES FOR IOT APPLICATIONS (2022)
Abstract / truncated to 115 words
With the rapid development of the internet of things (IoT) and the popularization of mobile internet applications, the location-based service (LBS) has attracted much attention due to its commercial, military, and social applications. The global positioning system (GPS) is the prominent and most widely used technology that provides localization and navigation services for outdoor location information. However, the GPS cannot be used well in indoor environments due to weak signal reception, radio multi-path effect, signal scattering, and attenuation. Therefore, localization-based systems for indoor environments have been designed using various wireless communication technologies such as Wi-Fi, ZigBee, Bluetooth, UWB, etc., depending on the context and application scenarios. Received signal strength indicator (RSSI) technology has been extensively ...
indoor localization – machine learning – internet of things – indoor positioning systems – wireless sensor networks – smart cities
Information
- Author
- Madduma Wellalage Pasan Maduranga
- Institution
- IIC University of Technology
- Supervisors
- Publication Year
- 2022
- Upload Date
- March 13, 2025
First few pages / click to enlarge
The current layout is optimized for mobile phones. Page previews, thumbnails, and full abstracts will remain hidden until the browser window grows in width.
The current layout is optimized for tablet devices. Page previews and some thumbnails will remain hidden until the browser window grows in width.