Publication Type : Conference Paper
Publisher : Intelligent Data Communication Technologies and Internet of Things, Springer Singapore
Source : Intelligent Data Communication Technologies and Internet of Things, Springer Singapore, Volume 57, Singapore (2021)
Url : https://link.springer.com/chapter/10.1007%2F978-981-15-9509-7_67
ISBN : 9789811595097
Campus : Coimbatore
School : School of Engineering
Department : Computer Science
Year : 2021
Abstract : Indoor positioning and navigation systems are used to track entities in indoor spaces using Global Positioning System (GPS) and other satellite technology. The objective of this research is to demonstrate a semi-dynamic offline 3D indoor navigation setup using Received Signal Strength Indicator (RSSI) values of WiFi routers in the building with the support of an Android application. The data collection module in the application collects RSSI data along with the user's co-ordinates (Online Phase) and a TensorFlow model is trained on the collected data, converted to TensorFlow Lite format and hosted online. In the Offline Phase, RSSI data is recorded, processed with the machine learning model in the device and passed to a module in the app developed with Unity that visualizes the user's co-ordinates in a three-dimensional model of the building. This paper is a bare-bones implementation of the above mentioned ideologies of an indoor navigation system and can be fine-tuned to use in specific applications.
Cite this Research Publication : V. S. Sidhaarthan, Mukul, A., Ragul, P., R. Krishna, G., and D. Bharathi, “Offline 3D Indoor Navigation Using RSSI”, in Intelligent Data Communication Technologies and Internet of Things, Singapore, 2021, vol. 57.