RSSIIndoorLocation-master

# RSSIIndoorLocation This repository is dedicated to test a dataset of RSSI Indoor Location Algorithm, currently using Trilateration and KNN. ## Installation To install this project start downloading the git repository: ``` $ git clone https://github.com/alefelipeoliveira/RSSIIndoorLocation.git ``` ## Requirements Libraries ```matplotib```, ```streamlit```, ```pandas```, ```copy``` and ```statistics``` are necessary. ``` $ pip install matplotlib streamlit pandas copy statistics ``` ## Run Streamlit creates a frontend environment to run different algorithms in the datasets, after installed strealit library, is possible to run the application in the local file, with the command ``` $ streamlit run .\main.py ``` ## Related Publication This project use the dataset from the following papers: S. Sadowski, P. Spachos, K. Plataniotis, "Memoryless Techniques and Wireless Technologies for Indoor Localization with the Internet of Things", IEEE Internet of Things Journal. https://github.com/pspachos/RSSI-Dataset-for-Indoor-Localization-Fingerprinting BELMONTE-HERNÁNDEZ, A.; HERNÁNDEZ-PEÑALOZA, G.; GUTIÉRREZ, D. M.; ÁLVAREZ, F. Swiblux:Multi-sensor deep learning fingerprint for precise real-time indoor tracking.IEEE Sensors Journal, IEEE, v. 19, n. 9,p. 3473–3486, 2019. http://www.gatv.ssr.upm.es/~abh/