To illustrate the impact of the obstacles, we consider indoor and outdoor scenarios. We consider the Department of Computer Science and Engineering, IIT(BHU) buildings as indoor buildings and the railway platform as an outdoor scenario. Here, we use single-channel LG in our experiment. The distance between LNs and LG varies from 5 to 50 meters. The floor map illustrates the walls, doors, and windows between LNs and LG. We consider railway stations for the outdoor environment. The outdoor environment did not consist of obstacles between LNs and LG.
This repository contains code and instruction to reproduce the experiments presented in the paper
"A Methodology and Simulation-based Toolchain for Estimating Deployment Performance of Intelligent Collective Services at the Edge"
by Roberto Casadei, Giancarlo Fortino, Danilo Pianini, Andrea Placuzzi, Claudio Savaglio, and Mirko Viroli.
The RSSI-Dataset provides a comprehensive set of Received Signal Strength Indication (RSSI) readings from within two indoor office buildings. Four wireless technologies were used:
- Zigbee (IEEE 802.15.4),
- WiFi (IEEE 802. 11),
- Bluetooth Low Energy (BLE) and
- Long Range Area-Wide Network (LoRaWAN).
For experimentation Arduinos Raspberry Pi, XBees, Gimbal beacons Series 10 and Dragino LoRa Shield were also used.