The manuscript entitled "Experimental data set analysis of RSSI-based indoor and outdoor localization in LoRa networks" has been accepted for publication in Internet Technology Letters []

The authors are: Emanuele Goldoni, Luca Prando, Anna Vizziello, Pietro Savazzi, and Paolo Gamba (TLC&RS lab).

Summary: Positioning capability represents one of the basic features of modern Internet of Things (IoT) applications. Although this objective may be pursued by using Global Navigation Satellite Systems, cheaper and simpler techniques are more suitable for low-power networks. In this letter, we present

a complete experimental data set of Received Signal Strength Indicator (RSSI) measurements collected in different indoor and outdoor environments using LoRa radios. Moreover, we apply simple and power efficient localization algorithms on the dataset. The main goal of this work is to share both the experimental data set and the preliminary results on localization among the community.