RETSINA: Reproducibility and Experimentation Testbed for Signal-Strength Indoor Near Analysis

Reproducibility is a core component of any scientific discovery. A step towards reproducibility within the IPIN community is the contribution of this paper, our software-based testbed, called RETSINA (Reproducibility and Experimentation Testbed for Signal-strength Indoor Near Analysis). RETSINA enables the repeatability, reproducibility and comparison of approaches that use machine learning to detect proximity. We demonstrate RETSINA’s functionality by repeating and extending the findings of a recent case study on Wi-Fi signal strength based contact tracing accuracy. Furthermore, we leverage RETSINA to experimentally compare the results for detecting close encounters produced by the original Wi-Fi signal strength readings study and our study using Bluetooth signal strength readings.