Omkar2118/datasets huggingface dataset:
TDMA CSI 16

This dataset is a collection of paired wireless signal data and corresponding image ground truth specifically designed for underground object sensing and image reconstruction. It utilizes Channel State Information (CSI) and Received Signal Strength Indicator (RSSI) collected from a low-cost WiFi Wireless Sensor Network (WSN) deployed around a soil volume containing underground potato tubers. The data was acquired in a controlled laboratory environment using an automated system that ensures precise alignment between the wireless measurements and the physical location/shape of the target.

The primary motivation for creating this dataset was to provide a resource for developing and evaluating non-destructive, low-cost methods for sensing underground biomass, overcoming the limitations of traditional techniques and simpler wireless metrics like RSSI. The dataset contains:

- CSI amplitude (52 data subcarriers) and RSSI values from a 16-node ESP32-C3 WiFi mesh network across 14 channels, capturing frequency-dependent and overall signal attenuation for numerous links.
For each wireless sample, a 360x360 pixel binary image mask representing the precise 2D cross-section of the underground potato tuber at that orientation, generated via automated camera and image segmentation.
The dataset includes data collected from 8 different potato tubers, with measurements taken at 32 distinct rotation angles for each.

Introducing paper: Underground Root Tuber Sensing via a Wi-Fi Mesh Network