A Synchronized Kinematic and Optical Dataset for Mobility-Aware Predictive Modeling in Indoor LiFi Systems

The objective of the dataset is to support research on channel aging, predictive modeling, adaptive communication, and sensor-based LiFi system analysis. Data were collected using a custom ESP32-based sensing platform equipped with an Inertial Measurement Unit (IMU) and an optical photodiode receiver.

Measurements were sampled at 100 Hz with aligned timestamps to ensure consistency between motion and optical observations. The dataset includes five experimental scenarios representing progressively different operating conditions: S1: Static baseline alignment S2: Controlled single-axis motion S3: Multi-axis orientation analysis S4: Realistic handheld motion S5: Strong random motion with intermittent signal degradation Each record may include timestamps, inter-sample intervals, acceleration, angular velocity, raw ADC optical readings, calibrated voltage, and scenario labels.