4G Signal Strength Prediction Dataset Based on Rain Failure and Winter Conditions

Solar-powered insecticidal lamps have been widely used in agricultural pest control systems, where stable 4G connectivity is critical for real-time transmission of multi-source field data (soil parameters, pest images, and environmental metrics). However, the lack of reliable 4G signal strength datasets in agricultural scenarios, especially under rainfall conditions that cause signal degradation, poses a great challenge to deployment planning and network reliability. This project fills this gap by constructing the first agricultural 4G signal strength dataset under different weather conditions. Using UAV-assisted surveys and manual collection of 4G signal strength data, we systematically collect 4G signal metrics (RSRP) synchronized with precise latitude and longitude coordinates and weather parameters. This dataset enables signal mapping and rain-induced attenuation modeling based on spatial interpolation.