AI-Driven UAV Gamma-Ray Spectroscopy for In-Situ Agricultural Soil Analysis
Natalie Austin
Stellenbosch University, South Africa
Abstract:
Agricultural soils contain naturally occurring radionuclides whose gamma-ray emissions can provide valuable information about soil properties such as moisture content, texture, and carbon levels. This MSc project aims to develop an AI-enabled unmanned aerial vehicle (UAV) platform capable of performing autonomous gamma-ray surveys for agricultural applications. By integrating lightweight radiation detectors, UAV-based sensing, and deep learning techniques, the system seeks to enable rapid, non-invasive soil characterization and radiological assessment over large areas. Machine learning models, including convolutional neural networks (CNNs), will be trained using a combination of experimental measurements and Monte Carlo simulated spectra to automate radionuclide identification and support the inference of key soil properties.
Seminar takes place on Monday, October 5th 2026 at 10:30 AM
in the IEAP conference center, Praha 1, Husova 240/5.
| Ing. Bartoloměj Biskup, Ph.D. seminar chair |
doc. Ing. Ivan Štekl, CSc. director of IEAP |
doc. Dr. André Sopczak IEEE CS - NPSS chair |
NUCLEAR & PLASMA SCIENCES SOCIETY CHAPTER
IEEE Czechoslovakia section
https://www.ieee.cz/main/section/nps/