This report presents a detailed overview of underground tomography research conducted with drone systems. The initiative was the highlight of the event organized by the IEEE AESS Student Chapter.
The topic addressed demonstrates the combination of cutting-edge technologies, such as high-precision sensors and machine learning algorithms, applied to a highly relevant interdisciplinary context.
The speaker explained the use of high-resolution radar bands, such as the P-band, to traverse solid surfaces and generate high-resolution maps.
The collected data was analyzed with machine learning algorithms, allowing efficient and accurate interpretation. The research revealed important applications, such as:
• Agriculture: Identifying soil conditions and locating water resources.
• Archaeology: Discovering historical structures without invasive excavations.
• Volcanology: Monitoring hidden geological formations for risk mitigation.
The research highlights the direct impact of the combination of drones and machine learning on the development of technological solutions. The identified applications have the potential to transform scientific, environmental and economic sectors, expanding the reach of geographic mapping technologies.
Future prospects include the expansion of the use of drones in geological, environmental and industrial studies, as well as the improvement of machine learning algorithms for real-time data analysis. This scenario points to a promising future, with more accessible and efficient solutions in multiple contexts.