Building a basic drone equipment set for conducting research to detect anomalies in soil

Abstract

The development of remote sensing technologies using unmanned aerial vehicles (UAVs) and sensors of various measurement methods makes it possible to contactlessly detect various anomalies. Traditional agricultural methods are insufficient to meet the growing demand. The reliability of information after its processing is of primary importance. This reliability is achieved by a combination of measurement methods, the correct choice of contactless measurement tools and the use of machine learning methods for data processing and training on known anomalies. Despite a fairly large selection of tools, there is a limited number of such tools for UAVs. First of all, this is due to the weight and size characteristics of these tools. The most widely used research tools are metal detectors, ground penetrating radars, magnetometers, radiosondes and optical-spectral devices, such as multispectral cameras. The article develops an open architecture that can be used as a basis for building UAVs for a wide range of specific applications. A minimum set of necessary tools has been selected, based on the measurements and processing of which there will be enough information to identify anomalies in the soil with a high degree of reliability. The scope of application of the obtained results is quite extensive: from precision farming, including monitoring crop diseases and chemical non-contact soil analysis to identifying foreign inclusions and anomalies in areas where military actions took place.