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This study investigated a nondestructive, remote-sensing-based testing method for detecting harmful wetness in immovable cultural heritage structures using unmanned aerial vehicle multispectral imagery combined with machine learning algorithms. The multispectral data were captured over a historic building with DJI Mavic 3M UAV, and supervised machine learning classifiers were applied to identify moisture-risk areas across the building’s facades. The spectral range of the employed multispectral sensor did not all...

The government electrical company – ESO manages and monitors 16 000 km powerlines in Bulgaria. In this paper the main focus is on monitoring forestry corridors, which are used to provide free of encroachment space for safe electrical power transmission. Those open spaces ensure that no tree or such can be near the conductor enough to cause induction of energy between a tree and a conductor, which is the main reason for wild fires and electrical power shortages. This paper presents a methodology for systematic mo...