P328 - EnviroInfo 2022

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Konferenzbeitrag
An Artificial Intelligence of Things based Method for Early Detection of Bark Beetle Infested Trees
(EnviroInfo 2022, 2022) Knebel, Peter; Appold, Christian; Guldner, Achim; Horbach, Marius; Juncker, Yasmin; Müller, Simon; Matheis, Alfons
Bark beetles, like the European Spruce Bark Beetle (Ips typographus), are inherent partsof a forest ecosystem. However, with favorable conditions, they can multiply quickly and infest vastamounts of trees and cause their extinction. Therefore, it is important for forest officials and rangers ofe. g. a national park, to monitor the population of the beetles and the infested trees. There are severalways to approach this, but they are often costly and time-consuming. Therefore, we design and test abark beetle early warning system with AI-based data analysis: Audio data, data on pheromones andinformation for a drought stress assessment of the affected trees are to be collected and used as a basisfor the analysis. The aim is to devise a micro-controller-based sensor system that detects the infestationof a tree as early as possible and warns the forest officials, e. g. via a message on their cell phone.