City trees are increasingly suffering from the consequences of climate change and the extreme weather of an urban climate. Due to their long lifespan and slow genetic adaptation in response to environmental changes, they are particularly hard hit by increasingly frequent droughts and temperature extremes.

QTrees resorts to the potential of AI to help take care of city trees and prevent them from withering and dying. We are developing AI models that use multiple data sources, for instance open data about trees themselves, soil, ground water, surface sealing, as well as data from sensors installed in the tree’s soil, the watering done by Berlin’s authorities and a shadow index.The machine learning algorithms provide a prediction of the state of trees that are not equipped with sensors as well as a forecast.

The results will be provided as an open source tool to support experts’ decision making processes by providing an overview of data affecting water consumption as well as an estimation of the watering needs. This can potentially lead to a reduction in the water use.

The project QTrees also engages the civil society into the protection of city trees by developing a tool that raises awareness about the topic and shows which measures can be taken to improve the conditions of trees in the city.

QTrees uniquely brings together experts for AI, service and UX design to preserve and care for Berlin’s city trees. The talk will introduce the project and provide some general lessons on using AI in environmental applications to ensure that AI is not simply used for its own sake but to create sustainable solutions.