Col, Giacomo daGiacomo daColEggeling, EvaEvaEggelingHudelist, MarcoMarcoHudelistSchinko, ChristophChristophSchinkoSurtmann, ChristofChristofSurtmannTeppan, ErichErichTeppan2022-09-292022-09-292022https://publica.fraunhofer.de/handle/publica/42712310.3233/FAIA220073Flat roofs have become popular also in central and northern Europe during the last decades. One advantage when compared to pitched roofs is that flat roofs are typically significantly cheaper. Furthermore, the roof space can be used also as a garden, a terrace or simply to quite easily install photo-voltaic systems on it. However, flat roofs are known to be prone to drainage and leakage issues. Roof utilization as a garden or the shadowing of installed photo-voltaic systems magnify this problem. For these reasons, installing moisture sensors inside the roof in order to monitor the moisture levels is one possibility to detect roof damages early and keep repairing costs low. In this paper we report on first results of an industrial project that aims to go one step further. Based on past sensor values the goal is to predict how moisture levels will progress in the near future and thus be able to identify problems before they become critical.enMachine learningInternet of things (IoT)EvaluationTime series analysisconference paper