@inproceedings{Ger2017,Author = {Gerka, Alexander and Bayer, Finn and Eichelberg, Marco and Frenken, Melina and Hein, Andreas },Title = {Ambient Water Usage Sensor for the Identification of Daily Activities},Year = {2017},Pages = {225 - 230},Month = {6},Publisher = {IEEE},Isbn = {978-1-5090-5873-0},Booktitle = {Global Internet of Things Summit},type = {inproceedings},Abstract = {Dementia patients, like most older adults, preferto live in their own home as long as possible. This requires,however, that they are able to perform activities of daily living(ADL). Therefore, many research projects install different sensorsetups to identify ADLs. Though the water usage correlates withmany ADLs (i.e.: bathing, cooking) only few of these systemsuse water usage sensors. The reason is that there is no waterusage sensor available that is unobtrusive, ambient and precise.In this article, we propose a water usage sensor that is basedon a piezoelectric element that fulfills these requirements. Wedescribe the implementation of the sensor system in a living lab.Additionally, we discuss different features that were extractedfrom the sensor signal and different machine learning algorithmsthat were used to classify the data. Finally, we present the resultsto several tests we performed to determine the accuracy of oursensor system under different environmental conditions.}}@COMMENT{Bibtex file generated on }