1. Indoor User Movement Prediction from RSS data: This dataset contains temporal data from a Wireless Sensor Network deployed in real-world office environments. The task is intended as real-life benchmark in the area of Ambient Assisted Living.
2. Activity Recognition system based on Multisensor data fusion (AReM): This dataset contains temporal data from a Wireless Sensor Network worn by an actor performing the activities: bending, cycling, lying down, sitting, standing, walking.
3. 3W dataset: The first realistic and public dataset with rare undesirable real events in oil wells.
4. WISDM Smartphone and Smartwatch Activity and Biometrics Dataset : Contains accelerometer and gyroscope time-series sensor data collected from a smartphone and smartwatch as 51 test subjects perform 18 activities for 3 minutes each.
5. Parking Birmingham: Data collected from car parks in Birmingham that are operated by NCP from
Birmingham City Council. UK Open Government Licence (OGL).
6. selfBACK: The SELFBACK dataset is a Human Activity Recognition Dataset of 9
activity classes recorded with two tri-axial accelerometers.