1. 3W dataset: The first realistic and public dataset with rare undesirable real events in oil wells.
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. Bar Crawl: Detecting Heavy Drinking: Accelerometer and transdermal alcohol content data from a college bar crawl. Used to predict heavy drinking episodes via mobile data.
4. Bar Crawl: Detecting Heavy Drinking: Accelerometer and transdermal alcohol content data from a college bar crawl. Used to predict heavy drinking episodes via mobile data.
5. Basketball dataset: It's data collected from different volunteers that are done in a basketball practice: dribbling, pass, shoot, picking the ball, and holding the ball.
6. Individual household electric power consumption: Measurements of electric power consumption in one household with a one-minute sampling rate over a period of almost 4 years. Different electrical quantities and some sub-metering values are available.
7. 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.
8. Localization Data for Person Activity: Data contains recordings of five people performing different activities. Each person wore four sensors (tags) while performing the same scenario five times.
9. Machine Learning based ZZAlpha Ltd. Stock Recommendations 2012-2014: The data here are the ZZAlpha® machine learning recommendations made for various US traded stock portfolios the morning of each day during the 3 year period Jan 1, 2012 - Dec 31, 2014.
10. Parking Birmingham: Data collected from car parks in Birmingham that are operated by NCP from
Birmingham City Council. UK Open Government Licence (OGL).
11. selfBACK: The SELFBACK dataset is a Human Activity Recognition Dataset of 9
activity classes recorded with two tri-axial accelerometers.
12. Taxi Service Trajectory - Prediction Challenge, ECML PKDD 2015: An accurate dataset describing trajectories performed by all the 442 taxis running in the city of Porto, in Portugal.
13. 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.