1. 3D Road Network (North Jutland, Denmark): 3D road network with highly accurate elevation information (+-20cm) from Denmark used in eco-routing and fuel/Co2-estimation routing algorithms.
2. EEG Eye State: The data set consists of 14 EEG values and a value indicating the eye state.
3. Hill-Valley: Each record represents 100 points on a two-dimensional graph. When plotted in order (from 1 through 100) as the Y co-ordinate, the points will create either a Hill (a “bump” in the terrain) or a Valley (a “dip” in the terrain).
4. Libras Movement: The data set contains 15 classes of 24 instances each. Each class references to a hand movement type in LIBRAS (Portuguese
name 'LÍngua BRAsileira de Sinais', oficial brazilian signal language).
5. 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.
6. Online Handwritten Assamese Characters Dataset: This is a dataset of 8235 online handwritten assamese characters. The â€śonlineâ€ť process involves capturing of data as text is written on a digitizing tablet with an electronic pen.
7. Ozone Level Detection: Two ground ozone level data sets are included in this collection. One is the eight hour peak set (eighthr.data), the other is the one hour peak set (onehr.data). Those data were collected from 1998 to 2004 at the Houston, Galveston and Brazoria area.
8. QtyT40I10D100K: Since there is no numerical sequential data stream available in standard data sets, this data set is generated from the original T40I10D100K data set
9. UJI Pen Characters: Data consists of written characters in a UNIPEN-like format
10. UJI Pen Characters (Version 2): A pen-based database with more than 11k isolated handwritten characters
11. Wall-Following Robot Navigation Data: The data were collected as the SCITOS G5 robot navigates through the room following the wall in a clockwise direction, for 4 rounds, using 24 ultrasound sensors arranged circularly around its 'waist'.
12. Wearable Computing: Classification of Body Postures and Movements (PUC-Rio): A dataset with 5 classes (sitting-down, standing-up, standing, walking, and sitting) collected on 8 hours of activities of 4 healthy subjects. We also established a baseline performance index.