1. MHEALTH Dataset: The MHEALTH (Mobile Health) dataset is devised to benchmark techniques dealing with human behavior analysis based on multimodal body sensing.
2. Behavior of the urban traffic of the city of Sao Paulo in Brazil: The database was created with records of behavior of the urban traffic of the city of Sao Paulo in Brazil.
3. Robot Execution Failures: This dataset contains force and torque measurements on a robot after failure detection. Each failure is characterized by 15 force/torque samples collected at regular time intervals
4. Japanese Vowels: This dataset records 640 time series of 12 LPC cepstrum coefficients taken from nine male speakers.
5. Absenteeism at work: The database was created with records of absenteeism at work from July 2007 to July 2010 at a courier company in Brazil.
6. Dow Jones Index: This dataset contains weekly data for the Dow Jones Industrial Index. It has been used in computational investing research.
7. Hybrid Indoor Positioning Dataset from WiFi RSSI, Bluetooth and magnetometer: The dataset was created for the comparison and evaluation of hybrid indoor positioning methods. The dataset presented contains data from W-LAN and Bluetooth interfaces, and Magnetometer.
8. CNNpred: CNN-based stock market prediction using a diverse set of variables: This dataset contains several daily features of S&P 500, NASDAQ Composite, Dow Jones Industrial Average, RUSSELL 2000, and NYSE Composite from 2010 to 2017.
9. 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.
10. Australian Sign Language signs (High Quality): This data consists of sample of Auslan (Australian Sign Language) signs. 27 examples of each of 95 Auslan signs were captured from a native signer using high-quality position trackers
11. Vicon Physical Action Data Set: The Physical Action Data Set includes 10 normal and 10 aggressive physical actions that measure the human activity. The data have been collected by 10 subjects using the Vicon 3D tracker.
12. Pedestrian in Traffic Dataset: This data-set contains a number of pedestrian tracks recorded from a vehicle driving in a town in southern Germany. The data is particularly well-suited for multi-agent motion prediction tasks.
13. BLE RSSI Dataset for Indoor localization and Navigation: This dataset contains RSSI readings gathered from an array of Bluetooth Low Energy (BLE) iBeacons in a real-world and operational indoor environment for localization and navigation purposes.
14. Spoken Arabic Digit: This dataset contains timeseries of mel-frequency cepstrum coefficients (MFCCs) corresponding to spoken Arabic digits. Includes data from 44 male and 44 female native Arabic speakers.
15. EEG Steady-State Visual Evoked Potential Signals: This database consists on 30 subjects performing Brain Computer Interface for Steady State Visual Evoked Potentials (BCI-SSVEP).
16. Gesture Phase Segmentation: The dataset is composed by features extracted from 7 videos with people gesticulating, aiming at studying Gesture Phase Segmentation. It contains 50 attributes divided into two files for each video.
17. EEG Eye State: The data set consists of 14 EEG values and a value indicating the eye state.
18. UJIIndoorLoc-Mag: The UJIIndoorLoc-Mag is an indoor localization database to test Indoor Positioning System that rely on Earth's magnetic field variations.
19. Buzz in social media : This data-set contains examples of buzz events from two different social networks: Twitter, and Tom's Hardware, a forum network focusing on new technology with more conservative dynamics.
20. Geo-Magnetic field and WLAN dataset for indoor localisation from wristband and smartphone: A multisource and multivariate dataset for indoor localisation methods based on WLAN and Geo-Magnetic ﬁeld ﬁngerprinting
21. Educational Process Mining (EPM): A Learning Analytics Data Set: Educational Process Mining data set is built from the recordings of 115 subjects' activities through a logging application while learning with an educational simulator.
22. Gas sensors for home activity monitoring: 100 recordings of a sensor array under different conditions in a home setting: background, wine and banana presentations. The array includes 8 MOX gas sensors, and humidity and temperature sensors.
23. BitcoinHeistRansomwareAddressDataset: BitcoinHeist datasets contains address features on the heterogeneous Bitcoin network to identify ransomware payments.
24. PAMAP2 Physical Activity Monitoring: The PAMAP2 Physical Activity Monitoring dataset contains data of 18 different physical activities, performed by 9 subjects wearing 3 inertial measurement units and a heart rate monitor.
25. Gas sensor array temperature modulation: A chemical detection platform composed of 14 temperature-modulated metal oxide (MOX) gas sensors was exposed during 3 weeks to mixtures of carbon monoxide and humid synthetic air in a gas chamber.
26. Gas sensor array under dynamic gas mixtures: The data set contains the recordings of 16 chemical sensors exposed to two dynamic gas mixtures at varying concentrations. For each mixture, signals were acquired continuously during 12 hours.
27. Human Activity Recognition from Continuous Ambient Sensor Data: This dataset represents ambient data collected in homes with volunteer residents. Data are collected continuously while residents perform their normal routines.
28. Heterogeneity Activity Recognition: The Heterogeneity Human Activity Recognition (HHAR) dataset from Smartphones and Smartwatches is a dataset devised to benchmark human activity recognition algorithms (classification, automatic data segmentation, sensor fusion, feature extraction, etc.) in real-world contexts; specifically, the dataset is gathered with a variety of different device models and use-scenarios, in order to reflect sensing heterogeneities to be expected in real deployments.
29. WESAD (Wearable Stress and Affect Detection): WESAD (Wearable Stress and Affect Detection) contains data of 15 subjects during a stress-affect lab study, while wearing physiological and motion sensors.