1. Grammatical Facial Expressions: This dataset supports the development of models that make possible to interpret Grammatical Facial Expressions from Brazilian Sign Language (Libras).
2. UJI Pen Characters: Data consists of written characters in a UNIPEN-like format
3. UJI Pen Characters (Version 2): A pen-based database with more than 11k isolated handwritten characters
4. detection_of_IoT_botnet_attacks_N_BaIoT: This dataset addresses the lack of public botnet datasets, especially for the IoT. It suggests *real* traffic data, gathered from 9 commercial IoT devices authentically infected by Mirai and BASHLITE.
5. 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'.
6. Online Handwritten Assamese Characters Dataset: This is a dataset of 8235 online handwritten assamese characters. The “online” process involves capturing of data as text is written on a digitizing tablet with an electronic pen.
7. Kitsune Network Attack Dataset: A cybersecurity dataset containing nine different network attacks on a commercial IP-based surveillance system and an IoT network. The dataset includes reconnaissance, MitM, DoS, and botnet attacks.
8. 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.
9. UJIIndoorLoc-Mag: The UJIIndoorLoc-Mag is an indoor localization database to test Indoor Positioning System that rely on Earth's magnetic field variations.
10. 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.
11. 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.
12. 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.
13. 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
14. 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.
15. 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.
16. microblogPCU: MicroblogPCU data is crawled from sina weibo microblog[http://weibo.com/]. This data can be used to study machine learning methods as well as do some social network research.
17. Parking Birmingham: Data collected from car parks in Birmingham that are operated by NCP from
Birmingham City Council. UK Open Government Licence (OGL).
18. 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.
19. 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.
20. BLE RSSI dataset for Indoor localization: This dataset contains RSSIs obtained on smartphones(Sony Xperia XA1). Signals were transmitted from BLE product called iTAG. Location column denotes the position of iTAG in building's entry.