1. Activities of Daily Living (ADLs) Recognition Using Binary Sensors: This dataset comprises information regarding the ADLs performed by two users on a daily basis in their
2. 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.
3. DSRC Vehicle Communications: This set Provides data regarding wireless communications between vehicles and road side units. two separate data sets are provided (normal scenario) and in the presence of attacker (jammer).
4. Grammatical Facial Expressions: This dataset supports the development of models that make possible to interpret Grammatical Facial Expressions from Brazilian Sign Language (Libras).
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. UJIIndoorLoc-Mag: The UJIIndoorLoc-Mag is an indoor localization database to test Indoor Positioning System that rely on Earth's magnetic field variations.
7. 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
8. 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.
9. 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.
10. 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.
11. 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.
12. 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.