Real-life application based datasets

Overview: Real-life datasets (in engineering, health sciences, etc..) are pressingly needed to fully explore the disruptive potential of IoFT and allow it to infiltrate different fields. Below we list existing ones.

  • FedIoT: FL for Internet of Things (IoT) datasets – 2021
    Description: Due to the heterogeneity, diversity, and personalization of IoT networks, Federated Learning (FL) has a promising future in the IoT cybersecurity field. As a result, we present the FedIoT, an open research platform and benchmark to facilitate FL research in the IoT field. In particular, we propose an autoencoder based trainer to IoT traffic […]

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  • Wind Energy Datasets – 2020
    Description: This dataset is based on the book: Data Science for Wind Energy. A  group of datasets collected from differnt inland and offshore windfarms and collects wind time-series data. Here each windfarm may acts as an client in a federated scenario. Link to Dataset […]

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  • Federated Desktop 3D printers – 2021
    Description: This dataset presents the relationships between the average nominal speed and the average measured acceleration for six identical printers (Ender 3 Pro) air printing cubes with size 20 × 20 × 3mm. For each print, the layer height is 0.2mm (i.e., each print has 15 layers), and a five-second pause is commanded between each […]

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  • UCL-Smartphone Dataset – 2016
    Description: The dataset is derived by carrying out experiments with a group of 30 volunteers within an age bracket of 19-48 years. Each person performed six activities (WALKING, WALKING_UPSTAIRS, WALKING_DOWNSTAIRS, SITTING, STANDING, LAYING) wearing a smartphone (Samsung Galaxy S II) on the waist. Using its embedded accelerometer and gyroscope,  3-axial linear acceleration and 3-axial angular […]

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  • BraTS Dataset – 2018
    Description: BraTS 2018 is a dataset that is commonly used in the healthcare landscape. It provides multimodal 3D brain MRIs and ground truth brain tumor segmentations annotated by physicians, consisting of 4 MRI modalities per case (T1, T1c, T2, and FLAIR). Annotations include 3 tumor sub-regions—the enhancing tumor, the peritumoral edema, and the necrotic and […]

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