IoT

This peach tree disease detection dataset is a multimodal, multi-angle dataset which was constructed for monitoring the growth of peach trees, including stress analysis and prediction. An orchard of peach trees is considered in the area of Thessaly, where 889 peach trees were recorded in a full crop season starting from Jul. 2021 to Sep. 2022. The dataset includes a) aerial / Unmanned Aerial Vehicle (UAV) images, b) ground RGB images/photos, and c) ground multispectral images/photos.

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In the digital era of the Industrial Internet of Things (IIoT), the conventional Critical Infrastructures (CIs) are transformed into smart environments with multiple benefits, such as pervasive control, self-monitoring and self-healing. However, this evolution is characterised by several cyberthreats due to the necessary presence of insecure technologies. DNP3 is an industrial communication protocol which is widely adopted in the CIs of the US. In particular, DNP3 allows the remote communication between Industrial Control Systems (ICS) and Supervisory Control and Data Acquisition (SCADA).

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This dataset is a collection of phase samples retrieved from an in-house design for a Bluetooth Low Energy (BLE) 5.1 based receiver, using an 8-element Uniform Circular Array (UCA). The purpose of the dataset was the implementation of localization techniques based on the use of Angle-of-Arrival data, possible due to the BLE 5.1 Direction Finding (DF) features.

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The Research Paper "Detection of Bicep Form Using Myoware and Machine Learning" based on the novel dataset has been recently accepted in September 2022 and is being published in SCOPUS Indexed SPRINGER Book Series “Lecture Notes in Networks and Systems”

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A real-world radio frequency (RF) fingerprinting dataset for commercial off-the-shelf (COTS) Bluetooth and WiFi emitters under challenging testbed setups is presented in this dataset. The chipsets within the devices (2 laptops and 8 commercial chips) are WiFi-Bluetooth combo transceivers. The emissions are captured with a National Instruments Ettus USRP X300 radio outfitted with a UBX160 daughterboard and a VERT2450 antenna. The receiver is tuned to record a 66.67 MHz bandwidth of the spectrum centered at the 2.414 GHz frequency.

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The Bluetooth 5.1 Core Specification brought Angle of Arrival (AoA) based Indoor Localization to the Bluetooth Standard. This feature is usually referred to as Bluetooth Direction Finding.Technically, the Direction Finding is done by adding a so-called Constant Tone Extension (CTE) to a Bluetooth packet. During this CTE, either transmitter or receiver can switch through several antennas of an antenna array while IQ data, i.e. amplitude and phase information, is sampled on the receiving side. Using these IQ samples, the direction(s) of the incident wavefronts can be estimated.

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Federated learning (FL), as a privacy-preserving distributed machine learning algorithm is being rapidly applied in wireless communication networks, which enables IoT clients to obtain well-trained models while keeping data local.

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The dataset contains the data collected using an Arduino Nano 33 BLE Sense for several classification tasks: color detection, keyword spotting, sound frequency recognition, vibration pattern detection, hand-gesture recognition, and vibration intensity detection. 

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