Sensors
Industrial Internet of Things (IIoTs) are high-value cyber targets due to the nature of the devices and connectivity protocols they deploy. They are easy to compromise and, as they are connected on a large scale with high-value data content, the compromise of any single device can extend to the whole system and disrupt critical functions. There are various security solutions that detect and mitigate intrusions.
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This is the calibration procedure and experimental data of a 4PPa-2PaR parallel mechanism, main_simulation.m and main_experiment.m are simulation and experimental programs, respectively, and end_measurement.xlsx is the experimental data measured by the laser tracker
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This dataset consists of measurements from a foot-mounted inertial measurement unit (IMU). In total, we provide data from five different test subjects travelling over more than 7.6 km. The data are combined with various forms of ground truth positioning information that can be used to evaluate the accuracy of a zero-velocity-aided, foot-mounted inertial navigation system (INS).
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Clamp-on ultrasonic transit time difference is used extensively to calculate the volumetric flow rate of a fluid through a pipe. The operating principle is that waves travelling along a path that is generally against the flow direction take longer to travel the same path than waves travelling along the same path in the opposite direction. The transit time difference between the waves travelling in opposite directions can be used to calculate the flow rate through the pipe, by applying suitable mathematical correction factors.
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The uploaded data are for the paper: "A Wearable Skin Temperature Monitoring System for Early Detection of Infections". Baseline kin temperature measurement data from all 5 volunteers (subjects) who wore the wearable band for 3-5 days are included along with 5-day temperature measurement data with anomalies of one volunteer who wore both the smart band and a heating pad. Augmented data generated using the methods described in the paper for COVID-19 infection anomaly detection are also included
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Packet delivery ratio data collected for the article Wireless-Sensor Network Topology Optimization in Complex Terrain: A Bayesian Approach. Published in the IEEE Internet of Things Journal.
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<p>The technique of electrical impedance tomography (EIT) has been recognized as a promising method to design tactile sensors with continuous sensing capability over a large area. The mechanism of electrical impedance tomography allows reconstructing tactile information within the sensing area based on measurements made only at the boundary. However, spatial performance of EIT-based tactile sensors has demonstrated location dependency in previous reports, which severely affects correct interpretation of tactile stimuli.
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This study presents a dataset that comprises the magnetic field, Wi-Fi, and the data from the inertial measurement unit (IMU) sensors of the smartphone including accelerometer, gyroscope, and barometer. First, the important
characteristics of both the Wi-Fi and the magnetic field that require further investigation are highlighted, and later the data are collected. The data are collected over a longer period spanning approximately five years involving five
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The data set is collected using Neurosky MindWave 2.0 Headset. It uses a single dry electrode placed at FP-1 position for the acquisition of EEG signals. The data is collected from Healthy Individuals and Epileptic Patients performing different Activities of Daily Living (ADLs) in an unconstraint environment.
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