Sensors

Dataset of a smart insole that are used to estimating stride length. Eight participants wore a pair of smart insoles and Gait Up. For a period of six minutes, each participant walked back and forth on a predefined 20-meter pathway in the indoor setting, and the numbers of round trips and strides taken were counted. The smart insole is equipped of five pressure sensors and one 3D accelerometer. The actual total distance was calculated by multiplying the number of round trips by 40 meters.

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39 Views

This is the dataset related to the article "Machine-learning-based Colorimetric Sensor on Smarthone for Salivary Uric Acid Detection". The dataset contains two types of images. The first type is the full-sized image captured by the sensor, which is used to evaluate the performance of the ROI detection. The second type is the reaction area from artificial saliva and clinical samples, which is used to train and test machine-learning models. 

 

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92 Views

AirIoT is a temporal dataset of air pollution concentration values measured for almost three years in Hyderabad, India. In AirIoT, a dense network of IoT-based PM monitoring devices equipped with low-cost sensors was deployed. The research focuses on two primary aspects: measurement and modelling. The team developed, calibrated, and deployed 50 IoT-based PM monitoring devices throughout Hyderabad, India, covering urban, semi-urban, and green areas.

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166 Views

This dataset consists of inertial, force, color, and LiDAR data collected from a novel sensor system. The system comprises three Inertial Measurement Units (IMUs) positioned on the waist and atop each foot, a color sensor on each outer foot, a LiDAR on the back of each shank, and a custom Force-Sensing Resistor (FSR) insole featuring 13 FSRs in each shoe. 20 participants wore this sensor system whilst performing 38 combinations of 11 activities on 9 different terrains, totaling over 7.8 hours of data.

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26 Views

Mechanical Scanning Sonars (MSS) are popular underwater sensors for Unmanned Underwater Vehicles (UUV) due to their low cost, small size, and low power consumption. But due to their simplicity, there are also many research challenges related to their usage.  Unfortunately, there is also a lack of data with ground truth UUV localization. We provide MSS datasets using a UUV with standard navigation sensors, i.e., an Inertial Measurement Unit (IMU) and a Doppler Velocity Log (DVL).

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132 Views

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The data was collected by outfitting one of the players with the experimental balloon, which incorporated the embedded circuit and sensors. The sensors positioned at the top-right to the player within the bubble balloon, where a player stand inside. The sensors' data  were collected at specific sampling frequencies (Accelerometer: 1000Hz, Gyroscope: 1000Hz, and Pressure: 40Hz). The experiment was conducted involving five different players. This approach allowed for the inclusion of diverse data samples, taking into account variations in player metrics, movements, and gameplay dynamics.

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77 Views

This share presents raw data and Python source code for signal processing in overflow velocity measurement using millimeter-wave MIMO-FMCW radar on a fabricated real-scale pseudo embankment. The dataset and code offer insights into developing robust river embankments, crucial for mitigating failures during heavy rains in Japan. The methodology involves constructing a pseudo embankment recommended by the Ministry of Land, Infrastructure, Transport, and Tourism (MLIT) for technology validation.

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201 Views

Laser-vision system (LVS), which provides the effective sensing of weld seams, is widely used in robotic welding. Due to the harsh visual noise during the welding process, the accurate real-time detection of weld seams is difficult. Since the optical propagation of the laser is affected by the arc light, the traditional passive vision system (PVS) filtering method for detecting weld seams is not applicable. This paper exploits the selection of an optimal imaging band for the LVS to eliminate the arc noise.

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129 Views

This dataset abstract presents findings from a study focused on enhancing surface crack detection in railroad safety through the development and optimization of a hybrid Eddy Current Testing (ECT) probe. Traditional ECT methods often encounter challenges related to 'lift-off noise', which arises from variations in probe-to-material distances. To mitigate this issue, the study introduces a novel probe design that integrates transmit and differential receiver coils, aimed at improving detection sensitivity and minimizing lift-off impact.

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31 Views

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