Sensors
This ZIP file contains two distinct datasets collected over a 14-day period. The first dataset consists of real-world smart home data, providing detailed logs from six devices: a Plug Fan, Plug PC, Humidity Sensor, Presence Sensor, Light Bulb, and Window Opening Sensor. The data includes device interactions and environmental conditions such as temperature, humidity, and presence. The second dataset is generated by a smart home simulator for the same period, offering simulated device interactions and environmental variables.
- Categories:
20 Views
In this dataset, a human detecting model using with UWB radar technology is presented. Two distinct datasets were created using the UWB radar device, leveraging its dual features. Data collection involved two main scenarios, each containing multiple sub-scenarios. These sub-scenarios varied parameters like the position, distance, angle, and orientation of the human subject relative to the radar. Unlike conventional approaches that rely on signal processing or noise/background removal, this study uniquely emphasizes analyzing raw UWB radar data directly.
- Categories:
194 Views
The bottom anode in the Direct Current Electric Arc Furnace (DC EAF) is critical for completing the electrical circuit necessary for sustaining the arc within the furnace. For pin-type bottom anodes, monitoring of the temperature of select pins instrumented with thermocouples is performed to track bottom wear in the EAF and inform the operator when the furnace should be removed from service.
- Categories:
8 Views
A multimodal dataset is presented for the cognitive fatigue assessment of physiological minimally invasive sensory data of Electrocardiography (ECG) and Electrodermal Activity (EDA) and self-reporting scores of cognitive fatigue during HRI. Data were collected from 16 non-STEM participants, up to three visits each, during which the subjects interacted with a robot to prepare a meal and get ready for work. For some of the visits, a well-established cognitive test was used to induce cognitive fatigue.
- Categories:
40 Views
High-frequency transmission spectroscopy (HFTS) is a novel technique for the classification of a wide range of materials in biomedical, environmental, security, and manufacturing domains. HFTS is based on the fusion of scattering parameter measurements and machine learning classification techniques to identify materials of interest in novel environments. This work seeks to demonstrate the efficacy of HFTS in the domain of integrated circuit classification.
- Categories:
72 Views
ZJT datasets: It was collected from the production line of China Tobacco Zhejiang Industrial Company. The data was sampled every two seconds for a week from 162 sensors deployed on a variety of production devices (e.g., paper cut-ting wheel, power supply, etc.). Since ZJT is a dataset from real-world production line, it does not contain serious anoma-lies from accidents or attacks. Thus, we treat the states of transforming between different producing modes as anoma-lies. The ratio of normal states to abnormal states is 4:1.
- Categories:
15 Views
This study introduces a novel soil texture dataset designed to overcome geographic constraints and improve the generalization of classification models. Using the USDA soil classification triangle as a framework, the dataset is systematically generated by combining pure sand, silt, and clay in varying proportions to create diverse soil texture classes. The soil mixtures are captured using a multispectral sensor with seven bands, ensuring a rich representation of spectral information.
- Categories:
60 Views
This study identifies representative sensors for monitoring fan performance by analyzing vibration data collected from piezoelectric sensors during various operational modes. The dataset, which includes measurements at a rate of 300 samples/sec from 10 sensors, covers six modes of operation: Maximum Speed, Maximum Speed with Oscillation, Minimum Speed, Minimum Speed with Oscillation, Minimum to Maximum Speed, and a comprehensive dataset combining all modes.
- Categories:
58 Views
A method of broadening frequency bandwidth and improving sensitivity of a Fabry-Pérot (F-P) geophone is proposed, and the corresponding high-performance device is designed and demonstrated experimentally.
- Categories:
7 Views
The data is collected from the deployed IoT sensor node at a pilot farm in Narrabri, Australia. The dataset includes information about soil characteristics such as soil moisture and soil temperature at 20-40-60 cm depth. The sensor node also provides information about environmental influencers, which are critical in constructing machine learning models to predict Evapotranspiration in diverse soil and environmental conditions.
- Categories:
458 Views