Sensors
Can we perceive the three-dimensional posture of the whole human body solely from extremely low-resolution thermal images (e.g., $8\times8$-pixels)?
This paper investigates the possibility of this challenging task.
Thermal images capture only the intensity of radiation, making them less likely to contain personal information such as facial or clothing features.
Thermal sensors are commonly integrated into daily-use appliances, such as air conditioners, automatic doors, and elevators.
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4 Views
GNSS-R Data for the paper: First Shipborne GNSS-R Ultra-long Observation Utilizing Oceangoing Freighter
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7 Views
As essential load-bearing components, the reliability of cables directly influences the safety of engineering structures. Online monitoring of cable tensions' enhances structural reliability and enables engineers to regulate stresses, extending the operational lifespan of cable systems. This study proposes A half-type cable tension sensor (HCTS) based on triboelectric nanogenerators. The HCTS features an internal sensing unit comprising conductive fabrics and silicone films.
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16 Views
The SDUITC database is a multi-modal resourse developed at the Shandong Cooperative Vehicle-Infrastructure Test Base, which uses roadside cameras and LiDAR to monitor road targets and collect point cloud information. Following ground segmentation (target point cloud extraction), target identification and tracking, and feature extraction, the target point cloud information is refined and summarized into the following content: 1. Video snapshot of the captured target; 2. Point cloud clustering information for the target; 3. Feature tables.
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101 Views
Repeated Route Naturalistic Driving Dataset (R2ND2) is a dual-perspective dataset for driver behavior analysis constituent of vehicular data collected using task-specific CAN decoding sensors using OBD port and external sensors, and (b) gaze-measurements collected using industry-standard multi-camera gaze calibration and collection system. Our experiment is designed to consider the variability associated with driving experience that depends on the time of day and provides valuable insights into the correlation of these additional metrics on driver behavior.
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210 Views
In this study, MMW data are collected using a commercial handheld scanner (Vayyar's ECS2000), focusing on localized scans of the human body. The collected data are complex-valued (CV) high-resolution local 3D pseudo-images over a volume of 13×13×10 cm with spatial resolutions of 1.6 mm, 1.6 mm, and 4.3 mm in the x, y, and z directions, respectively. The compact, portable ECS2000 Vayyar's MMW scanner is built around a single RF board working in the frequency range of [60.4-69.9] GHz, housing transmitting and receiving antennas in a multiple-input multiple-output (MIMO) setup.
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93 Views
The dataset used in paper Ke Ma et al. , A Dynamic Landslide Warning Model based on Grey System Theory.
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25 Views
Six flexible piezoelectric sensors were evenly attached around the patella of the knee joint to capture patellar motion signals during the knee flexion process. This dataset includes data from three distinct participant groups categorized by knee joint health status. The healthy group consists of 27 participants with normal knee joints (10 females). The subhealthy group includes 15 participants from Beihang University experiencing mild knee discomfort (8 females).
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27 Views
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.
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85 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.
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360 Views