Sensors
With the rapid pace of global urbanization and rising energy demands, efficient gas leak detection is vital for public safety. This study proposes an efficient and sensitive gas leak detection method based on reinforcement learning to enhance localization speed and robustness. The approach includes critical area identification, reinforcement learning model training, and leak point localization. Simultaneously introducing noise and missing data to test the robustness of the model.
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53 Views
In this dataset, we present a novel RGB-Thermal paired dataset, RGBT-1K, comprising 1,000 image pairs specifically curated to support research in multi-modality image processing. The dataset captures diverse indoor and outdoor scenes under varying lighting conditions, offering a robust benchmark for applications in image enhancement, object detection, and scene analysis. The image acquisition process involved using the FLIR A70 thermal camera and the Sony Handycam HDR-CX405, with the latter positioned atop the thermal camera for precise alignment.
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436 Views
Interference signals degrade and disrupt Global Navigation Satellite System (GNSS) receivers, impacting their localization accuracy. Therefore, they need to be detected, classified, and located to ensure GNSS operation. State-of-the-art techniques employ supervised deep learning to detect and classify potential interference signals. We fuse both modalities only from a single bandwidth-limited low-cost sensor, instead of a fine-grained high-resolution sensor and coarse-grained low-resolution low-cost sensor.
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445 Views
Jamming devices pose a significant threat by disrupting signals from the global navigation satellite system (GNSS), compromising the robustness of accurate positioning. Detecting anomalies in frequency snapshots is crucial to counteract these interferences effectively. The ability to adapt to diverse, unseen interference characteristics is essential for ensuring the reliability of GNSS in real-world applications. We recorded a dataset with our own sensor station at a German highway with eight interference classes and three non-interference classes.
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201 Views
Multimodal sensor fusion has been widely adopted in constructing scene understanding, perception, and planning for intelligent robotic systems. One of the critical tasks in this field is geospatial tracking, i.e., constantly detecting and locating objects moving across a scene. Successful development of multimodal sensor fusion tracking algorithms relies on large multimodal datasets where common modalities exist and are time-aligned, and such datasets are not readily available.
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699 Views
This dataset originates from a longitudinal study examining the factors contributing to the progression of cardiovascular disease. P This particular research employs the unprocessed sequential actigraph recordings collected from an actigraph device. We evaluate sleep quality based on the two indicators as proposed in our previous study [3] which are weekly sleep quality ‘SleepQualWeek’, and sleep consistency ‘SleepCons’. SleepQualWeek and SleepCons are calculated using the pre-processed attribute set derived from the MESA dataset.
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223 Views
In the domain of gait recognition, the scarcity of non-simulated, real-world data significantly hampers the performance and applicability of recognition systems. To address this limitation, we present a comprehensive gait recognition dataset - GaitMotion- collected using built-in sensors of Android smartphones in an uncontrolled, real-world environment. This dataset captures the walking activity of 24 subjects (14 females and 10 males) above 18 years old and weighing at least 50 kg.
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290 Views
Well logs are interpreted/processed to estimate the in-situ reservoir properties (petrophysical, geomechanical, and geochemical), which is essential for reservoir modeling, reserve estimation, and production forecasting. The modeling is often based on multi-mineral physics or empirical formulae. When sufficient amount of training data is available, machine learning solution provides an alternative approach to estimate those reservoir properties based on well log data and is usually with less turn-around time and human involvements.
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190 Views
This dataset comprises a range of features, including time slots, device IDs, geographic coordinates (x, y), energy consumption, uplink history, emergency status, QoS pool identifiers, data flags, resource IDs, and data sizes. The device locations are modeled using a Poisson distribution with a spread of \(100\) meters within a \(500 \times 500\) meter area. The uplink history, QoS pool assignments, and data flags are derived from the probabilities of data availability and priority values.
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358 Views
This video demonstrates the real-time data acquisition and noise reduction capabilities of a CMOS capacitive sensor array (CSA) implemented on an FPGA. The system captures the evaporation process of a deionized water droplet placed on the sensor array, using multiple sampling (MS) and pixel-wise accumulation (PWA) techniques to enhance signal quality and reduce random noise. The system efficiently processes and transmits the data, showcasing the gradual reduction in the droplet's size as it evaporates.
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112 Views