Sensors
creating a 3D reconstruction of an object using multiple inward depth sensors that can be imported into any augmented/virtual reality application.
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With the rapid deployment of indoor Wi-Fi networks, Channel State Information (CSI) has been used for device-free occupant activity recognition. However, various environmental factors interfere with the stable propagation of Wi-Fi signals indoors, which causes temporal variation of CSI data. In this study, we investigated temporal CSI variation in a real-world housing environment and its impact on learning-based occupant activity recognition.
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Two dataset collected by USkin tactile sensors for detecting grasping stability and slip detection during lifting objects.
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A reasonable approach to cope with increasing car traffic is the application of large-scale car traffic management solutions. Dense and widely applied car traffic monitoring is an important key prerequisite for this.
Established solutions like e.g. induction loops, video-camera-based systems, or radar, do not suit all the needs with regard to installation effort, privacy, and cost efficiency.
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Screening tools play a vital role in sensory processing disorder detection. The automatic collection of features related to behavioral parameters and the response to given stimuli is possible with the recent technology. Real time stress related health parameters are collected as response to visual stimuli created with experts’ suggestions based on visual sensory processing related questionnaire. Body temperature and heart rate are obtained by smart watch.
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This is the dataset for the letter "NLOS Mitigation Using Residual-Weighted Least-Squares in Wireless Localization"
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Eight participants, sat on a stable chair with no arm rests and a high backrest, with his/her right arm strapped to the passive manipulator. The participant’s motion was simultaneously recorded using a Kinect sensor, an electronic goniometer (Biopac Systems, USA), and a passive marker motion capture system, V120:Trio (OptiTrack, USA). The Kinect sensor was placed 2 m in front and slightly above the participant. The goniometer was attached, using double-sided tape, to the participant’s arm above the elbow. Three reflective markers were used for the V120:Trio recording.
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# RSS data from smartwatch for Contact Tracing
This dataset was collected for the purpose to understand the proximity between any two smartwatches worn by human.
We used the Google's Wear OS based smartwatch, powered by a Qualcomm Snapdragon Wear 3100 processor, from Fossil sport to collect the data.
The smartwatch is powered by a Qualcomm Snapdragon Wear 3100 processor and has an internal memory of up to 1GB.
Two volunteers were required to wear the smartwatch on different hand and stand at a certain distance from each other.
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This file contains VLC RSSI data from the IoRL Measurement campaign.
The processing files included are developed by Ben Meunier from Brunel University London.
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This dataset presents both raw and processed data from testing of two SMF-28 Ultra fibers heated up to 1000 deg. C. The data was collected using an OBR 4600. Benchmark temperatures were collected using thermocouples co-located at points along the fiber. See Readme file.
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