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26 results for “Indoor Localization”
BLE RSSI Dataset for Indoor localization
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Fig. 76. Normal Q-Q in Indoor Radio Map localization WiFi fingerprint datasets
Fig. 76. Normal Q-Q plot of standardized body length (SBL) for selected Texas Selenophorus species.
WiFi and Bluetooth RSSI SQI Indoor Localization
<h2><strong>Wi-Fi BLE RSSI SQI Localization dataset</strong></h2> <p>Wi-Fi BLE RSSI for positioning / Indoor Localization in <strong>4 different locations</strong> and using <strong>18 different APs</strong></p> <p>Data is only measured at the <strong>Router Side</strong></p> <p>Data is not measured at client side</p> <p>Has <strong>12 datasets</strong> inside the zip folder with over <strong>1,000,000 data points</strong></p> <p>Contains processed Wi-Fi and BLE packets from various routers in: <br>1. University of Victoria, Engineering Office Wing (EOW) <br>2. University of Victoria, Engineering Lab Wing (ELW) <br>3. University of Victoria, Engineering and Computer Science (ECS) <br> <br>Each folder contains a training dataset and a testing dataset that is independent in time and space</p> <p>Router Time is synchronized using chrony</p> <p> </p> <h2><strong>Dataset is in CSV format</strong></h2> <p>Relative Time (seconds) | X Position (meters) | Y Position (meters) | Feature 1 | Feature 2 | Feature 3 ..... <br> <br>Time resets at every new position and position accuracy is a few centimeters using LIDAR and RGBD camera <br> <br> <br>Map is in ROS2 PGM format that can read by ROS2 programs <br> <br> <br>Data for the paper <br> <br>Wi-Fi and Bluetooth Contact Tracing Without User Intervention</p> <p><br><a href="https://ieeexplore.ieee.org/document/9866766" rel="nofollow">https://ieeexplore.ieee.org/document/9866766</a></p> <p> </p> <p>Please Cite As</p> <blockquote> <pre>@article{yuen2022wi, title={Wi-Fi and Bluetooth contact tracing without user intervention}, author={Yuen, Brosnan and Bie, Yifeng and Cairns, Duncan and Harper, Geoffrey and Xu, Jason and Chang, Charles and Dong, Xiaodai and Lu, Tao}, journal={IEEE Access}, volume={10}, pages={91027--91044}, year={2022}, publisher={IEEE} }</pre> </blockquote>
A Soft Range Limited K-Nearest Neighbors Algorithm for Indoor Localization Enhancement
<p>WIFI RSSI Indoor Positioning Dataset</p> <p>A reliable and comprehensive public WiFi fingerprinting database for researchers to implement and compare the indoor localization’s methods.The database contains RSSI information from 6 APs conducted in different days with the support of autonomous robot.</p> <p>We use an autonomous robot to collect the WiFi fingerprint data. Our 3-wheel robot has multiple sensors including wheel odometer, an inertial measurement unit (IMU), a LIDAR, sonar sensors and a color and depth (RGB-D) camera. The robot can navigate to a target location to collect WiFi fingerprints automatically. The localization accuracy of the robot is 0.07 m ± 0.02 m. The dimension of the area is 21 m × 16 m. It has three long corridors. There are six APs and five of them provide two distinct MAC address for 2.4- and 5-GHz communications channels, respectively, except for one that only operates on 2.4-GHz frequency. There is one router can provide CSI information.<br>Data Format</p> <p>X Position (m), Y Position (m), RSSI Feature 1 (dBm), RSSI Feature 2 (dBm), RSSI Feature 3 (dBm), RSSI Feature 4 (dBm), ...</p>
Figs. 51–58 in Indoor Radio Map localization WiFi fingerprint datasets
Figs. 51–58. Habitus images and genitalia illustrations of Selenophorus species. 51–54) S. pararuficollis, new species, dorsal and ventral aspects, male median lobe left lateral and dorsal views; 55–58) S. neoruficollis, new species, dorsal and ventral aspects, male median lobe left lateral and dorsal views.
Figs. 19–28 in Indoor Radio Map localization WiFi fingerprint datasets
Figs. 19–28. Habitus images, genitalia illustrations, and SEMs of Selenophorus species. 19) S. hylacis, dorsal aspect; 20) S. intermedius, dorsal aspect; 21) S. mexicanus, dorsal aspect; 22) S. subquadratus, dorsal aspect; 23–28) S. balli, new species, dorsal and ventral aspects, male median lobe left lateral and dorsal views, and SEM images of pronotum and elytral striae showing setigerous puncture.
ScienceDex guides
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.