Find research datasets worth reusing
Search datasets from major research repositories and use ShareScore to quickly assess how well each record supports discovery, access, and reuse.
29
datasets available to search
ShareScore release 0.7.1
Dataset results
29 results for “RFID”
Hummingbird foraging patterns across alpine meadows with RFID-equipped feeders in the HJ Andrews Experimental Forest, 2014-2017
Landscape changes can alter pollinator movement and foraging patterns which can in turn influence demographic processes of plant populations. In the Cascade Mountains of the Pacific Northwest, USA, forests are encroaching on alpine meadows that harbor diverse plant and pollinator communities. Whether encroachment and isolation of sub-meadows will influence pollinator foraging behaviors is unknown. To help assess those behaviors, subcutaneous Passive Integrated Transponders were implanted into 163 Rufous Hummingbirds (Selasphorus rufus), common avian pollinators in western North America and four arrays of five hummingbird feeders were established equipped with Radio Frequency Identification data loggers to passively relocate individuals at points throughout the landscape. The feeder arrays were established on four peaks along Frizzel Ridge in the H. J. Andrews Experimental Forest (Lookout Mountain, M1, M2, and Carpenter Mountain). A center feeder was established in a large, central alpine meadow and four satellite feeders c.a. 250m from the center. The satellite feeders were positioned such that at least one was in the open and connected to the center feeder by open habitat, one was in the open but separated from the center by coniferous forest canopy, and one was placed under coniferous forest canopy. Feeders were maintained for 1.5-12 weeks per year from 2014-2017.
Dataset for "A 21 m Operation Range RFID Tag for "Pick to Light" Applications with a Photovoltaic Harvester"
<p>In the paper, a novel Radio-Frequency Identification (RFID) tag for “pick to light” applications is presented. The proposed tag architecture shows the implementation of a novel voltage limiter and a supply voltage (VDD) monitoring circuit to guarantee a correct operation between the tag and the reader for the “pick to light” application. The feasibility to power the tag with different photovoltaic cells is also analyzed, showing the influence of the illuminance level (lx), type of source light (fluorescent, LED or halogen) and type of photovoltaic cell (photodiode or solar cell) on the amount of harvested energy. Measurements show that the photodiodes present a power per unit package area for low illuminance levels (500 lx) of around 0.08 μW/mm<sup>2</sup>, which is slightly higher than the measured one for a solar cell of 0.06 μW/mm<sup>2</sup>. However, solar cells present a more compact design for the same absolute harvested power due to the large number of required photodiodes in parallel. Finally, an RFID tag prototype for “pick to light” applications is implemented, showing an operation range of 3.7 m in fully passive mode. This operation range can be significantly increased to 21 m when the tag is powered by a solar cell with an illuminance level as low as 100 lx and a halogen bulb as source light.</p> <p>This dataset contains some of the data gathered during the experimental work developed and used in the paper.</p>
Data from: Evaluating the foraging performance of individual honey bees in different environments with automated field RFID systems
<p>Measuring the individual foraging performances of pollinators is crucial to guide environmental policies that aim at enhancing pollinator health and pollination services. Automated systems have been developed to track the activity of individual honey bees, but their deployment is extremely challenging. This has limited the assessment of individual foraging performances in full-strength bee colonies in the field. Most studies available to date have been constrained to use downsized bee colonies located in urban and suburban areas. Environmental policy-making, on the other hand, needs a more comprehensive assessment of honey bee performances in a broader range of environments, including in remote agricultural and wild areas. Here we detail a new autonomous field method to record high quality data on the flight ontogeny and foraging performance of honey bees, using Radio-Frequency Identification (RFID). We separate bee traffic into returning and exiting tunnels to improve data quality, solving many previous limitations of RFID systems caused by traffic jams and the parasitic coupling of RFID antennae. With this method, we assembled a large RFID dataset made of control bee colonies from experiments conducted in different locations and seasons. We hope our results will be a starting point to understand how ontogenetic and environmental factors affect the individual performances of honey bees, and that our method will enable the large-scale replication of individual pollinator performance studies.</p>
Passive RFID indoor location dataset
<p>We use four monostatic UHF antennas that operate in the frequency range from 902 to 928 MHz with a 6 dBi gain (isotropic antenna gain) for the implementation environment preparation. The equipment we used to perform the readings was the ThingMagic Mercury 6, a high-performance UHF RFID reader, supporting up to four monostatic antennas, digital inputs and outputs, and a Wi-Fi connection. Both devices are commercially available.</p> <p>We affixed 400 labels to objects placed side by side on the shelves in an auto parts store. The distance between the antennas and tags was 115 cm, and the distance between the antenna group was 250 cm. The reader interrogates the tags every 5 seconds and organizes the input information in a data collection formed by TagID, RSSI, Read Count (RC), True_x, and True_y. This interrogation time was defined by the minimum limit at which all tags were identified at least once by the antenna. In order to carry out data collection, the objects were placed in known positions. We performed 100 readings on each target tag, measuring the RSSI and the RC of each of the four antennas, totaling 40,000 readings. </p>
An Attribute-Based Access Control model in RFID systems based on blockchain Decentralized Applications for healthcare environments (video demonstration)
<p>An Attribute-Based Access Control model in RFID systems based on blockchain Decentralized Applications for healthcare environments.</p>
Data for: Using radio frequency identification (RFID) technology to characterize nest site selection in wild Japanese tits (Parus minor)
<p>Selecting a suitable nest site is critical to the survival and reproduction of birds. Prospecting allows individuals to gather information on the local quality of potential future breeding sites, which may help them make the best nest site selection decision. However, few studies have focused on the direct links between the prospecting activity of breeders and subsequent nest site selection. In this study, we investigated the prospecting pattern of Japanese tits (<em>Parus minor</em>) during the pre-breeding period of the first breeding attempt and whether nest site characteristics influence their nest box visiting behaviour and occupied nest site. We used radio frequency identification (RFID) to track the movements of Japanese tits visiting nest boxes and compared nest site characteristics between visited and unvisited (control) nest boxes, as well as between visited and occupied nest boxes. We found that Japanese tits started visiting nest boxes approximately 20 days before breeding, visited an average of 6 nest boxes and eventually chose the most visited nest box for breeding activities. Japanese tits were more likely to visit nest boxes that had less canopy cover and lower shrub density but a greater total number of surrounding trees and ultimately chose breeding nest boxes with a smaller entrance inclination, in nesting trees with a larger diameter at breast height (DBH) which were surrounded by trees with a larger DBH. Our results suggest that Japanese tits visit several potential breeding sites before choosing breeding nest boxes and that nest site characteristics can influence their prospecting activity and nest site selection.</p>
Data from: Quantifying the impact of crop coverings on honey bee orientation and foraging in sweet cherry orchards using RFID
<p>Advancements in agricultural production have seen the rapid adoption of protected cropping systems globally. Such systems have been optimised for plant growth and efficiency, with little understanding of the potential impacts on key insect pollinators. Here we investigate the effect of netting and polythene rain covers on the health and performance of honey bees (<em>Apis mellifera </em>L.) during the pollination of sweet cherry crops. Over two consecutive seasons, twelve full-strength colonies were equipped with tagged bees and radio frequency identification (RFID) systems. The colonies were equally divided between open control, netted, and polythene (semi-permanent VOEN in 2019 and retractable Cravo in 2020) groups. Over 1,300 individual bees were monitored for the duration of the commercial pollination period to determine behavioural parameters such as foraging commencement age, number and duration of trips, and overall survival. Bees began foraging within the optimum age range (mean 15.7-24.1 days) under all covering types, with little indication of prolonged stress or increased mortality during the short season. Polythene covers (VOEN & Cravo) were found to significantly increase the total time needed for bees to orientate successfully. Once orientated, bees placed under covers conducted up to 155% more foraging trips, with a longer cumulative duration. Covering type was found to significantly impact the amount and type of pollen collected, with the most restrictive system (VOEN) yielding the highest proportion of cherry pollen. Overall, we found little evidence to suggest that protective covers have a detrimental impact on honey bee foraging in cherry crops.</p>
Data for: Using radio frequency identification (RFID) technology to characterize nest site selection in wild Japanese tits (Parus minor)
Open the record for dataset details and reuse information.
Data from: Evaluating the foraging performance of individual honey bees in different environments with automated field RFID systems
Open the record for dataset details and reuse information.
Data from: Quantifying the impact of crop coverings on honey bee orientation and foraging in sweet cherry orchards using RFID
Open the record for dataset details and reuse information.
Electromagnetic Wave Dataset for Strength Degradation Detection in Reinforced Concrete Structures Using RFID Measurements and CNN Model
<p>This dataset comprises 1,800 electromagnetic wave (EM-wave) images collected from three different reinforced concrete beams subjected to varying levels of corrosion. Each image is classified into 'normal' or 'reduced strength' categories based on the beam's structural integrity. Generated through a non-destructive RFID-based monitoring technique, this dataset integrates advanced analyses like 2-D Fourier transforms and fractal dimensions. It is specifically designed to train and validate Convolutional Neural Networks (CNNs) for detecting strength degradation in reinforced concrete structures.</p>
Video-RFID tracking data
<p>Video-RFID tracking raw data for the manuscript:</p> <p><strong>Sex-dependent control of pheromones on social organization within groups of wild house mice </strong></p>
Data from: How to quantify animal activity from radio-frequency identification (RFID) recordings
Automated animal monitoring via radio-frequency identification (RFID) technology allows efficient and extensive data sampling of individual activity levels, and is therefore commonly used for ecological research. However, processing RFID data is still a largely unresolved problem, which potentially leads to inaccurate estimates for behavioural activity. One of the major challenges during data processing is to isolate independent behavioural actions from a set of superfluous, non-independent detections. As a case study, individual blue tits (Cyanistes caeruleus) were simultaneously monitored during reproduction with both video recordings and RFID technology. We demonstrated how RFID data can be processed based on the time spent in- and outside a nest box. We then validated the number and timing of nest visits obtained from the processed RFID dataset by calibration against video recordings. The video observations revealed a limited overlap between the time spent in- and outside the nest box, with the least overlap at 23 seconds for both sexes. We then isolated exact arrival times from redundant RFID registrations by erasing all successive registrations within 23 seconds after the preceding registration. After aligning the processed RFID data with the corresponding video recordings, we observed a high accuracy in three behavioural estimates of parental care (individual nest visit rates, within-pair alternation and synchronization of nest visits). We provide a clear guideline for future studies that aim to implement RFID technology in their research. We argue that our suggested RFID data processing procedure improves the precision of behavioural estimates, despite some inevitable drawbacks inherent to the technology. Our method is useful, not only for other cavity breeding birds, but for a wide range of (in)vertebrate species that are large enough to be fitted with a tag and that regularly pass near or through a fixed antenna.
The OpenFeeder: a flexible automated RFID feeder to measure inter and intraspecies differences in cognitive and behavioral performance in wild birds
<p>Understanding the ecology and evolution of personality and cognition requires the development of new tools to measure individual and species differences in behavioral and cognitive performances in wild populations. Furthermore, such tools should facilitate collection of large sample sizes, evaluate the repeatability of measured traits and allow direct comparison of species performances across a variety of behavioural tasks. Here we present a RFID-based feeder (OpenFeeder) designed to run visual cognitive tasks in wild animals. We illustrate the flexibility of the tool showing performances of three wild passerine species (<em>Parus major</em>, <em>Cyanistes caeruleus</em> and <em>Poecile palustris</em>) in an associative learning task. We recorded performances of a large number of individuals (>300) in the wild and showed both inter and intraspecific differences in associative learning. We also found moderate to high repeatability in individual differences in associative learning in each species. We show that the OpenFeeder is a flexible tool to record performance in multiple cognitive and behavioural tasks in free ranging animals across a variety of passerine species. The design, firmware, and software are open source to facilitate use in a wide variety of species and thus allow continuous improvement of the system and development of new behavioural and cognitive tasks. In doing so, we hope that this tool will be used by a large community of cognitive ecologists and comparative psychologists for both within and across species studies. Furthermore, our system should facilitate replication of results across populations along large-scale environmental gradients to improve our understanding of the role ecology plays in the evolution of cognitive traits.</p>
RFID Location dataset
<p>The dataset includes measurements with a robot equipped with RFID antennas in a library enclosing 7000 tagged books with known locations.</p>
FIGURE 4 in Ultra-small RFID p-Chips on the heads of entomological pins provide an automatic and durable means to track and label insect specimens
FIGURE 4. Schematic of a cap for tagging specimen-bearing pins with p-Chips attached to a piece of ferrite to amplify the transponder response. A: Cross-section; B: Overall view; C: Mounting of the cap on a pin.
FIGURE 1 in Ultra-small RFID p-Chips on the heads of entomological pins provide an automatic and durable means to track and label insect specimens
FIGURE 1. Examples of how labels may be stacked below entomological specimens. Important information may be hidden and difficult to access.
FIGURE 3. a in Ultra-small RFID p-Chips on the heads of entomological pins provide an automatic and durable means to track and label insect specimens
FIGURE 3. a)-c) Schematic representation of p-Chips embedded in an epoxy dome and mounted onto entomological pins. d)- e) Photographs of p-Chip-tagged pins; a view from above the pin head (d), and from the side (e).
Breast Localization: RFID Tags vs Wire Localization
ClinicalTrials.gov study NCT04750889. IPD Sharing: NO. Countries: 1. Publications: 2.
Data from: Patterns of pollen and nectar foraging specialization by bumblebees over multiple timescales using RFID
Open the record for dataset details and reuse information.
ScienceDex guides
Understand access before you commit
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.