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7 results for “smartphone locations”

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dryad40/100

Data from: Maps made with smartphones highlight lower noise pollution during COVID-19 pandemic lockdown at four locations in Boston

<p>Noise pollution in cities has major negative effects on the health of both humans and wildlife. Using iPhones, we collected sound-level data at hundreds of locations in four areas of Boston, Massachusetts (USA) before, during, and after the fall 2020 pandemic lockdown, during which most people were required to remain at home. These spatially dispersed measurements allowed us to make detailed maps of noise pollution that are not possible when using standard fixed sound equipment. The four sites were: the Boston University campus (which sits between two highways), the Fenway/Longwood area (which includes an urban park and several hospitals), Harvard Square (home of Harvard University), and East Boston (a residential area near Logan Airport). Across all four sites, sound levels averaged 6.4 dB lower during the pandemic lockdown than after. Fewer high noise measurements occurred during lockdown as well. The resulting sound maps highlight noisy locations such as traffic intersections and quiet locations such as parks. This project demonstrates that changes in human activity can reduce noise pollution and that simple smartphone technology can be used to make highly detailed maps of noise pollution that identify sources of high sound levels potentially harmful to humans in urban environments.</p>

opencc-zeroMar 2024View details →
zenodo40/100

Locating undocumented orphaned oil and gas wells with smartphones

<p>Majority of the estimated 3 million abandoned oil and gas wells in the U.S. have missing documents and lack surface equipment making them difficult to locate. However, most of them have casings made of iron alloys which are magnetic and can be sensed by magnetometers. Here we utilize an iPhone 12 mini smartphone as a magnetometer to locate two abandoned wells. We designed a simple unmanned aerial vehicle (UAV) survey setup where the iPhone 12 mini was hung from an inexpensive small drone. We surveyed the two sites by flying the drone at altitudes, 10 m, 15 m, and 20 m above ground level. Our results show that at altitude of 10 magl the smartphone magnetometer could pick the magnetic anomaly of either of the wells at intensities &ge; 52 &mu;T; sufficient to accurately locate the wells. At altitude of 15 magl the smartphone could locate the wells within ~5 m radius of the actual wells&rsquo; location, and it was unable to detect any magnetic anomalies at 20 magl. Simplicity of the setup, minimal required scientific knowledge and low cost of the setup makes this setup an ideal tool for locating orphaned wells by citizen scientists.</p>

opencc-by-4.0Mar 2023View details →
dryad40/100

Data from: Maps made with smartphones highlight lower noise pollution during COVID-19 pandemic lockdown at four locations in Boston

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publicMar 2024View details →
ClinicalTrials.gov36/100

Location-based Smartphone Technology to Guide College Students Healthy Choices Ph II

ClinicalTrials.gov study NCT02996864. IPD Sharing: NO. Countries: 1. Publications: 15.

closedIPD-NOFeb 2026View details →
dryad36/100

Effect of smartphone location on pharmacy students’ attention and working memory

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publicFeb 2024View details →
ClinicalTrials.gov32/100

Impact of a Smartphone Intervention on Tanzanian Women's Childbirth Location

ClinicalTrials.gov study NCT03161184. IPD Sharing: NO. Countries: 0. Publications: 1.

closedIPD-NOFeb 2026View details →
dryad32/100

Dynamic riskscapes for prey: Disentangling the impact of human and cougar presence on deer behavior using GPS smartphone locations

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publicApr 2025View details →

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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.

allen-brain-atlas
neuroscienceopenDocumentation, web resources, and API references are available online.
Last verified 2026-04-30Open record

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.

abode-home-cage
behavioral-neuroscienceopenThe DataShare record exposes download links for annotations, documentation, license text, and the zipped per-snippet data directory.
Last verified 2026-04-30Open record

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.

dandi-nwb
electrophysiologyopenPublished Dandiset metadata and archive endpoints are available through the production DANDI API.
Last verified 2026-04-30Open record

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.

ibl
behavioral-neuroscienceopenPublic sessions can be searched and loaded from the IBL public data server through ONE.
Last verified 2026-04-29Open record

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.

openneuro
neuroscienceopenPublished datasets are available on demand over the internet.
Last verified 2026-04-29Open record