About: A GNSS-Based Crowd-Sensing Strategy for Specific Geographical Areas

Facets (new session)
Description
Metadata
Settings
- owl:sameAs
- Inference Rule:

About: A GNSS-Based Crowd-Sensing Strategy for Specific Geographical Areas Goto Sponge NotDistinct Permalink

An Entity of Type : schema:ScholarlyArticle, within Data Space : covidontheweb.inria.fr associated with source document(s)

Attributes	Values
type	Academic Article research paper schema:ScholarlyArticle
isDefinedBy	Covid-on-the-Web dataset
has title	A GNSS-Based Crowd-Sensing Strategy for Specific Geographical Areas
Creator	Chen, Jong-Shin Hsu, Chi-Yueh Hung, Ruo-Wei Lin, Chuan-Bi
Source	Medline; PMC
abstract	Infectious diseases, such as COVID-19, SARS, MERS, etc., have seriously endangered human safety, economy, and education. During the spread of epidemics, restricting the range of activities of personnel is one of the options for the prevention and treatment of infectious diseases. A global navigation satellite system (GNSS), it can provide accurate coordinates of latitude and longitude to targets with GNSS receivers. However, it is not common to use GNSS coordinates to represent positions in social life. For epidemic management, it is important to know the locations (and addresses) of targets, especially in social life. When there are many targets, it is not easy to efficiently map these coordinates to locations. Therefore, we propose a GNSS-based crowd-sensing strategy for specific geographical areas that can be used to calculate how many targets are in specific geographical areas or whether a target is in a specific area. This strategy is based on the coordinates of latitude and longitude provided by GNSS to find the locations of these coordinates. As simulated data, the data records containing latitude and longitude in a well-known social networking service platform are used. The strategy is also available for mining hot spots or hot areas.
has issue date	2020-07-27(xsd:dateTime)
bibo:doi	10.3390/s20154171
bibo:pmid	32727101
has license	cc-by
sha1sum (hex)	d223f6772437771073e358013944056adbfdf288
schema:url	https://doi.org/10.3390/s20154171
resource representing a document's title	A GNSS-Based Crowd-Sensing Strategy for Specific Geographical Areas
has PubMed Central identifier	PMC7435739
has PubMed identifier	32727101
schema:publication	Sensors (Basel)
resource representing a document's body	covid:d223f6772437771073e358013944056adbfdf288#body_text
is schema:about of	named entity 'map' named entity 'specific' named entity 'common' named entity 'longitude' named entity 'coordinates' named entity 'specific' named entity 'receivers' named entity 'Areas' named entity 'Geographical' named entity 'HOT' named entity 'AVAILABLE' named entity 'ENDANGERED' named entity 'HOW MANY' named entity 'USED' named entity 'longitude' named entity 'Infectious diseases' named entity 'geographical' named entity 'area' named entity 'locations' named entity 'algorithm' named entity 'geographical points' named entity 'PIP' named entity 'algorithm' named entity 'algorithm' named entity 'coordinates' named entity 'records' named entity 'platform' named entity 'data records' named entity 'latitude and longitude' named entity 'hot spots' named entity 'geographical points' named entity 'longitude' named entity 'Cartesian coordinates' named entity 'algorithm' named entity 'latitude' named entity 'error-free' named entity '5.1' named entity 'regular hexagon' named entity 'geographical area' named entity 'GPS receivers' named entity 'latitude' named entity 'spot height' named entity 'L5 band' named entity '5.2' named entity 'Global Positioning' named entity 'Facebook' named entity 'population density' named entity 'longitude' named entity 'Fisher Information' named entity 'GNSS positioning' named entity 'database' named entity 'PIP' named entity 'GPS' named entity 'special municipalities' named entity 'ellipsoidal coordinates' named entity 'population density' named entity 'population density' named entity 'longitude and latitude' named entity 'GNSS' named entity 'geographical points' named entity 'unit area' named entity 'latitude' named entity 'square root' named entity 'Algorithm' named entity 'PEER REVIEW' named entity 'Algorithm' named entity 'east longitude' named entity 'latitude' named entity 'Facebook' named entity 'Cartesian coordinate' named entity 'time signals' named entity 'algorithm' named entity 'latitude and longitude' named entity 'geographical area' named entity 'time complexity' named entity 'access method' named entity 'algorithm' named entity 'Taiwan Island'

Faceted Search & Find service v1.13.91 as of Mar 24 2020

Alternative Linked Data Documents: Sponger | ODE Content Formats:

RDF

ODATA

Microdata

About

OpenLink Virtuoso version 07.20.3229 as of Jul 10 2020, on Linux (x86_64-pc-linux-gnu), Single-Server Edition (94 GB total memory)
Data on this page belongs to its respective rights holders.
Virtuoso Faceted Browser Copyright © 2009-2024 OpenLink Software