Ontology type: schema:ScholarlyArticle
2019-05
AUTHORSZhang Yong, Zhang Liyi, Han Jianfeng, Ban Zhe, Yang Yi
ABSTRACTGas leakage source localization based on sensor networks has an important practical significance in many fields such as environmental monitoring, security protection and pollution control. This paper proposed a gas leakage source localization algorithm using distributed maximum likelihood estimation method for mobile sensor network to improve the lower performance with static sensor network. Firstly, the likelihood function of gas leakage source parameters was deduced based on the gas turbulent diffusion model. Then, the parameters of gas leakage source were estimated based on the likelihood function with the gas concentration measurement in environment. Finally, the gas leakage source location would be achieved through the iterative optimization of the likelihood function. The preliminary experimental results show that the proposed distributed Maximum Likelihood Estimation method could be achieved an acutely gas leakage source location in an indoor environment. And the reasonable path planning and dynamic topology changing could improve the positioning performance. More... »
PAGES1703-1712
http://scigraph.springernature.com/pub.10.1007/s12652-017-0624-z
DOIhttp://dx.doi.org/10.1007/s12652-017-0624-z
DIMENSIONShttps://app.dimensions.ai/details/publication/pub.1092854697
JSON-LD is the canonical representation for SciGraph data.
TIP: You can open this SciGraph record using an external JSON-LD service: JSON-LD Playground Google SDTT
[
{
"@context": "https://springernature.github.io/scigraph/jsonld/sgcontext.json",
"about": [
{
"id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/0906",
"inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/",
"name": "Electrical and Electronic Engineering",
"type": "DefinedTerm"
},
{
"id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/09",
"inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/",
"name": "Engineering",
"type": "DefinedTerm"
}
],
"author": [
{
"affiliation": {
"alternateName": "Tianjin University of Commerce",
"id": "https://www.grid.ac/institutes/grid.464478.d",
"name": [
"The College of Information, Tianjin University of Commerce, 300134, Tianjin, China"
],
"type": "Organization"
},
"familyName": "Yong",
"givenName": "Zhang",
"id": "sg:person.012154156372.25",
"sameAs": [
"https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.012154156372.25"
],
"type": "Person"
},
{
"affiliation": {
"alternateName": "Tianjin University of Commerce",
"id": "https://www.grid.ac/institutes/grid.464478.d",
"name": [
"The College of Information, Tianjin University of Commerce, 300134, Tianjin, China"
],
"type": "Organization"
},
"familyName": "Liyi",
"givenName": "Zhang",
"id": "sg:person.010335742143.37",
"sameAs": [
"https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.010335742143.37"
],
"type": "Person"
},
{
"affiliation": {
"alternateName": "Tianjin University of Commerce",
"id": "https://www.grid.ac/institutes/grid.464478.d",
"name": [
"The College of Information, Tianjin University of Commerce, 300134, Tianjin, China"
],
"type": "Organization"
},
"familyName": "Jianfeng",
"givenName": "Han",
"type": "Person"
},
{
"affiliation": {
"alternateName": "Tianjin University of Commerce",
"id": "https://www.grid.ac/institutes/grid.464478.d",
"name": [
"The College of Information, Tianjin University of Commerce, 300134, Tianjin, China"
],
"type": "Organization"
},
"familyName": "Zhe",
"givenName": "Ban",
"id": "sg:person.014344477772.19",
"sameAs": [
"https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.014344477772.19"
],
"type": "Person"
},
{
"affiliation": {
"alternateName": "Tianjin University of Commerce",
"id": "https://www.grid.ac/institutes/grid.464478.d",
"name": [
"The College of Information, Tianjin University of Commerce, 300134, Tianjin, China"
],
"type": "Organization"
},
"familyName": "Yi",
"givenName": "Yang",
"id": "sg:person.015142060372.26",
"sameAs": [
"https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.015142060372.26"
],
"type": "Person"
}
],
"citation": [
{
"id": "https://doi.org/10.1155/2016/2080536",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1003515112"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1016/j.atmosenv.2016.06.046",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1004555705"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1016/j.ijggc.2012.04.001",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1008420569"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1016/j.sigpro.2009.10.006",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1009788014"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1016/j.atmosenv.2006.08.044",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1013121079"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1016/j.inffus.2016.11.010",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1026127830"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1016/j.atmosenv.2017.01.014",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1026908860"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1155/2014/271547",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1032806258"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1016/j.atmosenv.2008.05.024",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1035461869"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1007/s10514-011-9219-2",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1038390013",
"https://doi.org/10.1007/s10514-011-9219-2"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1016/j.atmosenv.2013.02.051",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1041288646"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1016/j.envsoft.2010.01.006",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1048822926"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1021/es202807s",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1055503647"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1109/access.2016.2550033",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1061252232"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1109/lsp.2009.2016481",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1061377431"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1109/taes.2013.110499",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1061485945"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1109/tii.2015.2397879",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1061632588"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1109/tsp.2006.885770",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1061800325"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1109/tsp.2006.889975",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1061800408"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1109/tsp.2014.2302746",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1061804242"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1109/tsp.2014.2385039",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1061804672"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1109/access.2017.2695232",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1084948308"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1109/icsens.2007.355495",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1095167109"
],
"type": "CreativeWork"
}
],
"datePublished": "2019-05",
"datePublishedReg": "2019-05-01",
"description": "Gas leakage source localization based on sensor networks has an important practical significance in many fields such as environmental monitoring, security protection and pollution control. This paper proposed a gas leakage source localization algorithm using distributed maximum likelihood estimation method for mobile sensor network to improve the lower performance with static sensor network. Firstly, the likelihood function of gas leakage source parameters was deduced based on the gas turbulent diffusion model. Then, the parameters of gas leakage source were estimated based on the likelihood function with the gas concentration measurement in environment. Finally, the gas leakage source location would be achieved through the iterative optimization of the likelihood function. The preliminary experimental results show that the proposed distributed Maximum Likelihood Estimation method could be achieved an acutely gas leakage source location in an indoor environment. And the reasonable path planning and dynamic topology changing could improve the positioning performance.",
"genre": "research_article",
"id": "sg:pub.10.1007/s12652-017-0624-z",
"inLanguage": [
"en"
],
"isAccessibleForFree": false,
"isFundedItemOf": [
{
"id": "sg:grant.7185738",
"type": "MonetaryGrant"
}
],
"isPartOf": [
{
"id": "sg:journal.1043999",
"issn": [
"1868-5137",
"1868-5145"
],
"name": "Journal of Ambient Intelligence and Humanized Computing",
"type": "Periodical"
},
{
"issueNumber": "5",
"type": "PublicationIssue"
},
{
"type": "PublicationVolume",
"volumeNumber": "10"
}
],
"name": "An indoor gas leakage source localization algorithm using distributed maximum likelihood estimation in sensor networks",
"pagination": "1703-1712",
"productId": [
{
"name": "readcube_id",
"type": "PropertyValue",
"value": [
"960203e86aa237f3c18deb294052787c0a3d5458f866a4b6467f01ff445fea54"
]
},
{
"name": "doi",
"type": "PropertyValue",
"value": [
"10.1007/s12652-017-0624-z"
]
},
{
"name": "dimensions_id",
"type": "PropertyValue",
"value": [
"pub.1092854697"
]
}
],
"sameAs": [
"https://doi.org/10.1007/s12652-017-0624-z",
"https://app.dimensions.ai/details/publication/pub.1092854697"
],
"sdDataset": "articles",
"sdDatePublished": "2019-04-11T13:53",
"sdLicense": "https://scigraph.springernature.com/explorer/license/",
"sdPublisher": {
"name": "Springer Nature - SN SciGraph project",
"type": "Organization"
},
"sdSource": "s3://com-uberresearch-data-dimensions-target-20181106-alternative/cleanup/v134/2549eaecd7973599484d7c17b260dba0a4ecb94b/merge/v9/a6c9fde33151104705d4d7ff012ea9563521a3ce/jats-lookup/v90/0000000371_0000000371/records_130805_00000005.jsonl",
"type": "ScholarlyArticle",
"url": "https://link.springer.com/10.1007%2Fs12652-017-0624-z"
}
]Download the RDF metadata as: json-ld nt turtle xml License info
JSON-LD is a popular format for linked data which is fully compatible with JSON.
curl -H 'Accept: application/ld+json' 'https://scigraph.springernature.com/pub.10.1007/s12652-017-0624-z'
N-Triples is a line-based linked data format ideal for batch operations.
curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1007/s12652-017-0624-z'
Turtle is a human-readable linked data format.
curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1007/s12652-017-0624-z'
RDF/XML is a standard XML format for linked data.
curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1007/s12652-017-0624-z'
This table displays all metadata directly associated to this object as RDF triples.
160 TRIPLES
21 PREDICATES
50 URIs
19 LITERALS
7 BLANK NODES