Please use this identifier to cite or link to this item:
https://ruomoplus.lib.uom.gr/handle/8000/1913
DC Field | Value | Language |
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dc.contributor.author | Griva, Aikaterini | el |
dc.contributor.author | Boursianis, Achilles D. | el |
dc.contributor.author | Wan, Shaohua | el |
dc.contributor.author | Sarigiannidis, Panagiotis | el |
dc.contributor.author | Psannis, Konstantinos | el |
dc.contributor.author | Karagiannidis, George K. | el |
dc.contributor.author | Goudos, Sotirios K. | el |
dc.date.accessioned | 2024-12-04T17:34:21Z | - |
dc.date.available | 2024-12-04T17:34:21Z | - |
dc.date.issued | 2023-02-03 | - |
dc.identifier.uri | https://ruomoplus.lib.uom.gr/handle/8000/1913 | - |
dc.description.abstract | The implementation of smart networks has made great progress due to the development of the Internet of Things (IoT). LoRa is one of the most prominent technologies in the Internet of Things industry, primarily due to its ability to achieve long-distance transmission while consuming less power. In this work, we modeled different environments and assessed the performances of networks by observing the effects of various factors and network parameters. The path loss model, the deployment area size, the transmission power, the spreading factor, the number of nodes and gateways, and the antenna gain have a significant effect on the main performance metrics such as the energy consumption and the data extraction rate of a LoRa network. In order to examine these parameters, we performed simulations in OMNeT++ using the open source framework FLoRa. The scenarios which were investigated in this work include the simulation of rural and urban environments and a parking area model. The results indicate that the optimization of the key parameters could have a huge impact on the deployment of smart networks. | el |
dc.language.iso | en | el |
dc.relation.ispartof | Sensors (Basel, Switzerland) | el |
dc.rights | Attribution-NonCommercial-NoDerivatives 4.0 Διεθνές | * |
dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/4.0/ | * |
dc.subject | FRASCATI__Natural sciences__Computer and information sciences | el |
dc.subject.other | data extraction rate (DER) | el |
dc.subject.other | Internet of Things (IoT) | el |
dc.subject.other | long-range network | el |
dc.subject.other | low-power wide-area network (LPWAN) | el |
dc.subject.other | network energy consumption (NEC) | el |
dc.subject.other | smart agriculture | el |
dc.subject.other | smart city | el |
dc.title | LoRa-Based IoT Network Assessment in Rural and Urban Scenarios | el |
dc.type | journal article | el |
dc.identifier.doi | 10.3390/s23031695 | - |
dc.identifier.pmid | 36772734 | - |
dc.identifier.scopus | 2-s2.0-85147894785 | - |
dc.identifier.url | https://api.elsevier.com/content/abstract/scopus_id/85147894785 | - |
dc.relation.issn | 1424-8220 | el |
dc.relation.issn | 1424-8220 | el |
dc.description.volume | 23 | el |
dc.description.issue | 3 | el |
dc.description.startpage | 1695 | el |
dc.contributor.department | Department of Applied Informatics | el |
dc.relation.eissn | 1424-8220 | el |
item.grantfulltext | open | - |
item.openairecristype | http://purl.org/coar/resource_type/c_6501 | - |
item.openairetype | journal article | - |
item.fulltext | With Fulltext | - |
item.languageiso639-1 | en | - |
item.cerifentitytype | Publications | - |
crisitem.journal.journalissn | 1424-8220 | - |
crisitem.journal.journaleissn | 1424-8220 | - |
crisitem.author.dept | University of Macedonia | - |
crisitem.author.dept | University of Macedonia | - |
crisitem.author.dept | University of Macedonia | - |
crisitem.author.dept | University of Macedonia | - |
crisitem.author.dept | University of Macedonia | - |
crisitem.author.dept | University of Macedonia | - |
crisitem.author.department | Department of Applied Informatics | - |
crisitem.author.orcid | 0000-0002-8301-0970 | - |
crisitem.author.orcid | 0000-0003-0020-6394 | - |
crisitem.author.faculty | School of Information Sciences | - |
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sensors-23-01695.pdf | 1,4 MB | Adobe PDF | View/Open |
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