Evidence map›Paper›PMID 31357407›Full record

ArticleSensors (Basel, Switzerland)2019

Design and Experimental Validation of a LoRaWAN Fog Computing Based Architecture for IoT Enabled Smart Campus Applications.

Paula Fraga-Lamas, Mikel Celaya-Echarri, Peio Lopez-Iturri, Luis Castedo, Leyre Azpilicueta, Erik Aguirre, Manuel Suárez-Albela, Francisco Falcone, Tiago M Fernández-Caramés

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

14 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors.

Paula Fraga-LamasDepartment of Computer Engineering, Faculty of Computer Science, Centro de investigación CITIC, Universidade da Coruña, 15071 A Coruña, Spain. paula.fraga@udc.es.ORCID 0000-0002-4991-6808
Mikel Celaya-EcharriSchool of Engineering and Sciences, Tecnologico de Monterrey, 64849 Monterrey, NL, Mexico.ORCID 0000-0002-7880-8224
Peio Lopez-IturriDepartment of Electric, Electronic and Communication Engineering, Public University of Navarre, 31006 Pamplona, Spain.ORCID 0000-0001-8411-1928
Luis CastedoDepartment of Computer Engineering, Faculty of Computer Science, Centro de investigación CITIC, Universidade da Coruña, 15071 A Coruña, Spain.ORCID 0000-0002-3801-012X
Leyre AzpilicuetaSchool of Engineering and Sciences, Tecnologico de Monterrey, 64849 Monterrey, NL, Mexico.ORCID 0000-0002-3821-0105
Erik AguirreDepartment of Electric, Electronic and Communication Engineering, Public University of Navarre, 31006 Pamplona, Spain.ORCID 0000-0002-7882-1453
Manuel Suárez-AlbelaDepartment of Computer Engineering, Faculty of Computer Science, Centro de investigación CITIC, Universidade da Coruña, 15071 A Coruña, Spain.ORCID 0000-0001-9891-4553
Francisco FalconeDepartment of Electric, Electronic and Communication Engineering, Public University of Navarre, 31006 Pamplona, Spain.ORCID 0000-0002-4911-9753
Tiago M Fernández-CaramésDepartment of Computer Engineering, Faculty of Computer Science, Centro de investigación CITIC, Universidade da Coruña, 15071 A Coruña, Spain. tiago.fernandez@udc.es.ORCID 0000-0003-2179-5917

Funding

Agencia Estatal de Investigación of Spain TEC2016-75067-C4-1-RXunta de Galicia ED431C 2016-045, ED431G/01
6 · The paper itself

Abstract

A smart campus is an intelligent infrastructure where smart sensors and actuators collaborate to collect information and interact with the machines, tools, and users of a university campus. As in a smart city, a smart campus represents a challenging scenario for Internet of Things (IoT) networks, especially in terms of cost, coverage, availability, latency, power consumption, and scalability. The technologies employed so far to cope with such a scenario are not yet able to manage simultaneously all the previously mentioned demanding requirements. Nevertheless, recent paradigms such as fog computing, which extends cloud computing to the edge of a network, make possible low-latency and location-aware IoT applications. Moreover, technologies such as Low-Power Wide-Area Networks (LPWANs) have emerged as a promising solution to provide low-cost and low-power consumption connectivity to nodes spread throughout a wide area. Specifically, the Long-Range Wide-Area Network (LoRaWAN) standard is one of the most recent developments, receiving attention both from industry and academia. In this article, the use of a LoRaWAN fog computing-based architecture is proposed for providing connectivity to IoT nodes deployed in a campus of the University of A Coruña (UDC), Spain. To validate the proposed system, the smart campus has been recreated realistically through an in-house developed 3D Ray-Launching radio-planning simulator that is able to take into consideration even small details, such as traffic lights, vehicles, people, buildings, urban furniture, or vegetation. The developed tool can provide accurate radio propagation estimations within the smart campus scenario in terms of coverage, capacity, and energy efficiency of the network. The results obtained with the planning simulator can then be compared with empirical measurements to assess the operating conditions and the system accuracy. Specifically, this article presents experiments that show the accurate results obtained by the planning simulator in the largest scenario ever built for it (a campus that covers an area of 26,000 m 2 ), which are corroborated with empirical measurements. Then, how the tool can be used to design the deployment of LoRaWAN infrastructure for three smart campus outdoor applications is explained: a mobility pattern detection system, a smart irrigation solution, and a smart traffic-monitoring deployment. Consequently, the presented results provide guidelines to smart campus designers and developers, and for easing LoRaWAN network deployment and research in other smart campuses and large environments such as smart cities.

Indexed as

3D Ray-Launchingfog computingIoTLoRaWANLPWANoutdoor applicationssmart campussmart citiessustainabilityWireless Sensor Networks (WSN)

Identifiers

PMID31357407
PMCPMC6696130

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.