<?xml version="1.0" encoding="UTF-8"?><?xml-stylesheet type="text/xsl" href="static/style.xsl"?><OAI-PMH xmlns="http://www.openarchives.org/OAI/2.0/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/ http://www.openarchives.org/OAI/2.0/OAI-PMH.xsd"><responseDate>2026-06-02T04:16:18Z</responseDate><request verb="GetRecord" identifier="oai:riubu.ubu.es:10259/7254" metadataPrefix="marc">https://riubu.ubu.es/oai/request</request><GetRecord><record><header><identifier>oai:riubu.ubu.es:10259/7254</identifier><datestamp>2023-01-18T01:05:25Z</datestamp><setSpec>com_10259_3847</setSpec><setSpec>com_10259_5086</setSpec><setSpec>com_10259_2604</setSpec><setSpec>col_10259_3848</setSpec></header><metadata><record xmlns="http://www.loc.gov/MARC21/slim" xmlns:doc="http://www.lyncode.com/xoai" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns:dcterms="http://purl.org/dc/terms/" xsi:schemaLocation="http://www.loc.gov/MARC21/slim http://www.loc.gov/standards/marcxml/schema/MARC21slim.xsd">
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<subfield code="a">Casado Vara, Roberto</subfield>
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<subfield code="a">Canal-Alonso, Ángel</subfield>
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<subfield code="a">Martín del Rey, Ángel</subfield>
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<subfield code="a">Prieta, Fernando de la</subfield>
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<subfield code="a">Prieto, Javier</subfield>
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<subfield code="c">2019-10</subfield>
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<subfield code="a">Internet of Things (IoT) is the paradigm that has largely contributed to the development of&#xd;
smart buildings in our society. This technology makes it possible to monitor all aspects of the smart&#xd;
building and to improve its operation. One of the main challenges encountered by IoT networks&#xd;
is that the the data they collect may be unreliable since IoT devices can lose accuracy for several&#xd;
reasons (sensor wear, sensor aging, poorly constructed buildings, etc.). The aim of our work is to&#xd;
study the evolution of IoT networks over time in smart buildings. The hypothesis we have tested is&#xd;
that, by amplifying the Lotka–Volterra equations as a community of living organisms (an ecosystem&#xd;
model), the reliability of the system and its components can be predicted. This model comprises&#xd;
a set of differential equations that describe the relationship between an IoT network and multiple&#xd;
IoT devices. Based on the Lotka–Volterra model, in this article, we propose a model in which the&#xd;
predators are the non-precision IoT devices and the prey are the precision IoT devices. Furthermore,&#xd;
a third species is introduced, the maintenance staff, which will impact the interaction between both&#xd;
species, helping the prey to survive within the ecosystem. This is the first Lotka–Volterra model that&#xd;
is applied in the field of IoT. Our work establishes a proof of concept in the field and opens a wide&#xd;
spectrum of applications for biology models to be applied in IoT.</subfield>
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<subfield code="a">http://hdl.handle.net/10259/7254</subfield>
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<subfield code="a">10.3390/s19214642</subfield>
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<subfield code="a">1424-8220</subfield>
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<subfield code="a">Internet of Things</subfield>
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<subfield code="a">Lotka-Volterra model</subfield>
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<subfield code="a">Predator-prey system</subfield>
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<datafield ind1=" " ind2=" " tag="653">
<subfield code="a">Bio-inspired system evolution</subfield>
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<subfield code="a">Algorithm desing</subfield>
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<datafield tag="245" ind1="0" ind2="0">
<subfield code="a">Smart Buildings IoT Networks Accuracy Evolution Prediction to Improve Their Reliability Using a Lotka–Volterra Ecosystem Model</subfield>
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