2024-03-29T12:32:41Zhttps://riubu.ubu.es/oai/requestoai:riubu.ubu.es:10259/72542023-01-18T01:05:25Zcom_10259_3847com_10259_5086com_10259_2604col_10259_3848
Smart Buildings IoT Networks Accuracy Evolution Prediction to Improve Their Reliability Using a Lotka–Volterra Ecosystem Model
Casado Vara, Roberto
Canal-Alonso, Ángel
Martín del Rey, Ángel
Prieta, Fernando de la
Prieto, Javier
Internet of Things
Lotka-Volterra model
Predator-prey system
Bio-inspired system evolution
Algorithm desing
Informática
Computer science
Internet of Things (IoT) is the paradigm that has largely contributed to the development of
smart buildings in our society. This technology makes it possible to monitor all aspects of the smart
building and to improve its operation. One of the main challenges encountered by IoT networks
is that the the data they collect may be unreliable since IoT devices can lose accuracy for several
reasons (sensor wear, sensor aging, poorly constructed buildings, etc.). The aim of our work is to
study the evolution of IoT networks over time in smart buildings. The hypothesis we have tested is
that, by amplifying the Lotka–Volterra equations as a community of living organisms (an ecosystem
model), the reliability of the system and its components can be predicted. This model comprises
a set of differential equations that describe the relationship between an IoT network and multiple
IoT devices. Based on the Lotka–Volterra model, in this article, we propose a model in which the
predators are the non-precision IoT devices and the prey are the precision IoT devices. Furthermore,
a third species is introduced, the maintenance staff, which will impact the interaction between both
species, helping the prey to survive within the ecosystem. This is the first Lotka–Volterra model that
is applied in the field of IoT. Our work establishes a proof of concept in the field and opens a wide
spectrum of applications for biology models to be applied in IoT.
This paper has been partially supported by the Salamanca Ciudad de Cultura y Saberes Foundation under the Talent Attraction Program (CHROMOSOME project).
2023-01-17T11:48:20Z
2023-01-17T11:48:20Z
2019-10
info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
http://hdl.handle.net/10259/7254
10.3390/s19214642
1424-8220
eng
Sensors. 2019, V. 19, n. 21, e4642
https://doi.org/10.3390/s19214642
Atribución 4.0 Internacional
http://creativecommons.org/licenses/by/4.0/
info:eu-repo/semantics/openAccess
application/pdf
MDPI
https://riubu.ubu.es/bitstream/10259/7254/4/Casado-sensors_2019.pdf.jpg
Hispana
TEXT
http://creativecommons.org/licenses/by/4.0/
RIUBU. Repositorio Institucional de la Universidad de Burgos
http://hdl.handle.net/10259/7254