RT info:eu-repo/semantics/article
T1 Smart Buildings IoT Networks Accuracy Evolution Prediction to Improve Their Reliability Using a Lotka–Volterra Ecosystem Model
A1 Casado Vara, Roberto Carlos
A1 Canal-Alonso, Ángel
A1 Martín del Rey, Ángel
A1 Prieta, Fernando de la
A1 Prieto, Javier
K1 Internet of Things
K1 Lotka-Volterra model
K1 Predator-prey system
K1 Bio-inspired system evolution
K1 Algorithm desing
K1 Informática
K1 Computer science
AB Internet of Things (IoT) is the paradigm that has largely contributed to the development ofsmart buildings in our society. This technology makes it possible to monitor all aspects of the smartbuilding and to improve its operation. One of the main challenges encountered by IoT networksis that the the data they collect may be unreliable since IoT devices can lose accuracy for severalreasons (sensor wear, sensor aging, poorly constructed buildings, etc.). The aim of our work is tostudy the evolution of IoT networks over time in smart buildings. The hypothesis we have tested isthat, by amplifying the Lotka–Volterra equations as a community of living organisms (an ecosystemmodel), the reliability of the system and its components can be predicted. This model comprisesa set of differential equations that describe the relationship between an IoT network and multipleIoT devices. Based on the Lotka–Volterra model, in this article, we propose a model in which thepredators 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 bothspecies, helping the prey to survive within the ecosystem. This is the first Lotka–Volterra model thatis applied in the field of IoT. Our work establishes a proof of concept in the field and opens a widespectrum of applications for biology models to be applied in IoT.
PB MDPI
YR 2019
FD 2019-10
LK http://hdl.handle.net/10259/7254
UL http://hdl.handle.net/10259/7254
LA eng
NO This paper has been partially supported by the Salamanca Ciudad de Cultura y Saberes Foundation under the Talent Attraction Program (CHROMOSOME project).
DS Repositorio Institucional de la Universidad de Burgos
RD 23-nov-2024