Smart Buildings IoT Networks Accuracy Evolution Prediction to Improve Their Reliability Using a Lotka–Volterra Ecosystem Model
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...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2019-10-01
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| Series: | Sensors |
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| Online Access: | https://www.mdpi.com/1424-8220/19/21/4642 |
| _version_ | 1811304380935176192 |
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| author | Roberto Casado-Vara Angel Canal-Alonso Angel Martin-del Rey Fernando De la Prieta Javier Prieto |
| author_facet | Roberto Casado-Vara Angel Canal-Alonso Angel Martin-del Rey Fernando De la Prieta Javier Prieto |
| author_sort | Roberto Casado-Vara |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-04-13T08:06:03Z |
| format | Article |
| id | doaj.art-a4d65afb27474838a47e4535965f7155 |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-04-13T08:06:03Z |
| publishDate | 2019-10-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-a4d65afb27474838a47e4535965f71552022-12-22T02:55:09ZengMDPI AGSensors1424-82202019-10-011921464210.3390/s19214642s19214642Smart Buildings IoT Networks Accuracy Evolution Prediction to Improve Their Reliability Using a Lotka–Volterra Ecosystem ModelRoberto Casado-Vara0Angel Canal-Alonso1Angel Martin-del Rey2Fernando De la Prieta3Javier Prieto4BISITE Research Group, University of Salamanca, Edificio Multiusos I+D+i, 37007 Salamanca, SpainBISITE Research Group, University of Salamanca, Edificio Multiusos I+D+i, 37007 Salamanca, SpainDepartment of Applied Mathematics, Institute of Fundamental Physics and Mathematics, University of Salamanca, Calle del Parque 2, 37008 Salamanca, SpainBISITE Research Group, University of Salamanca, Edificio Multiusos I+D+i, 37007 Salamanca, SpainBISITE Research Group, University of Salamanca, Edificio Multiusos I+D+i, 37007 Salamanca, SpainInternet 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.https://www.mdpi.com/1424-8220/19/21/4642internet of thingslotka–volterra modelpredator–prey systembio-inspired system evolutionalgorithm design |
| spellingShingle | Roberto Casado-Vara Angel Canal-Alonso Angel Martin-del Rey Fernando De la Prieta Javier Prieto Smart Buildings IoT Networks Accuracy Evolution Prediction to Improve Their Reliability Using a Lotka–Volterra Ecosystem Model Sensors internet of things lotka–volterra model predator–prey system bio-inspired system evolution algorithm design |
| title | Smart Buildings IoT Networks Accuracy Evolution Prediction to Improve Their Reliability Using a Lotka–Volterra Ecosystem Model |
| title_full | Smart Buildings IoT Networks Accuracy Evolution Prediction to Improve Their Reliability Using a Lotka–Volterra Ecosystem Model |
| title_fullStr | Smart Buildings IoT Networks Accuracy Evolution Prediction to Improve Their Reliability Using a Lotka–Volterra Ecosystem Model |
| title_full_unstemmed | Smart Buildings IoT Networks Accuracy Evolution Prediction to Improve Their Reliability Using a Lotka–Volterra Ecosystem Model |
| title_short | Smart Buildings IoT Networks Accuracy Evolution Prediction to Improve Their Reliability Using a Lotka–Volterra Ecosystem Model |
| title_sort | smart buildings iot networks accuracy evolution prediction to improve their reliability using a lotka volterra ecosystem model |
| topic | internet of things lotka–volterra model predator–prey system bio-inspired system evolution algorithm design |
| url | https://www.mdpi.com/1424-8220/19/21/4642 |
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