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A Standard-Based Internet of Things Platform and Data Flow Modeling for Smart Environmental Monitoring

The environment consists of the interaction between the physical, biotic, and anthropic means. As this interaction is dynamic, environmental characteristics tend to change naturally over time, requiring continuous monitoring. In this scenario, the internet of things (IoT), together with traditional...

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Autores principales: Filho, Tércio, Fernando, Luiz, Rabelo, Marcos, Silva, Sérgio, Santos, Carlos, Ribeiro, Maria, Grout, Ian A., Moreira, Waldir, Oliveira-Jr, Antonio
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8234585/
https://www.ncbi.nlm.nih.gov/pubmed/34203055
http://dx.doi.org/10.3390/s21124228
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author Filho, Tércio
Fernando, Luiz
Rabelo, Marcos
Silva, Sérgio
Santos, Carlos
Ribeiro, Maria
Grout, Ian A.
Moreira, Waldir
Oliveira-Jr, Antonio
author_facet Filho, Tércio
Fernando, Luiz
Rabelo, Marcos
Silva, Sérgio
Santos, Carlos
Ribeiro, Maria
Grout, Ian A.
Moreira, Waldir
Oliveira-Jr, Antonio
author_sort Filho, Tércio
collection PubMed
description The environment consists of the interaction between the physical, biotic, and anthropic means. As this interaction is dynamic, environmental characteristics tend to change naturally over time, requiring continuous monitoring. In this scenario, the internet of things (IoT), together with traditional sensor networks, allows for the monitoring of various environmental aspects such as air, water, atmospheric, and soil conditions, and sending data to different users and remote applications. This paper proposes a Standard-based Internet of Things Platform and Data Flow Modeling for Smart Environmental Monitoring. The platform consists of an IoT network based on the IEEE 1451 standard which has the network capable application processor (NCAP) node (coordinator) and multiple wireless transducers interface module (WTIM) nodes. A WTIM node consists of one or more transducers, a data transfer interface and a processing unit. Thus, with the developed network, it is possible to collect environmental data at different points within a city landscape, to perform analysis of the communication distance between the WTIM nodes, and monitor the number of bytes transferred according to each network node. In addition, a dynamic model of data flow is proposed where the performance of the NCAP and WTIM nodes are described through state variables, relating directly to the information exchange dynamics between the communicating nodes in the mesh network. The modeling results showed stability in the network. Such stability means that the network has capacity of preserve its flow of information, for a long period of time, without loss frames or packets due to congestion.
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spelling pubmed-82345852021-06-27 A Standard-Based Internet of Things Platform and Data Flow Modeling for Smart Environmental Monitoring Filho, Tércio Fernando, Luiz Rabelo, Marcos Silva, Sérgio Santos, Carlos Ribeiro, Maria Grout, Ian A. Moreira, Waldir Oliveira-Jr, Antonio Sensors (Basel) Article The environment consists of the interaction between the physical, biotic, and anthropic means. As this interaction is dynamic, environmental characteristics tend to change naturally over time, requiring continuous monitoring. In this scenario, the internet of things (IoT), together with traditional sensor networks, allows for the monitoring of various environmental aspects such as air, water, atmospheric, and soil conditions, and sending data to different users and remote applications. This paper proposes a Standard-based Internet of Things Platform and Data Flow Modeling for Smart Environmental Monitoring. The platform consists of an IoT network based on the IEEE 1451 standard which has the network capable application processor (NCAP) node (coordinator) and multiple wireless transducers interface module (WTIM) nodes. A WTIM node consists of one or more transducers, a data transfer interface and a processing unit. Thus, with the developed network, it is possible to collect environmental data at different points within a city landscape, to perform analysis of the communication distance between the WTIM nodes, and monitor the number of bytes transferred according to each network node. In addition, a dynamic model of data flow is proposed where the performance of the NCAP and WTIM nodes are described through state variables, relating directly to the information exchange dynamics between the communicating nodes in the mesh network. The modeling results showed stability in the network. Such stability means that the network has capacity of preserve its flow of information, for a long period of time, without loss frames or packets due to congestion. MDPI 2021-06-20 /pmc/articles/PMC8234585/ /pubmed/34203055 http://dx.doi.org/10.3390/s21124228 Text en © 2021 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Filho, Tércio
Fernando, Luiz
Rabelo, Marcos
Silva, Sérgio
Santos, Carlos
Ribeiro, Maria
Grout, Ian A.
Moreira, Waldir
Oliveira-Jr, Antonio
A Standard-Based Internet of Things Platform and Data Flow Modeling for Smart Environmental Monitoring
title A Standard-Based Internet of Things Platform and Data Flow Modeling for Smart Environmental Monitoring
title_full A Standard-Based Internet of Things Platform and Data Flow Modeling for Smart Environmental Monitoring
title_fullStr A Standard-Based Internet of Things Platform and Data Flow Modeling for Smart Environmental Monitoring
title_full_unstemmed A Standard-Based Internet of Things Platform and Data Flow Modeling for Smart Environmental Monitoring
title_short A Standard-Based Internet of Things Platform and Data Flow Modeling for Smart Environmental Monitoring
title_sort standard-based internet of things platform and data flow modeling for smart environmental monitoring
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8234585/
https://www.ncbi.nlm.nih.gov/pubmed/34203055
http://dx.doi.org/10.3390/s21124228
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