Temperature and Relative Humidity Prediction in Swine Livestock Buildings

Andres Molano-Jimenez; Alvaro D. Orjuela-Canon; Wilmer Acosta-Burbano

doi:10.1109/LA-CCI.2018.8625245

Temperature and Relative Humidity Prediction in Swine Livestock Buildings

Andres Molano-Jimenez
, Alvaro D. Orjuela-Canon
, Wilmer Acosta-Burbano

Producción científica: Redes de conocimiento › Actas de congreso › revisión exhaustiva

3 Citas (Scopus)

Resumen

Based on available data from a swine livestock warehouse located in Puerto Gaitan - Meta, four models were proposed to predict relative humidity and temperature using artificial neural networks and measurements from temperature, humidity and CO₂ concentration. Results seem to indicate that the model structures used are suitable for predict humidity in barns not equipped with humidity sensors and improve current installed microclimate control systems in Colombia.

Idioma original	Inglés estadounidense
DOI	https://doi.org/10.1109/LA-CCI.2018.8625245
Estado	Publicada - ene. 23 2019
Publicado de forma externa	Sí
Evento	2018 IEEE Latin American Conference on Computational Intelligence, LA-CCI 2018 - Gudalajara, México Duración: nov. 6 2018 → nov. 9 2018

Conferencia

Conferencia	2018 IEEE Latin American Conference on Computational Intelligence, LA-CCI 2018
País/Territorio	México
Ciudad	Gudalajara
Período	11/6/18 → 11/9/18

ODS de las Naciones Unidas

Este resultado contribuye a los siguientes Objetivos de Desarrollo Sostenible

ODS 3: Salud y bienestar

Áreas temáticas de ASJC Scopus

Inteligencia artificial
Redes de ordenadores y comunicaciones
Gestión y sistemas de información

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10.1109/LA-CCI.2018.8625245

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title = "Temperature and Relative Humidity Prediction in Swine Livestock Buildings",

abstract = "Based on available data from a swine livestock warehouse located in Puerto Gaitan - Meta, four models were proposed to predict relative humidity and temperature using artificial neural networks and measurements from temperature, humidity and CO2 concentration. Results seem to indicate that the model structures used are suitable for predict humidity in barns not equipped with humidity sensors and improve current installed microclimate control systems in Colombia.",

author = "Andres Molano-Jimenez and Orjuela-Canon, \{Alvaro D.\} and Wilmer Acosta-Burbano",

note = "Publisher Copyright: {\textcopyright} 2018 IEEE.; 2018 IEEE Latin American Conference on Computational Intelligence, LA-CCI 2018 ; Conference date: 06-11-2018 Through 09-11-2018",

year = "2019",

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Temperature and Relative Humidity Prediction in Swine Livestock Buildings. / Molano-Jimenez, Andres; Orjuela-Canon, Alvaro D.; Acosta-Burbano, Wilmer.
2019. Papel presentado en 2018 IEEE Latin American Conference on Computational Intelligence, LA-CCI 2018, Gudalajara, México.

Producción científica: Redes de conocimiento › Actas de congreso › revisión exhaustiva

TY - CONF

T1 - Temperature and Relative Humidity Prediction in Swine Livestock Buildings

AU - Molano-Jimenez, Andres

AU - Orjuela-Canon, Alvaro D.

AU - Acosta-Burbano, Wilmer

PY - 2019/1/23

Y1 - 2019/1/23

N2 - Based on available data from a swine livestock warehouse located in Puerto Gaitan - Meta, four models were proposed to predict relative humidity and temperature using artificial neural networks and measurements from temperature, humidity and CO2 concentration. Results seem to indicate that the model structures used are suitable for predict humidity in barns not equipped with humidity sensors and improve current installed microclimate control systems in Colombia.

AB - Based on available data from a swine livestock warehouse located in Puerto Gaitan - Meta, four models were proposed to predict relative humidity and temperature using artificial neural networks and measurements from temperature, humidity and CO2 concentration. Results seem to indicate that the model structures used are suitable for predict humidity in barns not equipped with humidity sensors and improve current installed microclimate control systems in Colombia.

UR - https://www.scopus.com/pages/publications/85062550286

UR - https://www.scopus.com/pages/publications/85062550286#tab=citedBy

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DO - 10.1109/LA-CCI.2018.8625245

M3 - Conference proceedings

AN - SCOPUS:85062550286

T2 - 2018 IEEE Latin American Conference on Computational Intelligence, LA-CCI 2018

Y2 - 6 November 2018 through 9 November 2018

ER -

Temperature and Relative Humidity Prediction in Swine Livestock Buildings

Resumen

Conferencia

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