The study highlights the importance of monitoring and visualizing the Temperature-Humidity Index (THI) in farm buildings due to its direct impact on livestock health, productivity, and welfare. To address the limitations of traditional monitoring techniques, a Smart Monitoring System (SMS) was employed in a study case to gather real-time THI measurements from various indoor sampling points within an experimental livestock barn. This system integrates temperature and humidity sensors, enabling automatic, remote and continuous data collection. To visualize the THI distribution throughout the farm and overcome data sparsity, the Discrete Sibson Interpolation method was employed. This method effectively interpolates the collected THI data onto a three-dimensional grid, providing a comprehensive representation of the THI distribution. The study involved the definition of spatially continuous distributions that can be visualized through various types of graphs, supporting the identification of meaningful insights about the spatial and temporal trends of indoor THI in livestock buildings. The results obtained from the pilot farm investigation revealed the presence of critical zones with high THI values, which can affect limited areas of the barn volume, even in periods when the average THI of the barn is below the alert threshold. It is important to identify such localized anomalies of THI, because they negatively impact livestock welfare and subsequently reduce the productive levels of the herd. The research addresses the limitations of the analysis of discrete data and average spatial values by employing data processing for interpolation and visualization and the results demonstrates the significance of monitoring THI in livestock barns through SMSs. The findings of this investigation offer valuable insights and practical advice for farmers and stakeholders in developing PLF tools for the analysis and control of the indoor environment of barns, to optimize livestock conditions and mitigate the negative effects of discomfort caused by hot weather conditions.

PEREZ GARCIA, C.A., Tassinari, P., Bovo, M., Torreggiani, D., Barbaresi, A., Benni, S. (2023). Modelling the Spatial Distribution of THI in a Cattle Barn From Data of a Smart Monitoring System. IEEE.

Modelling the Spatial Distribution of THI in a Cattle Barn From Data of a Smart Monitoring System

Carlos Alejandro Perez Garcia
;
Patrizia Tassinari;Marco Bovo;Daniele Torreggiani;Alberto Barbaresi;Stefano Benni
2023

Abstract

The study highlights the importance of monitoring and visualizing the Temperature-Humidity Index (THI) in farm buildings due to its direct impact on livestock health, productivity, and welfare. To address the limitations of traditional monitoring techniques, a Smart Monitoring System (SMS) was employed in a study case to gather real-time THI measurements from various indoor sampling points within an experimental livestock barn. This system integrates temperature and humidity sensors, enabling automatic, remote and continuous data collection. To visualize the THI distribution throughout the farm and overcome data sparsity, the Discrete Sibson Interpolation method was employed. This method effectively interpolates the collected THI data onto a three-dimensional grid, providing a comprehensive representation of the THI distribution. The study involved the definition of spatially continuous distributions that can be visualized through various types of graphs, supporting the identification of meaningful insights about the spatial and temporal trends of indoor THI in livestock buildings. The results obtained from the pilot farm investigation revealed the presence of critical zones with high THI values, which can affect limited areas of the barn volume, even in periods when the average THI of the barn is below the alert threshold. It is important to identify such localized anomalies of THI, because they negatively impact livestock welfare and subsequently reduce the productive levels of the herd. The research addresses the limitations of the analysis of discrete data and average spatial values by employing data processing for interpolation and visualization and the results demonstrates the significance of monitoring THI in livestock barns through SMSs. The findings of this investigation offer valuable insights and practical advice for farmers and stakeholders in developing PLF tools for the analysis and control of the indoor environment of barns, to optimize livestock conditions and mitigate the negative effects of discomfort caused by hot weather conditions.
2023
IEEE International Workshop on Metrology for Agriculture and Forestry Proceedings
484
489
PEREZ GARCIA, C.A., Tassinari, P., Bovo, M., Torreggiani, D., Barbaresi, A., Benni, S. (2023). Modelling the Spatial Distribution of THI in a Cattle Barn From Data of a Smart Monitoring System. IEEE.
PEREZ GARCIA, CARLOS ALEJANDRO; Tassinari, Patrizia; Bovo, Marco; Torreggiani, Daniele; Barbaresi, Alberto; Benni, Stefano
File in questo prodotto:
File Dimensione Formato  
2023226820.pdf

accesso aperto

Tipo: Postprint / Author's Accepted Manuscript (AAM) - versione accettata per la pubblicazione dopo la peer-review
Licenza: Licenza per accesso libero gratuito
Dimensione 613.49 kB
Formato Adobe PDF
613.49 kB Adobe PDF Visualizza/Apri

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11585/955183
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 0
  • ???jsp.display-item.citation.isi??? 0
social impact