Multi-Sensor Platform in Precision Livestock Farming for Air Quality Measurement Based on Open-Source Tools

Monitoring air quality in livestock farming facilities is crucial for ensuring the health and well-being of both animals and workers. As livestock farming can contribute to the emission of various gaseous and particulate pollutants, there is a pressing need for advanced air quality monitoring systems to manage and mitigate these emissions effectively. This study introduces a multi-sensor air quality monitoring system designed specifically for livestock farming environments. Utilizing open-source tools and low-cost sensors, the system can measure multiple air quality parameters simultaneously. The system architecture is based on SOLID principles to ensure robustness, scalability, and ease of maintenance. Understanding a trend of evolution of air quality monitoring from single-parameter measurements to a more holistic approach through the integration of multiple sensors, a multi-sensor platform is proposed in this work. This shift towards multi-sensor systems is driven by the recognition that a comprehensive understanding of air quality requires consideration of diverse pollutants and environmental factors. The aim of this study is to construct a multi-sensor air quality monitoring system with the use of open-source tools and low-cost sensors as a tool for Precision Livestock Farming (PLF). Analysis of the data collected by the multi-sensor device reveals some insights into the environmental conditions in the monitored barn. Time-series and correlation analyses revealed significant interactions between key environmental parameters, such as strong positive correlations between ammonia and hydrogen sulfide, and between total volatile organic compounds and carbon dioxide. These relationships highlight the critical impact of these odorants on air quality, emphasizing the need for effective barn environmental controls to manage these factors.

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Publication Details

Journal
Applied Sciences
Published
2024-09-10
DOI
https://doi.org/10.3390/app14188113
Citations
12
Primary Topic
Air Quality Monitoring and Forecasting
Type
article
Field-Weighted Citation Impact
2.47
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article

Multi-Sensor Platform in Precision Livestock Farming for Air Quality Measurement Based on Open-Source Tools

Victor Danev, Tatiana Atanasova, Kristina Dineva
12 citations
Applied Sciences
Air Quality Monitoring and Forecasting
2.47
article

Multi-Sensor Platform in Precision Livestock Farming for Air Quality Measurement Based on Open-Source Tools

Victor Danev, Tatiana Atanasova, Kristina Dineva
article en
12 citations

Abstract

Monitoring air quality in livestock farming facilities is crucial for ensuring the health and well-being of both animals and workers. As livestock farming can contribute to the emission of various gaseous and particulate pollutants, there is a pressing need for advanced air quality monitoring systems to manage and mitigate these emissions effectively. This study introduces a multi-sensor air quality monitoring system designed specifically for livestock farming environments. Utilizing open-source tools and low-cost sensors, the system can measure multiple air quality parameters simultaneously. The system architecture is based on SOLID principles to ensure robustness, scalability, and ease of maintenance. Understanding a trend of evolution of air quality monitoring from single-parameter measurements to a more holistic approach through the integration of multiple sensors, a multi-sensor platform is proposed in this work. This shift towards multi-sensor systems is driven by the recognition that a comprehensive understanding of air quality requires consideration of diverse pollutants and environmental factors. The aim of this study is to construct a multi-sensor air quality monitoring system with the use of open-source tools and low-cost sensors as a tool for Precision Livestock Farming (PLF). Analysis of the data collected by the multi-sensor device reveals some insights into the environmental conditions in the monitored barn. Time-series and correlation analyses revealed significant interactions between key environmental parameters, such as strong positive correlations between ammonia and hydrogen sulfide, and between total volatile organic compounds and carbon dioxide. These relationships highlight the critical impact of these odorants on air quality, emphasizing the need for effective barn environmental controls to manage these factors.

Applied SciencesVol. 14(18)
Bulgarian Academy of Sciences (BG), Institute of Information and Communication Technologies (BG)
Openalex Percentile: Top 11%
Air Quality Monitoring and Forecasting
2.47
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