Machine Learning-Based Microclimate Model for Indoor Air Temperature and Relative Humidity Prediction in a Swine Building

Arulmozhi, Elanchezhıan; Basak, Jayanta Kumar; Sihalath, Thavisack; Park, Jaesung; Kim, Hyeon Tae; Moon, Byeong Eun

doi:10.3390/ani11010222

Cited by 46 publications

(35 citation statements)

References 43 publications

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“…Arulmozhi et al evaluated performance of multiple linear regression (MLR), multilayered perceptron (MLP), decision tree regression (DTR), and support vector regression (SVR) to predict indoor air temperature (IAT) and indoor relative humidity (IRH). RFR performs well with IAT and IRH prediction with R² > 0.98 for IAT and R² > 0.93 for IRH [60].…”

Section: Pigsmentioning

confidence: 88%

Farm Animals’ Behaviors and Welfare Analysis with IA Algorithms: A Review

Debauche¹,

Elmoulat²,

Mahmoudi³

et al. 2021

RIA

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Numerous bibliographic reviews related to the use of AI for the behavioral detection of farm animals exist, but they only focus on a particular type of animal. We believe that some techniques were used for some animals that could also be used for other types of animals. The application and comparison of these techniques between animal species are rarely done. In this paper, we propose a review of machine learning approaches used for the detection of farm animals’ behaviors such as lameness, grazing, rumination, and so on. The originality of this paper is matched classification in the midst of sensors and algorithms used for each animal category. First, we highlight the most implemented approaches for different categories of animals (cows, sheep, goats, pigs, horses, and chickens) to inspire researchers interested to conduct investigation and employ the methods we have evaluated and the results we have obtained in this study. Second, we describe the current trends in terms of technological development and new paradigms that will impact the AI research. Finally, we critically analyze what is done and we draw new pathways of research to advance our understanding of animal’s behaviors.

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Section: Pigsmentioning

confidence: 88%

Farm Animals’ Behaviors and Welfare Analysis with IA Algorithms: A Review

Debauche¹,

Elmoulat²,

Mahmoudi³

et al. 2021

RIA

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“…As projected by economic experts, the world population in 2050 will be almost 10 billion, 23% more than the current population. Moreover, there will be a considerable shortfall in feeding the additional 3 billion people due to the lower food production achieved by conventional farming, as per statistical reports [ 1 , 2 , 3 ]. With 350 million tons of meat consumed per year worldwide, meat production needs to be boosted significantly, with less land use, to avoid hunger in the coming decades.…”

Section: Introductionmentioning

confidence: 99%

“… Environmental management—protect the animals from environmental stressors (PLF could regulate environmental stressors such as temperature, humidity, airflow, ventilation, etc.) [ 3 , 14 ]. Performance—the workload of the animals can be reduced, or they can be subjected to external stress due to human activity inside the pen [ 8 , 16 ].…”

Section: Introductionmentioning

confidence: 99%

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The Application of Cameras in Precision Pig Farming: An Overview for Swine-Keeping Professionals

Arulmozhi

Bhujel

Moon

et al. 2021

Animals

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Pork is the meat with the second-largest overall consumption, and chicken, pork, and beef together account for 92% of global meat production. Therefore, it is necessary to adopt more progressive methodologies such as precision livestock farming (PLF) rather than conventional methods to improve production. In recent years, image-based studies have become an efficient solution in various fields such as navigation for unmanned vehicles, human–machine-based systems, agricultural surveying, livestock, etc. So far, several studies have been conducted to identify, track, and classify the behaviors of pigs and achieve early detection of disease, using 2D/3D cameras. This review describes the state of the art in 3D imaging systems (i.e., depth sensors and time-of-flight cameras), along with 2D cameras, for effectively identifying pig behaviors and presents automated approaches for the monitoring and investigation of pigs’ feeding, drinking, lying, locomotion, aggressive, and reproductive behaviors.

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“…Breeding pigs with a high growth rate requires maintaining comfortable microclimate parameters in pigsties [1,2]. Even though a regulated microclimate is created in the premises of pig complexes, it still does not always correspond to the optimal values.…”

Section: Introductionmentioning

confidence: 99%

Project development of a “smart” premise system for pig keeping

et al. 2021

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The economic efficiency of intensive animal husbandry on an industrial basis depends on the rational animal keeping, which is largely determined by the availability of optimal microclimate in the premises. Whatever breed and pedigree qualities animals possess, they are unable to maintain health and display their potential hereditary productive abilities without creating the necessary microclimate conditions. In the period of 2018-2020, a survey of 11 farms in Perm Krai was carried out, where respiratory, digestive, skin diseases were found, in some cases stress was observed in animals. The cost of heating livestock premises is generally much lower than losses from murrain, reduced productivity, and feed overruns. Physical properties of the air environment are unstable factors and are subject to large fluctuations. To optimize the microclimate in livestock premises, an algorithm program for computers was developed, which will allow to create a system that provides optimal conditions for keeping and maintenance of animals and improve life safety on livestock farms. In this regard, to improve the conditions of calves and cows’ keeping, a project for managing microclimate parameters on farms in the conditions of Perm Krai has been developed. Microclimate management system was developed on the basis of: the Order of the Ministry of Agriculture of the Russian Federation dated October 21, 2000 No. 621 “On approval of Veterinary rules for the maintenance of pigs for the purpose of their reproduction, cultivation and sales.” Monitoring is based on automated analysis and regulation of microclimate parameters' indicators. The software and hardware implementation were done on Omron PLC.

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Machine Learning-Based Microclimate Model for Indoor Air Temperature and Relative Humidity Prediction in a Swine Building

Cited by 46 publications

References 43 publications

Farm Animals’ Behaviors and Welfare Analysis with IA Algorithms: A Review

Farm Animals’ Behaviors and Welfare Analysis with IA Algorithms: A Review

The Application of Cameras in Precision Pig Farming: An Overview for Swine-Keeping Professionals

Project development of a “smart” premise system for pig keeping

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