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

Abstract

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.

Prediction of Total Soluble Solids and pH of Strawberry Fruits Using RGB, HSV and HSL Colour Spaces and Machine Learning Models

“…In the measured data, there were no missing values; therefore, the current research did not consider any method for imputing the missing data. A rank correlation test was widely used to identify the right features from the available datasets [ 49 ]. In this study, rank correlation, i.e., the Pearson correlation technique, was applied, as briefly described in the input datasets for model development section.…”

“…In this study, rank correlation, i.e., the Pearson correlation technique, was applied, as briefly described in the input datasets for model development section. A different range of variables in a same dataset used as an input parameters for developing machine learning (ML) models may reduce the model’s learning performance and prediction efficiency [ 49 ]. For that reason, data normalization, a popular data preprocessing technique, has been commonly used to avoid complications.…”

“…Moreover, the prediction capabilities of ML models are also influenced by the data partition in the training and testing stages. Several studies used 70:30 (training: testing), 80:20 and 90:10 partition to develop and validate model [ 49 , 50 , 51 , 52 ]. After examining the model performance using the three data partitions (70:30, 80:20 and 90:10), the current study utilized 80% data during the training stage and 20% data during the testing stage.…”

“…Foods 2022, 11, x FOR PEER REVIEW 7 of 24 widely used to identify the right features from the available datasets [49]. In this study, rank correlation, i.e., the Pearson correlation technique, was applied, as briefly described in the input datasets for model development section.…”

A Top-Down Survey on Optical Wireless Communications for the Internet of Things

“…They can also be used to monitor the behavior and weight of birds and notify the farmers about potential problems in the poultry house [54], [55]. Furthermore, 2D/3D cameras can be used to supervise pigs' behavior in barns to identify a potential illness at an early stage [56]. As previously mentioned, cameras deployed to surveil/monitor animal farms can be used for OCC systems, where the light emitted by LEDs situated on an animal's body or reflected on it from the ceiling can be detected by the camera to ensure hybrid sensing and communication.…”