Table 10.

Livestock: animal welfare.

Author	Animal Species	Observed Features	Functionality	Models/Algorithms	Results
[98]	Cattle	Features like grazing, ruminating, resting, and walking, which were recorded using collar systems with three-axis accelerometer and magnetometer	Classification of cattle behaviour	EL/Bagging with tree learner	96% accuracy
[99]	Calf	Data: chewing signals from dietary supplement, Tifton hay, ryegrass, rumination, and idleness. Signals were collected from optical FBG sensors	Identification and classification of chewing patterns in calves	DT/C4.5	94% accuracy
[100]	Pigs	3D motion data by using two depth cameras	Animal tracking and behavior annotation of the pigs to measure behavioral changes in pigs for welfare and health monitoring	BM: Gaussian Mixture Models (GMMs)	Animal tracking: mean multi-object tracking precision (MOTP) = 0.89 accuracy behavior annotation: standing: control R2 = 0.94, treatment R2 = 0.97 feeding: control R2 = 0.86, treatment R2 = 0.49