Abstract
Building fences to manage the cattle grazing can be very expensive; cost inefficient. These do not provide dynamic control over the area in which the cattle are grazing. Existing virtual fencing techniques for the control of herds of cattle, based on polygon coordinate definition of boundaries is limited in the area of land mass coverage and dynamism. This work seeks to develop a more robust and an improved monocular vision based boundary avoidance for non-invasive stray control system for cattle, with a view to increase land mass coverage in virtual fencing techniques and dynamism. The monocular vision based depth estimation will be modeled using concept of global Fourier Transform (FT) and local Wavelet Transform (WT) of image structure of scenes (boundaries). The magnitude of the global Fourier Transform gives the dominant orientations and textual patterns of the image; while the local Wavelet Transform gives the dominant spectral features of the image and their spatial distribution. Each scene picture or image is defined by features v, which contain the set of global (FT) and local (WT) statistics of the image. Scenes or boundaries distances are given by estimating the depth D by means of the image features v. Sound cues of intensity equivalent to the magnitude of the depth D are applied to the animal ears as stimuli. This brings about the desired control as animals tend to move away from uncomfortable sounds.
Highlights
Intensive monitoring of domestic cattle has many economic and welfare benefits, but to realize these, timely notifications of changes in animal conditions, environmental and physiological events can advance at a rate for which constant monitoring of cattle would be necessary
Based on the existing work, cattle movement control is achievable with the adaptation of wireless sensor network (WSNs) technological innovations, Global Positioning System (GPS) for animal tracking schemes
This paper proposes a model to enhance the existing work on cattle movement control with the application of wireless sensor network (WSNs); Global Positioning System (GPS); Artificial Intelligence (Image Processing); Monocular Vision System and Target recognition sub-systems
Summary
Intensive monitoring of domestic cattle has many economic and welfare benefits, but to realize these, timely notifications of changes in animal conditions, environmental and physiological events can advance at a rate for which constant monitoring of cattle would be necessary. Virtual fences techniques for cattle control are achieved by applying aversive stimuli (sound or vibration) to an animal when it approaches a predefined boundary. It is implemented by a small smart collar integrated with a Global Positioning System (GPS) sensor, flash memory, wireless transceivers, and a small CPU; essentially, each node is a small wireless computing device. The monocular vision boundary avoidance for non-invasive stray control system for cattle will require no motion planning algorithm to shift boundaries of virtual fences. It will require no path planning protocol.
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