Authors :
Abuka Emmanuel Ifuchenwuwa; E.O. Osaghae; Frederick Duniya Basaky(PhD)
Volume/Issue :
Volume 8 - 2023, Issue 6 - June
Google Scholar :
https://bit.ly/3TmGbDi
Scribd :
https://tinyurl.com/srfs7j6m
DOI :
https://doi.org/10.5281/zenodo.8150171
Abstract :
Abstract:-In the subject of Artificial Intelligence (AI)
known as computer vision, it is possible to teach
computers to comprehend and analyze visual input from
the outside world, including pictures and videos.
It entails the creation of algorithms and systems
that can decipher, interpret, and comprehend visual
input in order to carry out operations like image and
facial identification, object detection and tracking, and
scene comprehension. Despite the contributions made by
other academics' work on this subject, there are still
certain difficulties to be resolved. The bottleneck in the
image/video processing aspect, among many others, is
the identification, selection, and tracking of bird activity
within the poultry farm. This study focuses on the use of
cameras in conjunction with specialized AI systems to
appropriately analyze flocks for health issues. It also
discusses the integration of AI-assisted technology.
Computer vision model was designed using deep
learning algorithm for monitoring and controlling
diseases in birds for the purpose of improving the safety
and productivity of the poultry system. This was
achieved through their captured images from their
droppings (feces) to determine their health state.Data
was collected from two groups of birds; the healthy and
the unhealthy infected with coccidiosis.By providing an early warning and
disease incidence prediction, the designed model, when
put into use, can function as an automatic monitoring
system. This model is to contribute to the advanced
development of computer vision in recent times and to
inform poultry farmers the new trend in the poultry
system to maximize profit.The quality of poultry
products will increase as a result of the correct analysis
of flocks for health issues using cameras integrated to
specialized systems and Artificial Intelligence (AI)
technology, which will increase bird survival rates.
Keywords :
Birds, Computer Vision (CV),Convolutional Neural Network (CNN), Deep Learning (DL), Poultry, Droppings, Coccidiosis.
Abstract:-In the subject of Artificial Intelligence (AI)
known as computer vision, it is possible to teach
computers to comprehend and analyze visual input from
the outside world, including pictures and videos.
It entails the creation of algorithms and systems
that can decipher, interpret, and comprehend visual
input in order to carry out operations like image and
facial identification, object detection and tracking, and
scene comprehension. Despite the contributions made by
other academics' work on this subject, there are still
certain difficulties to be resolved. The bottleneck in the
image/video processing aspect, among many others, is
the identification, selection, and tracking of bird activity
within the poultry farm. This study focuses on the use of
cameras in conjunction with specialized AI systems to
appropriately analyze flocks for health issues. It also
discusses the integration of AI-assisted technology.
Computer vision model was designed using deep
learning algorithm for monitoring and controlling
diseases in birds for the purpose of improving the safety
and productivity of the poultry system. This was
achieved through their captured images from their
droppings (feces) to determine their health state.Data
was collected from two groups of birds; the healthy and
the unhealthy infected with coccidiosis.By providing an early warning and
disease incidence prediction, the designed model, when
put into use, can function as an automatic monitoring
system. This model is to contribute to the advanced
development of computer vision in recent times and to
inform poultry farmers the new trend in the poultry
system to maximize profit.The quality of poultry
products will increase as a result of the correct analysis
of flocks for health issues using cameras integrated to
specialized systems and Artificial Intelligence (AI)
technology, which will increase bird survival rates.
Keywords :
Birds, Computer Vision (CV),Convolutional Neural Network (CNN), Deep Learning (DL), Poultry, Droppings, Coccidiosis.
