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Article Details

Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.

Fault Tolerance Smart Egg Incubation System with Computer Vision

Author 1: Emiliyan Petkov
Author 2: Teodor Kalushkov
Author 3: Donika Valcheva
Author 4: Georgi Shipkovenski

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Digital Object Identifier (DOI) : 10.14569/IJACSA.2023.0140260

Article Published in International Journal of Advanced Computer Science and Applications(IJACSA), Volume 14 Issue 2, 2023.

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Abstract: Reliability of incubators is one of their most important specifications. Development of wireless, cloud and computer vision based technologies gives new possibilities for work process control and increasing fault tolerance. Regardless of whether the hatching is in the field of mass production or in the breeding of rare species of birds, detecting a critical situation and sending timely notifications can prevent serious losses. Experience shows that network isolated solutions are not reliable enough and good management requires complex algorithms that are beyond the capabilities of a local, single controller. Even with the duplication of some sensors and actuators, incubators without external connection are high risk due to the fact that their controller is a central point in the architecture and can fail, leaving the farmer with no alert about the accident. The report presents a solution that uses periodic checks from cloud structures on the condition and operability of the incubator. In parallel, a video surveillance system analyzes the internal environment and the condition of hatching chicks. When potential and real risks occur, the system sends notifications to the responsible persons even to his or her wrist. Additionally, the proposed smart egg incubation methodology has been found to reduce the amount of time required for farmers to oversee the incubation process by up to 50%, allowing them to focus on other important tasks while still ensuring optimal hatching conditions for their eggs. Overall, the proposed methodology offers a significant improvement in egg incubation efficiency and reliability, with potential applications in both commercial and personal settings.

Keywords: Hatching; incubation; computer vision; cloud architecture; sending alerts; smart farming; internet of things

Emiliyan Petkov, Teodor Kalushkov, Donika Valcheva and Georgi Shipkovenski, “Fault Tolerance Smart Egg Incubation System with Computer Vision” International Journal of Advanced Computer Science and Applications(IJACSA), 14(2), 2023. http://dx.doi.org/10.14569/IJACSA.2023.0140260

@article{Petkov2023,
title = {Fault Tolerance Smart Egg Incubation System with Computer Vision},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2023.0140260},
url = {http://dx.doi.org/10.14569/IJACSA.2023.0140260},
year = {2023},
publisher = {The Science and Information Organization},
volume = {14},
number = {2},
author = {Emiliyan Petkov and Teodor Kalushkov and Donika Valcheva and Georgi Shipkovenski}
}


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