Autors: Rizanov, S. M., Yakimov, P. I.
Title: Cattle Disease Detecting IoT Thermographic System
Keywords: Artificial intelligence, cattle disease detection, cloud com

Abstract: The food industry is facing enormous challenges in order to ensure sufficient amounts of food for the expanding population, while meeting and fulfilling rapidly changing quality demands. With cattle being one of the essential food-supplying animal breeds, imposed are strict requirements towards their wellbeing support and monitoring. Within this work a novel developed IoT based thermographic system for cattle disease detection is presented, which allows scalability and direct farming applicability. Emphasis is additionally pointed towards methods for parasitic effects' cancellation.

References

    Issue

    2021 XXX International Scientific Conference Electronics (ET), 2021, Bulgaria, doi: 10.1109/ET52713.2021.9579577

    Full text of the publication

    Цитирания (Citation/s):
    1. K. Kumar Ghosh, M. F. Ul Islam, A. A. Efaz, A. Chakrabarty and S. Hossain, "Real-Time Mastitis Detection in Livestock using Deep Learning and Machine Learning Leveraging Edge Devices," 2023 IEEE 17th International Symposium on Medical Information and Communication Technology (ISMICT), Lincoln, NE, USA, 2023, pp. 01-06, doi: 10.1109/ISMICT58261.2023.10152110. - 2023 - в издания, индексирани в Scopus или Web of Science

    Вид: публикация в международен форум, публикация в реферирано издание, индексирана в Scopus