Please use this identifier to cite or link to this item: https://dspace.univ-guelma.dz/jspui/handle/123456789/18267
Title: FarmlQ: Al-powered virtual assistant for precision livestock farming
Authors: MESSAHEL AYOUB, KOLLI MAROUA
Keywords: Al, loT, Smart Farming, monitoring, Deep Learning
Issue Date: 2025
Publisher: university of guelma
Abstract: Precision Livestock Farming is a system that introduces a welfare dimension while en hancing herd management through technological advances. Manual monitoring strategies which are a common practice in husbandry have time as well as cost constraints. This gap can permit health challenges to develop into key outbreaks within herds, resulting disruption of economic activities and the threat to public health, specially in the case of zoonoses. The innovative Precision Livestock Farming on the market developed within this framework, utilising A technologies, smart cameras and IoT sensors, offers solution for constant monitoring of the animals’ health status, provide an early warning in the case of illnesses and allow giving appropriate support to every single animal. Economically, this assistant could offset some losses due to reduction in the ability to transmit diseases leading o reduced expenditure on not only veterinary treatment but also the number of deaths. The assistant’s objectives focus on enabling self interactive and responsive system to health problems and behaviors in order to limit the number of human intervention and enhance the rate of response from a health perspective. The selected tools encompass individual tracking of animals with the use of smart cameras, the use of loT sensors for the purpose of gathering environmental and behavioral context and using of deep learning algorithms for the purpose of predictive analysis. Key actions would be supported by data management platform for this purpose, at the same time notification systems would serve the purpose of rapid responses
URI: https://dspace.univ-guelma.dz/jspui/handle/123456789/18267
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