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DTSTAMP:20250421T091044Z
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DTSTART;TZID=Asia/Muscat:20250430T110000
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DESCRIPTION:The integration of predictive analytics\, driven by advancement
 s in Machine Learning and Artificial Intelligence\, has significantly tran
 sformed the dairy industry. This study utilizes extensive datasets\, which
  include milk production records\, environmental data\, and genetic profil
 es\, to support the development of Artificial Intelligence and Machine Lea
 rning-based decision support systems. These sophisticated tools are capabl
 e of forecasting milk production\, detecting significant patterns\, and id
 entifying key factors that impact dairy output. The insights gained from t
 hese systems enable dairy farmers to make well informed decisions\, effici
 ently allocate resources\, improve operational efficiencies\, and advance 
 bovine health care practices. Moreover\, the use of Artificial Intelligenc
 e and Machine Learning in predictive analytics allows farmers to quickly a
 dapt to environmental changes\, effectively manage risks\, and increase pr
 oductivity. This presentation proposes a novel methodology for predicting 
 milk yield and lactation patterns at various stages\, using a comprehensiv
 e dataset from one of Jordan’s largest dairy farms. The farm tracks appr
 oximately 4000 cattle\, each outfitted with individual sensors\, allowing 
 for continuous and detailed monitoring of milk output.\n\nCo-sponsored by:
  Amjad Gawanmeh\n\nSpeaker(s): \, Dr. Mohammad Alwadi\n\nUniversity of Dub
 ai\, Dubai\, United Arab Emirates\, United Arab Emirates
LOCATION:University of Dubai\, Dubai\, United Arab Emirates\, United Arab E
 mirates
ORGANIZER:amjad.gawanmeh@ieee.org
SEQUENCE:6
SUMMARY:Smart Dairy Farming: Predicting Milk Production with AI 
URL;VALUE=URI:https://events.vtools.ieee.org/m/482163
X-ALT-DESC:Description: <br /><div class="elementor-element elementor-eleme
 nt-53b9b45 elementor-widget elementor-widget-heading" data-id="53b9b45" da
 ta-element_type="widget" data-widget_type="heading.default">\n<div class="
 elementor-widget-container">\n<p>The integration of predictive analytics\,
  driven by advancements in Machine Learning and Artificial Intelligence\, 
 has significantly transformed the dairy industry. This study utilizes exte
 nsive datasets\, which include milk production records\, environmental dat
 a\, and genetic profiles\, to support the development of Artificial Intell
 igence and Machine Learning-based decision support systems. These sophisti
 cated tools are capable of forecasting milk production\, detecting signifi
 cant patterns\, and identifying key factors that impact dairy output. The 
 insights gained from these systems enable dairy farmers to make well infor
 med decisions\, efficiently allocate resources\, improve operational effic
 iencies\, and advance bovine health care practices. Moreover\, the use of 
 Artificial Intelligence and Machine Learning in predictive analytics allow
 s farmers to quickly adapt to environmental changes\, effectively manage r
 isks\, and increase productivity. &nbsp\;This presentation proposes a nove
 l methodology for predicting milk yield and lactation patterns at various 
 stages\, using a comprehensive dataset from one of Jordan&rsquo\;s largest
  dairy farms. The farm tracks approximately 4000 cattle\, each outfitted w
 ith individual sensors\, allowing for continuous and detailed monitoring o
 f milk output.</p>\n</div>\n</div>
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