Dr. Mohammad Alwadi of Arab Open University – Jordan branch, Jordan, and University of Canberra, Australia

The integration of predictive analytics, driven by advancements in Machine Learning and Artificial Intelligence, has significantly transformed the dairy industry. This study utilizes extensive datasets, which include milk production records, environmental data, and genetic profiles, to support the development of Artificial Intelligence and Machine Learning-based decision support systems. These sophisticated tools are capable of forecasting milk production, detecting significant patterns, and identifying key factors that impact dairy output. The insights gained from these systems enable dairy farmers to make well informed decisions, efficiently allocate resources, improve operational efficiencies, and advance bovine health care practices. Moreover, the use of Artificial Intelligence and Machine Learning in predictive analytics allows farmers to quickly adapt to environmental changes, effectively manage risks, and increase productivity.  This presentation proposes a novel methodology for predicting milk yield and lactation patterns at various stages, using a comprehensive dataset from one of Jordan’s largest dairy farms. The farm tracks approximately 4000 cattle, each outfitted with individual sensors, allowing for continuous and detailed monitoring of milk output.

Biography:

Dr. Mohammad Alwadi is an Assistant Professor at the Arab Open University – Jordan branch and a Professional Associate at the University of Canberra, Australia. He holds a PhD in Information Sciences and Engineering, with expertise in data science, AI, and machine learning. Dr. Alwadi has published extensively in the fields of sensor networks and intelligent systems and is actively engaged in research leadership, academic innovation, and international collaboration.