Using Digital Twins and Predictive Analytics to Enhance Chicken Production Inventory Management

In today’s global market for chicken, producers of broiler hatching eggs face challenges in managing production
efficiently. Traditional methods struggle with complex record-keeping and a lack of real-time monitoring and
prediction capabilities. To overcome these challenges, we propose a digital twin framework—a virtual copy of the
chicken production system. This framework uses synthetic data generated by models like Generative Adversarial
Network and transformers to simulate realistic egg production scenarios. The framework includes layers for the
physical environment, virtual replication, data storage, analytics using Machine Learning, and user interaction. By
integrating digital twin technology, we aim to enhance data management, real-time monitoring, and control in
chicken production, optimizing efficiency and decision-making for producers.

Faculty Supervisor:

Ralph Deters

Student:

Partner:

Saskatchewan Broiler Hatching Egg Producers

Discipline:

Computer science

Sector:

Agriculture

University:

University of Saskatchewan

Program: