This research explores the application of federated deep learning to optimize sustainability in food management and reduce waste in refrigeration systems.
Utilized federated deep learning techniques to analyze food waste data.
Simulated virtual refrigeration scenarios to assess environmental impacts.
Employed models to evaluate triple bottom line outcomes.
Identified significant reduction in food waste through optimized refrigeration practices.
Demonstrated lower greenhouse gas emissions associated with improved management.
Showed that integrative approaches yield better economic and environmental benefits.
Resumen
The world food systems are inefficiently trapped with at least one billion tonnes of food wasted every year, which adds 8-10% of the anthropogenic greenhouse gas emissions, 1 trillion in...