A new agentic AI system designed to optimize workout routines and macronutrient management has been developed by a computer engineering team at Srinakharinwirot University (SWU) in Thailand. Published on the SWU SoftwareEngineer YouTube channel, the project demonstrates an advanced application of artificial intelligence in the health and fitness domain.
The system leverages agentic AI principles—autonomous agents that can perceive their environment, make decisions, and take actions—to create personalized exercise regimens and dietary plans. By analyzing user data, including fitness goals, current physical condition, and nutritional needs, the AI dynamically adjusts workout intensity, exercise selection, and macronutrient ratios (proteins, fats, and carbohydrates) in real time.
This innovation falls under the broader umbrella of AI-driven digital health, integrating technologies such as generative AI, fuzzy logic, and neural networks. The project was developed by the Computational Intelligence Research Lab (CIRL) at SWU's Department of Computer Engineering. The team emphasized that the system is designed for educational and knowledge-sharing purposes, not commercial gain.
The video description notes that the system combines elements of software engineering, knowledge engineering, and data engineering, showcasing how modern AI techniques can be applied to solve practical problems in health optimization.