Intelligent ontological multi-agent for healthy diet planning

  • Authors:

  • Mei-Hui Wang;Chang-Shing Lee;Kuang-Liang Hsieh;Chin-Yuan Hsu;Chong-Ching Chang

  • Affiliations:

  • Department of Computer Science and Information Engineering, National University of Tainan, Taiwan;Department of Computer Science and Information Engineering, National University of Tainan, Taiwan;Graduate Institute of System Engineering, National University of Tainan, Taiwan;Innovative Digitech-Enabled Applications & Services Institute, Institute for Information Industry, Taiwan;Graduate Institute of System Engineering, National University of Tainan, Taiwan

  • Venue:
  • FUZZ-IEEE'09 Proceedings of the 18th international conference on Fuzzy Systems
  • Year:
  • 2009

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Abstract

Good eating habits can make human beings to live in a healthy lifestyle. When a person constantly eats too much or too little, it will have a high risk of causing a disease for him. Therefore, developing healthy and balanced eating habits is important for most people to stay away from diseases. This study proposes an intelligent healthy diet planning multi-agent (IHDPMA), including a personal profile agent, a nutrition facts analysis agent, a knowledge analysis agent, a discovery agent, a fuzzy inference agent, and a semantic generation agent for healthy diet planning. The IHDPMA provides a semantic analysis of healthy diet status for people based on the pre-constructed ontology by domains experts and results of fuzzy inference. With the generated semantic analysis, people can get healthy information about what they eat and make it easier to eat a balanced and healthy diet. The experimental platform has been constructed to test the performance of the IHDPMA. The results indicate that the IHDPMA can effectively work for healthy diet planning.