Virtual Nutritionist using AI
Siddarthan Chitra Suseendran1, Nanda Kishore B3, Josephus Andrew4, M.S.Rajyashree5
1Siddarthan Chitra Suseendran, Student Computer Science and Engineering SRM Institute of Science and Technology, Chennai (Tamil Nadu), India
2Nanda Kishore B., Student Computer Science and Engineering SRM Institute of Science and Technology, Chennai (Tamil Nadu), India
3Josephus Andrew, Student Computer Science and Engineering SRM Institute of Science and Technology, Chennai (Tamil Nadu), India
4Ms. Rajyashree, Assistant professo, Computer Science and Engineering SRM Institute of Science and Technology, Chennai (Tamil Nadu), India
Manuscript received on 18 June 2019 | Revised Manuscript received on 25 June 2019 | Manuscript published on 30 June 2019 | PP: 474-477 | Volume-8 Issue-5, June 2019 | Retrieval Number: E6978068519/19©BEIESP
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Good food is a standout amongst the most basic angles for the family, particularly for their dynamic individuals as solid eating regimen for them results in better life including the expansion of their capacity to learn, work out, and notwithstanding carrying on. In this way, a requirement for a full help for furnishing them with solid nourishment is a fundamental focus to reach. In this paper, we propose a model for a sustenance master framework which point is to give its clients the nourishment skill. It creates solid dinners for people in various ages as indicated by various criteria including their development stage, sexual orientation, and their wellbeing status. An application is created and a few contextual investigations are connected to show how the proposed model can be connected for deciding one’s nourishment utilizing Artificial Intelligence (Machine and deep learning).
Keywords: Artificial Intelligence, Machine Learning, Supervised Machine Learning , Unsupervised Machine Learning , Macronutrients, Micronutrients, TDEE ,BMR
Scope of the Article: Machine Learning