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- Vol. 5 Issue 4
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AI-Powered Smart Cooking Assistant
Authors
1Student, MCA, Deccan College of Engineering and Technology, Hyderabad, Telangana, India. 2Assistant Professor, MCA, Deccan College of Engineering and Technology, Hyderabad, Telangana, India.
Article Information
- Published In
- Volume 5, Issue 4 (2025)
- Published Online
- July-August 2025
- Pages
- 31-34
- Article Type
- Original Article
- Check for updates
-
References
1) Brown, T. B., et al. (2020). Language Models are Few-Shot Learners. arXiv preprint arXiv:2005.14165.
2) Vaswani, A., et al. (2017). Attention Is All You Need. In Advances in Neural Information Processing Systems (NeurIPS).
3) Wolf, T., et al. (2020). Transformers: State-of-the-Art Natural Language Processing. In Proceedings of EMNLP.
4) Chae, D. H., Lee, Y., & Park, J. (2020). Smart Kitchen Assistants: A Review of AI Applications in Cooking. ACM Computing Surveys, 53(6), Article 122.
5) Lin, J., Kang, J., & Liu, Q. (2020). Recipe Recommendation Using Graph Neural Networks. In Proceedings of the 14th ACM Conference on Recommender Systems (RecSys 2020).
6) Fallaize, R., et al. (2019). Using Wearable Technology and AI to Improve Diet and Health Outcomes. Nutrients, 11(11), 2515.
7) Martinez, S., & Kawka, M. (2021). AI for Sustainable Food Systems. Journal of Sustainable Development, 14(2), 45–56.
8) Ferrara, E., et al. (2021). The Role of AI in Health-Oriented Meal Recommendations. IEEE Access, 9, 11458–11470.
9) Pinder, C., et al. (2018). Exploring Meal Planning Behavior: Insights from Food Journals. Appetite, 123, 210–218.
10) Teng, C., Lin, Y., & Wang, H. (2012). Integrating Nutritional Knowledge in Meal Planning: A Computational Approach. Expert Systems with Applications, 39(2), 1336–1344.
11) Fang, H., et al. (2020). DeepFood: Deep Learning-Based Food Image Recognition for Dietary Assessment. IEEE Access, 8, 63434–63444.
12) Min, W., et al. (2019). A Survey on Food Computing. ACM Computing Surveys (CSUR), 52(5), 1–36.
13) Trattner, C., & Elsweiler, D. (2017). Food Recommender Systems: Important Contributions, Challenges and Future Research Directions. arXiv preprint arXiv:1711.02760.
14) Zhao, Z., Xu, J., & Guo, Y. (2022). AI-Based Recipe Generation Using Reinforcement Learning. Journal of Artificial Intelligence Research, 73, 335–358.
15) Achananuparp, P., et al. (2018). Nutribuddy: A Personalized Nutrition Recommendation System. Proceedings of the 2018 International Conference on Digital Health, 95–99.
16) Karpyn, A., et al. (2020). Application of Technology in Meal Planning for Nutrition Interventions. Journal of Nutrition Education and Behavior, 52(1), 15–25.
17) Lajnef, N., et al. (2021). IoT-Based Smart Kitchen for Recipe Prediction and Ingredient Management. International Journal of Interactive Multimedia and Artificial Intelligence, 6(6), 39–47.
18) Dey, A., & Bedi, P. (2020). A Multi-Agent Framework for Recipe Recommendation Based on Dietary Constraints. Expert Systems with Applications, 140, 112881.
19) Silva, A., et al. (2021). Smart Kitchen and AI: An Ontology-Based Recipe Recommendation System. Procedia Computer Science, 181, 858–865.
2) Vaswani, A., et al. (2017). Attention Is All You Need. In Advances in Neural Information Processing Systems (NeurIPS).
3) Wolf, T., et al. (2020). Transformers: State-of-the-Art Natural Language Processing. In Proceedings of EMNLP.
4) Chae, D. H., Lee, Y., & Park, J. (2020). Smart Kitchen Assistants: A Review of AI Applications in Cooking. ACM Computing Surveys, 53(6), Article 122.
5) Lin, J., Kang, J., & Liu, Q. (2020). Recipe Recommendation Using Graph Neural Networks. In Proceedings of the 14th ACM Conference on Recommender Systems (RecSys 2020).
6) Fallaize, R., et al. (2019). Using Wearable Technology and AI to Improve Diet and Health Outcomes. Nutrients, 11(11), 2515.
7) Martinez, S., & Kawka, M. (2021). AI for Sustainable Food Systems. Journal of Sustainable Development, 14(2), 45–56.
8) Ferrara, E., et al. (2021). The Role of AI in Health-Oriented Meal Recommendations. IEEE Access, 9, 11458–11470.
9) Pinder, C., et al. (2018). Exploring Meal Planning Behavior: Insights from Food Journals. Appetite, 123, 210–218.
10) Teng, C., Lin, Y., & Wang, H. (2012). Integrating Nutritional Knowledge in Meal Planning: A Computational Approach. Expert Systems with Applications, 39(2), 1336–1344.
11) Fang, H., et al. (2020). DeepFood: Deep Learning-Based Food Image Recognition for Dietary Assessment. IEEE Access, 8, 63434–63444.
12) Min, W., et al. (2019). A Survey on Food Computing. ACM Computing Surveys (CSUR), 52(5), 1–36.
13) Trattner, C., & Elsweiler, D. (2017). Food Recommender Systems: Important Contributions, Challenges and Future Research Directions. arXiv preprint arXiv:1711.02760.
14) Zhao, Z., Xu, J., & Guo, Y. (2022). AI-Based Recipe Generation Using Reinforcement Learning. Journal of Artificial Intelligence Research, 73, 335–358.
15) Achananuparp, P., et al. (2018). Nutribuddy: A Personalized Nutrition Recommendation System. Proceedings of the 2018 International Conference on Digital Health, 95–99.
16) Karpyn, A., et al. (2020). Application of Technology in Meal Planning for Nutrition Interventions. Journal of Nutrition Education and Behavior, 52(1), 15–25.
17) Lajnef, N., et al. (2021). IoT-Based Smart Kitchen for Recipe Prediction and Ingredient Management. International Journal of Interactive Multimedia and Artificial Intelligence, 6(6), 39–47.
18) Dey, A., & Bedi, P. (2020). A Multi-Agent Framework for Recipe Recommendation Based on Dietary Constraints. Expert Systems with Applications, 140, 112881.
19) Silva, A., et al. (2021). Smart Kitchen and AI: An Ontology-Based Recipe Recommendation System. Procedia Computer Science, 181, 858–865.
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