Smart Ingredient Based Cooking

      Smart Ingredient-Based Cooking represents a significant advancement in the field of intelligent food technology and smart home automation. By integrating artificial intelligence, machine learning, IoT devices, and cloud computing, the system provides efficient recipe recommendations and intelligent cooking assistance based on available ingredients and user preferences. The research demonstrates that smart cooking systems can reduce food wastage, improve nutritional awareness, and simplify daily meal preparation activities.

[1] Freyne, J., & Berkovsky, S. (2010) Discussed intelligent food planning systems that help users make cooking decisions based on available ingredients and preferences. https://doi.org/10.1145/1719970.1720021 [2] Harvey, M., et al. (2013) Focused on reducing food waste through smart recommendation systems and efficient ingredient utilization. [3] Teng, T., et al. (2012) Presented ingredient-based recipe recommendation techniques that suggest meals from available ingredients. https://doi.org/10.1145/2380718.2380757 [4] Ge, M., Delgado-Battenfeld, C., & Jannach, D. (2010) Explained evaluation methods for recommender systems beyond simple accuracy measures. https://doi.org/10.1145/1864708.1864761  [5] Food and Agriculture Organization (FAO) (2019) Provided global statistics and insights on food loss, food waste, and sustainable food consumption.  [6] Yang, Y., et al. (2017) Developed recipe recommendation models that consider ingredients and user preferences. [7] Min, K., et al. (2019) Applied deep learning techniques for automatic ingredient recognition from food images. [8] Wang, H., et al. (2020) Explored machine learning applications in smart cooking and food recommendation systems. [9] Meyers, S., et al. (2015) Studied computer vision methods for recognizing food items and ingredients from images.  [10] Salvador, A., et al. (2017) Proposed cross-modal learning approaches to connect recipes with food images for better recommendations.