Abstract
dc:descriptionSmell and food have always been important in different cultures and countries. However, we haven't yet developed a method to document and record the food culture. Human society can only describe a recipe through words and images for a long time. And the smell and taste of food, which is the most important part, can not be recorded due to the limitations of existing technologies and the lack of people's interest in smell. The smell and taste of family meals are so particular for individuals and families. The odor-evoked memories associated with the family member pass from generation to generation, and they are the most valuable memories that accompany one's entire life. Therefore, I tested and developed a method that combines artificial intelligence vision and olfactory to record the cooking process and then utilize the smell information as a reference for later duplicating the same meals. By applying the latest technology about AI olfactory, the machine can record the smell changes during the cooking process and record the unique smell pattern that reflects the cooking status of the food. And that smell pattern will tell the user how well the food should be cooked through an application on smartphones, tablets, or smart watches while cooking. The name of this product is called Odora Smell Camera. The smell camera may not be the ultimate way of applying AI nose to the food industry. There is still a lot of work that needs to be done to let my design be a mature product. But I hope this thesis can draw more attention from the public to this young industry full of potential.
Degree
thesis:*- Name thesis:degree_name
- M.F.A.
- Level thesis:degree_level
- Thesis
- Discipline thesis:degree_discipline
- Art and Design
- Grantor
- University of Illinois at Urbana-Champaign
- Year dc:date
- 2022
Author and committee
dc:creator, dc:contributor.*- Author dc:creator
-
- Tang, Zhihao
- Contributors dc:contributor
-
- Sethi, Suresh
- Raheel, Salman
- Bohn, Dawn M
Subjects
dc:subject × 4Rights
dc:rights- Statement dc:rights
-
- Copyright 2022 Zhihao Tang
- Language dc:language
- en, eng
Identifiers
dc:identifier.*- Handle dc:identifier
- https://hdl.handle.net/2142/116269