interiqr: Unobtrusive Edible Tags using Food 3D Printing

Document Title

interiqr: Unobtrusive Edible Tags using Food 3D Printing

Document Information

• Subject Area: Edible tags, human-food interaction, innovative applications of digital 3D food printing
• Keywords: digital manufacturing, food 3D printing, human-food interaction, invisible tags, edible codes

Research Background and Problem

• Identified Problems or Challenges:

  1. Food tags have broad applications in storing information, identifying food origins, and enhancing dining experiences, but existing methods often compromise food aesthetics or are difficult to consume.
  2. Most existing embedded tags rely on physical or chemical alterations of the food surface, which may limit ingredient choices and negatively impact food appearance and appeal.
  3. Hidden information needs to be machine-readable while remaining virtually invisible, a balance that current technologies struggle to achieve.

• Significance of the Research:

  1. Developing invisible and edible tags has significant implications for the food industry, personalized dining, and innovative applications in human-food interaction (HFI).
  2. It promotes advancements in food traceability, personalized diets, and intelligent food management.

• Motivation and Related Work:

  • To address the conflict between tag functionality and food aesthetics/edibility, the researchers designed an innovative framework combining food materials, 3D printing technology, and image processing, building on extensive prior work in digital 3D printing and human-computer interaction.

Solution

• Proposed Method or Solution:

  1. A method (interiqr) is proposed to embed information inside food using 3D printing without altering the external geometry, making the information tag invisible to the human eye but machine-readable.
  2. QR codes (or AR markers) are constructed using internal infill structures or multiple food materials during the 3D printing process.

• Innovative Aspects:

  • Tags are concealed within the food and made entirely from edible materials.
  • An end-to-end 3D printing workflow is provided, integrating data embedding and tag decoding.
  • A backend image processing technique is developed to capture hidden information using backlighting and a camera.

• Implementation Steps and Key Technologies:

  1. Tag Generation:
     • Based on user-provided text, images, or hyperlinks, the infill patterns and printing paths of the 3D-printed food are calculated.
     • For infill rates below 70%, binary encoding is generated using air gaps and infill structures; for rates above 70%, multiple food materials (e.g., different-colored food materials) are used for marking.
  2. Food 3D Printing:
     • A food-specific 3D printer (e.g., syringe-based printer) is used to embed tags into the food.
     • Required support structures and parameters are automatically calculated by dedicated software.
  3. Tag Decoding:
     • Backlighting (visible or infrared light) is used to illuminate the food, and a camera captures the images.
     • Image processing techniques extract QR codes or marker information, which are decoded using standard image libraries (e.g., QR code libraries).

Research Outcomes

• Specific Outcomes:

  1. Successfully developed a complete workflow for creating invisible edible tags using 3D printing.
  2. Validated the tag's invisibility, readability, and edibility on various food materials (e.g., cookie dough).
  3. Provided practical evaluations of tag embedding, including transmission spectrum experiments, tag size testing, and user dining experience surveys.

• Advantages Over Existing Solutions:

  • Tag Invisibility: By using infill structures or material combinations, the food's geometry or appearance remains unchanged.
  • Edibility: Tags are entirely made from food materials, requiring no non-food components.
  • Functionality: Hidden data or markers enhance food interactivity and traceability.

• Experimental or Evaluation Results:

  1. Tag Readability: Tags created with infill structures or multi-materials maintained good machine recognition under various lighting conditions; combining air gaps with multi-materials extended the recognition distance to 35 cm.
  2. Tag Invisibility: Improved support structures resolved surface bulges and depressions during the baking process, resulting in a smoother contour.
  3. User Experience: In user testing, food with embedded tags showed no significant differences in texture or perceived sweetness compared to food without tags.

• Limitations and Future Directions:

  1. For more complex ingredients (e.g., moist or unstable materials), the robustness of internal structures needs further optimization.
  2. Tag information capacity is limited; the current system can embed small QR codes but not large, complex datasets.
  3. The application of infrared spectrum tags requires exploration of more materials and absorption properties.
  4. Flexibility: Adapting the method to other food manufacturing techniques (e.g., molds) and more diverse food forms (e.g., vegetables or meat).