02 Project Overview - phthisic/EATUP GitHub Wiki

Problem Space

Food waste is a problem that needs to be solved urgently on a global scale. Studies have shown that a large amount of food waste occurs during the consumption stage and is driven by individual consumer behavior (Reynolds et al., 2019). Many consumers are worried about not eating enough because they don’t understand the weight of the cuisine, so they order too much. Instead of reducing food waste itself, it is better to encourage people to monitor the amount of food. In food consumption statistics, the food waste of many tourists is very prominent. But most of them cannot see the impact of food waste because they do not directly feel the adverse consequences.

Concept

EATUP is an application that contributes to reduce food waste during a journey by helping users understand the meals through an AR application. Its potential users are signal tourists. This is because tourists often fail to predict their appetite before ordering, which can cause food waste. By using AR technology, users can identify the exact size of the meals because it is more eye-catching than pictures. It displays objects in a more three-dimensional form so that people can receive richer information, such as the ingredients, weight, flavor of the meals. In addition, EATUP can offer the rate of wasted food and comment functions to make other potential consumers familiar with this meal. Hence, users can receive comments from other users who commented on this meal and marked the same rate of wasted food as them.

Design Process

Our process is iterative, we utilized the HCI Interaction Lifecycle Model as our basis for the whole design concept.

Establishing requirements and Design alternatives: They are the first step of the design concept. We confirmed our design domain through literature review and conducted user research involving observations, interviews, and cultural probes. The target users are set to tourists who are not familiar with the food during a trip. We determine the main reason and the first-round idea is to generate specifically pointed to the reasons.

More information about user research can be found here: Design Process

Prototype and evaluation: According to the user research, we designed a low-fidelity prototype, a mid-fidelity prototype, and a high-fidelity prototype with whole functions and AR technology. After every prototype design, we tested our prototype through evaluation methods to understand the needs of users further.

Redesigning: This step is aimed to modify the prototype according to the results from each evaluation iteration.

Prototype

The design idea iterates 4 times, and each is with a prototype.

First prototype:

According to the user research, we believe that there are two main points that lead to waste:

  • Tourists do not familiar with the food so they might waste food.
  • Tourists do not care about the influence of wasting food. Thus, we build the paper prototype which includes both an AR order meal page to help people understand the dishes and a data visualization page to show the influence of the waste.

Second prototype:

For this prototype, the idea did not change much, but the paper has changed to a digital form. It is mainly designed to get wider user feedback. Based on the user feedback from the first test (use paper and digital version), we found that:

  • The buttons on the initial page are easy to cause accidental touches as an AR interface.
  • The effect of residual food only takes effect once after eating.
  • Users cannot get the most effective information to make decisions.

Third prototype:

According to the feedback on the second prototype, we optimize the low-fidelity prototype. We decided to focus on helping people understand the dishes to stop wasting food. We include more useful information into the interface and trying to convey a complete experience of our idea. We also found that the homeland of the users would mainly influence their taste. Thus, we decided to enlarge the social function and shrink the mobile elements. The recommendation would highly depend on the user’s preference rather than where they come from. The location would only be a reference for certain flavor challenges.

Final prototype:

The final prototype is building with Unity and Vuforia so when doing the testing, the participants can use a functional prototype. Based on the third prototype, we found that interface influences users’ cognition quite a lot. Thus, the interface has changed a lot.

If you want to know more about our prototype iteration and user testing, please come to: Prototype iteration

Reference

Reynolds, C., Goucher, L., Quested, T., Bromley, S., Gillick, S., Wells, V. K., . . . Katzeff, C. (2019). Consumption-stage food waste reduction interventions–What works and how to design better interventions. Food Policy, 83, 7-27.