Food Scanner is an app that helps people who have special food allergies or the want to avoid eating meat - like vegetarians, but also people who want to avoid to eat specific food ingredients. The app works with a barcode-scanner-web-technology and a specific filter-algorithm which works over a product database.
The filter algorithms search in the product description for ingredients which the user avoids to eat.
If the user is in a grocery store and wants to check a product to find out whether he can eat the product, he can scan the product and the app warns the user if there is a match with preset filter settings in the app.
Beyond this functionality, the app can also store filters from other users. This makes it possible for someone can go shopping for another person.
If there is a match with the filters and the user really wants or needs the product. The app gives recommendations for similar products which the user is allowed to eat.
In cooperation with:
Carl Albertsson, Carl Lindvall, Florian Wachter, Pontus Åberg, Simon Larsson Takman
The Empathize Stage is about gaining empathy and understanding of the problem that should be solved.
At the beginning of the course, all participants had to find a topic in the field of data visualization. Me and my group we discussed many topics and ideas but we decided to go for a topic which depresses us all. It was the problem of staying in a store and reading the back of a product in order to know if we can eat the product based on being a vegetarian.
We instantly jumped on the subject to set up some fundamental questions for an interview session, this was intended to find out whether or not this subject is appropriate. We were fortunate enough to study in Lindholmen, Gothenburg, which is situated in the center of a lot of tech companies that share the same cafeteria. This allows individuals from distinct areas, age groups, and genders to be interviewed to gain new perspectives. In reality, individuals agreed to our problems based on vegan and vegetarian food preferences, but we found even more insights about the large majority of individuals reporting issues with their food allergies.
From the insights we have acquired from our Interviews, we have created a collection of User Stories that will help us to empathize our target group and make it simpler to identify problems at the Define stage of the process.
A lot of the text on the product must be read by the customer, and even then it is not clear whether the customer can eat the product. Basis of manufacturing procedures some products have hidden ingredients that are not obviously defined in the product itself. People with allergies, diabetes, vegetarians, vegans, pescetarians are often not well informed and obviously consume the wrong products.
In a brainstorming session, we developed features that could solve the problem. Some of these features address a very challenging technology issue that needs to be resolved before we can proceed. For this reason, we have chosen to conduct technical research between our design stage in order to ensure that our concept is feasible.
One of the features we had to research was about the possibility to get specific data about a product over its barcode on the back. And, we were luky and found a database which could use for an implementation.
We had to write non-functional and functional requirements before we could begin creating wireframes. In order to produce a structure that helped to creates the flow and lastly the structure of the wireframes.
The wireframes were developed for four situations that we wanted to distinguish. Scan the item and set the filter for food allergies or unique preferences. A history of scanned products. If a user is fully committed to the product and registered, which will give it additional functionality. And lastly, if someone wishes to share their filters with someone else in case the other individual is purchasing products for that individual.
Hi-fi / Lo-Fi Prototyping
Due to time limitations, some features have been implemented in a hi-fi prototype and some have been implemented in a lo-fi digital prototype (Click Dummy) for testing.
In this technique, the current stage of the prototype is evaluated on which the prototype is working well and the prototype is working badly. This also resulted to an enhancement in the written requirements, which contributes to the faster development of the product during the implementation stage.
Moodboards, design systems and final screens have been produced during the implementation stage.