Project Description

#Know What You Eat

There are many food serving outlets around us. Some serve to large number of people such as the university cafeterias and canteens. Others are various restaurants. Many people eat their meals at one of these places while not very aware of what they eat, that is how healthy it is, how many calories they take, what is the amount of protein they consume and such. With this project, we will try to let our users know the answers of these questions while also providing a detailed directory based on consumption preferences of users, popularity of servers, and many different filtering options. Our goal is to serve people to learn more about what they eat in terms of macro and micro nutrients.

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Food servers will be able to create a profile and add descriptions about the food they serve. The nutritional properties of the food will be determined from recipes through nutritional information about ingredients. Information should be gathered from university cafeteria, canteens, and restaurants about what they serve and how they describe it.

Regular users will be able to explore servers and foods and to see the information about the food. In addition to nutritional values, eating preferences of users will also be important. Diets such as vegan and vegetarian, allergies, foods which are not preferred, calorie intake restrictions of users will be part of their profile. Searching and displaying information must be filtered according to user preferences.

Users will be able to tag, comment on, and rate food as well as the servers. They will be able to post media in their comments. Such information can be very useful for users to benefit from others' experiences. One can indicate "I ate that" for a food via a button. She can also indicate what she ate for multiple foods as well as with other users. The user should be able to view their history of consumption. They should also be able to share foods, servers, and comments with other users as well as via social media.

Servers can also benefit from comments and reactions to improve their service quality. User preferences among foods of a server also can help enormously to the server. Thus, an analysis of user contributions should be presented to servers.

Semantic tags will be used to facilitate semantic search and recommendations. Web annotation model must to be used for annotation for tagging.

The application must have a web and a mobile client, preferably Android. Localization must be handled for alternative languages.