May 12, 2015

Within the United Kingdom many individuals have dietary requirements or preferences, making it difficult for businesses to successfully organise meals with multiple attendees. To tackle this problem Dine was created, a busineses meal planning service utilising open data sources to simplify the process of arranging a meal that meets the needs of all attendees. Dine's natural language form The aim of this project was to make use of open data to create a novel application which could be turned into a successful business idea. Once implementation had finished, the product was to be pitched to a panel of industry experts who would assess the viability of the idea and determined whether a business venture was plausible. Restaurant shortlist We believed that an application which could exploit the open data associated with recent EU legislation — stating allergen information had to be provided for all uncovered food — could be turned into one such successful business. Restaurant detail The Django web framework was used to allow rapid prototyping of the application and demonstrated Dine’s core ideas. Features included:

  • Use of Google’s services to allow meal events to be sychronised to a user’s calendar and gain quick access to a user’s address book for inviting attendees;
  • A clean, minimal user experience to allow an event organiser to quickly, create an event and choose the most suitable restaurant based on images of the food, food hygiene data, location, price, and user rating;
  • Use of Open Street Map (OSM) to plot the location of a venue; and
  • Use of Instagram and Foursquare APIs to source the images and restaurant details respectively.

The application was well received by the panel of judges and they believed that there was future potential for the idea.

Repository Link: https://github.com/eskriett/dine
Languages: Python, JavaScript
Collaborated with: Jamie Davies, Miles Armstrong, Chantel Spencer-Bowdage