Eatable

Inspiration

Food Waste simply put, is food which is fit for consumption but consciously discarded at the retail or consumption phases. As consumers of food, how can we put an end to food waste and utilise the food we have at our own disposal in our fridges, cabinets, pantries, or larders? Using our Pega skills and knowhow, Team Canyon set about creating an App, with the aim of providing the perfect way to either donate food or provide the perfect recipe for our ingredients. We wanted to create a practical solution to a real-world problem which in turn could help us to be more conscientious in our choices and provide an opportunity to learn some new recipes and cuisines. This led to the inspiration and guiding theme for the eatable App.

What it does

The eatable App provides two core journeys which aid in ending food waste. Journey 1: “Select a Recipe” provides a pathway to entering the ingredients you wish to use to find recipes based on meal type and cuisine. Using Pega Decisioning, the eatable App also recommends the most suitable recipes based on the entry. There is also an opportunity to add recipes to a Meal Planner which you can save and download to help end food waste. The user can also provide feedback on the recipe and upload pictures of their meal. Journey 2: “Donate Food Items” provides an opportunity to enter the food items you wish to donate into our decisioning engine which in turn will return the nearest foodbanks based on your location. An email can also be sent to the Foodbank to notify them of your intent. The app also has a handy Helpful Food Tips blog page which provides useful ways you can reduce food waste in your kitchen. We hope you will join our bid to end food waste.

How we built it

Built on Pega Platform 8.7, Eatable uses pega custom UI built using Theme Cosmos, pega case management capabilities and out of the box features. The application business logic uses pega Digital Experience (DX) API. The Pega Decisioning feature has been used to perform predictions related to recipes offered to the user based on ingredients added and their food choice like meal type, cuisine, food type. We used the Pega Express approach of four phases to support solution delivery.

1. Discover- Ideation Phase to drill down the idea of food wastage & the requirements for eatable app. Identified 2 use cases for finding recipe & the other for food donation (MLP).
2. Prepare - Peg Env setup, Gathered info about the Open Source API’s available for Food Recipes/Food Banks List. Logged user stories in Agile Workbench
3. Build - Case Type creation with App Studio, Integration for external API’s, UI Mapping, Dataflow/Adaptive Model configuration
4. Adopt - Feedback from co-team members, Documentation, Release Preparation

Solution We identified our case type Eatable and our data model. We worked on the workflow and the majority of the views in the application using Pega App Studio. Screens were designed using pega Theme Cosmos. Customized the pega OOTB login screen and user portal for Eatable app. Implemented data page for sourcing data for UI elements.

Pega decisioning - ADM Once the Food Recipe API provides the List of Recipes. Recipe List is imported in the strategy as Propositions. ADM component is used to create recipe models which have predictors defined as Food Items, Meal Type, Type of Food, Cuisine selected by the user on UI. Propensity calculated by ADM is used to order the Recipes. Ranking returned by strategy results is used to order the recipe list on UI.

Custom APIs We used two custom REST APIs for finding local food banks based on post code and another one for finding recipes based on user food choices and ingredients. We used pega OOTB connect REST integration services for configuring the APIs.

What we learned

As a part of provisioning the solution to this challenge, we learnt:

1. Information related to public API’s which are readily available for Integration to get Recipe Information, local food charity/banks details etc.

2. Pega Decisioning capabilities, which can be used to predict recommended recipes for a user based on their food choice selection/preferences.

3. Pega google map api, which can be used to show the geolocation of local food banks.

4. We can solve the problem of food wastage by making recipes or donating food to local food banks and create healthier living for human beings.

5. Conceiving, designing, and building an application within such a short period of time provided us great opportunity to learn and work together as a team.

What's next for Eatable

Eatable MLP1 version was basically developed for individual users to reduce food waste at home by finding recipes and ways to donate food. Also including the meal planner facility in the app helps user to plan meals in advance and shop food items accordingly. MLP2 of eatable can be extended for business users like charities, restaurants owners and foodbanks to find items in their locality to pick up as donation. Eatable can provide a platform for these business users to connect and pick extra food items ready for donation or buying. Proposed plan to develop another case for business users to login and using reporting capabilities to search for food donation bags. Also include a feature for tracking the food items shopping list based on usage from recipes and donations.

Built With

• adm
• case-management
• decisioning
• google-javascript-api
• pega8.7
• rest-api
• theme-cosmos