When was the last time you cleaned your fridge and didn’t find half of a sandwich, few vegetables/fruits that had been rotting there for two weeks? Or having to throw away the excess food cooked as a result of overestimation? United States sees a total wastage of about 35 MILLION TONS of food each year worth $165 BILLION, and for an average American family, that approximately evaluates to $2,200 per household per annum. An incredible 40 percent of the available food supply in the U.S. is never consumed, meanwhile, millions of Americans are suffering due to lack of food. Landfills due to food wasted are increasing and contributing to excessive generation of greenhouse gas along with land and water pollution. This is not just a problem faced in the United States, but is a Global issue. On January 13, 2016, France became the first country in the world to pass a law requiring supermarkets to donate food that is approaching its expiration date instead of throwing it away.

What it does

“RotMeNot” is a software solution which runs seamlessly on all platforms, that provides the user a real time inventory status of all the food items previously purchased and available in his/her personal space, by incorporating automatic update of inventory list by capturing the image of the shopping receipt, extracting information like the items purchased, quantity, cost, category and its expiration date. Very often we find ourselves in the confusion of having to decide what to cook with the ingredients available to us. Our system uses the information in the inventory to then provide alerts of food items with approaching expiration dates and provide an option to either consume the food item by suggesting recipes or donate it. As the application is already aware of what and how much the user has consumed throughout the day, it informs the user of the dietary supplements consumed and suggests recipes or food items with low/high percentage of remaining necessary nutrition for a balanced diet. “RotMeNot” also provides a platform to plan your shopping using information about the availability of the items in your fridge and the quantity to be bought. Each user is offered the functionality of segregating his groceries into private and public. Food listed under public is up for grabs and available in a list, “Food near me”. Selection of a particular food item leads the user to a google map with the location where it is available. This includes a rating system for the provider, to maintain trust and quality of products.
When the user wants to sell excess food or groceries, prices of the same is automatically suggested by the application according to the market rates at which the user purchased but the user always has the option to override this.

How I built it

The server is hosted on Digital Ocean. The UI/UX of the application is built and tested on Ionic platform, which is built on top of Apache Cordova and Angular.js. Optical character recognition uses Cloud Vision API with a custom parser to extract food items, costs and purchase dates. Locations of nearby food is populated on maps using the Google Maps API.

Challenges I ran into

The team had not previously worked with AngularJS, but worked swiftly to pick up the language and build the application within 36hrs. Getting accuracy of the OCR was tricky and time consuming. We started out with an accuracy of 40% and worked our way up to 80% accuracy.

Accomplishments that I'm proud of

Getting OCR to work was tricky and time consuming. The team managed to build an application with 7 crucial features within 36 hours.

What I learned

Setting up the Android and Ionic platform definitely builds character -- lots of syntactic differences in Mobile and Web versions even though both use HTML/CSS/JS. Ionic is not as easy to understand and use as they claim to be.

What's next for RotMeNot

Suggest recipes according to the user’s diet plan. In app payment system between the buyer and seller Powerful machine learning algorithms for more accurate estimation of food item. Gamification with respect to user with least amount of food wastage. Prescriptive analytics according to nutrition in diet.


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