SWAP

Challenge

Swap is an iOS application that helps you create digital business cards, exchange it with important contacts, and never worry about losing a connection. The main challenge for this project was to work with optical character recognition technology to capture the content of the card, effectively picking up the real-world card text and storing the info into the application as a digital business card. We also had to implement a novel way to display all of the stored cards in the app so that the user could easily swipe and see them all. Other valuable information such as where and when the card was exchanged would also be required.

Solution

Design Thinking

When the client first approached us, there was a general idea as to what the high level requirements would be but, many details were still yet to be specified We needed to define what the application would actually look like. Our experienced design team worked to guide our client through the complete and renowned Design Thinking methodology. Within that process, the project was fleshed out in a lot more detail. Deeper thought was given into who the end users of the app might be. Questions were asked as to what the application should look like and why. How could we create a smooth and satisfying user experience? After having responded to these and many more questions, the design team then began the sensitive process of UI/UX design for the application. With a little hard work , the design assets were completed. Now it was time for the development team to begin their part of the work.

Key Features

Optical Character Recognition

The first feature we began to develop was the text recognition technology, OCR (Optical Character Recognition). There are many OCR libraries out there, so we started with one of the most popular ones, Tesseract OCR. During our initial testing we got good recognition results but much more work had to be done to improve its accuracy. Because the team decided to implement an alternative. Our new solution was the usage of a more advanced OCR solution called Google Vision API, which has a much better accuracy rates when detecting text compared to Tesseract. We also added a Natural Language Processor pipeline to distinguish each business card category with greater accuracy instead of only using string matching to equate them.

Mobile Client Database

On the backend side we needed a mobile client database that would allow automatic synching on any data changes to a remote server in order to achieve data redundancy and safety. CouchbaseDB, a non relational database met that requirement and was installed. Now, everytime user data is added or updated by the end user, the data will be immediately synched and backed up in a remote server. This prevents users from losing their business card data if anything should happen to the user's phone.

Location

We also implemented a map that displays where the user had exchanged the card using iOS geolocation services. This helps the user remember where that business card exchange took place.

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