Description as a Tweet:

Ever find yourself lost in the hustle and bustle of a big city but can't seem to find the dang laundromat? Sometimes it's the simplest things that we often take for granted. That's where NewInTown comes in! All the closest essential services right in the palm of your hand.

Inspiration:

Being young avid travelers (and college students), we often find ourselves caught up in the excitement of exploring a new location. Although it can be an adventure, discovering a new place can also be disorienting, especially when you're unfamiliar with the surrounding community. It can be difficult to quickly identify the best place to go for the simplest and most essential services. This is why we decided to develop an app that could help similar users keep track of the best places to go for everyday tasks in an unfamiliar place.

What it does:

NewInTown is an intuitive iOS app that displays several categories of essential businesses (laundromat, groceries, pharmacy...etc) and allows users to compare the fastest routes to the nearest locations of interest. Users can choose to either track their current location or input a manual location, enabling them to plan their future travels with peace of mind. This app is geared towards those with a busy schedule, who may not have the time to peruse lists and lists of irrelevant Google data. NewInTown is simple, yet elegant, and provides busy users with a fast and user-friendly resource.

How we built it:

NewInTown utilizes Radar.io API and SDK to fetch locations relating to a specific category within a predetermined radius. The app takes utilizes the user's location services, with permission, to provide quick feedback at the tap of a button. Should the user choose to disable location services, they can manually perform a search based on an address. NewInTown is built using Swift and it employs CoreData to store the user's "favorited" locations even after closing the app for easy access. Within the Swift framework, we utilized MKMapView, an embeddable map interface that is similar to the one provided by the Maps application.

Technologies we used:

• SQL
• Swift
• Objective C

Challenges we ran into:

We ran into a lot of challenges during this project. Being freshmen, we don't have as much experience interacting with APIs or developing software. Taking on such a large project in such a short period of time was extremely daunting, but ultimately we rose up to the occasion and delivered a working product that we are very happy with. Specifically, we ran into the challenge of working with Swift constraints, as they are a very new topic and can be tricky to learn. Additionally, retrieving the user's location from their location services was a confusing task, but we were ultimately able to work out any bugs.

Accomplishments we're proud of:

Despite the challenges we faced, we are very proud of the product we have developed over the past two days and have gained confidence in our technical abilities. One accomplishment that we are particularly proud of is the UX that we have developed. We put a lot of work into developing the backend of the app but spent just as much effort perfecting our front-end UI to be as sleek and user-friendly as possible. We are also proud that we decided to stick with our idea despite struggling immensely to learn so much in so little time. We dreamed big with our idea and were able to implement all of the features we desired

What we've learned:

An important thing that we learned while building the project was how to integrate a database within our software. This was our first time working with databases, so we had to research exactly what including data management within the software entailed. We specifically learned how to use CoreData to create an entity and add attributes to store data. We also learned how to reference this data throughout the project to use and modify the data to complete different tasks.

What's next:

Since the Radar.io API is such an expansive location resource, NewInTown could be adaptable for several other ideas. Some possible creations in the future could be a COVID-19 resources app that cross references the locations in Radar.io’s database with testing centers and future vaccine providers. Another idea would be to integrate Machine Learning to predict a diagnosis from an inputted list of symptoms. From there, NewInTown’s current architecture could be used to display the nearest specialized doctors based on the Machine Learning output.

Built with:

We used GitHub, XCode, CoreData, and Radar.io API/SDK to build our project.

Prizes we're going for:

• Best Documentation
• Best Venture Pitch
• Best Mobile Hack
• Best Beginner Software Hack
• Most Creative Radar.io Hack

Emily Cooper
Frankie Furnelli

Table TBD