## Inspiration

A lack of housing is far from the only issues that homeless individuals face. With lack of support, information, and assistance services, the homeless population is largely unaware of and isolated from proper healthcare services.

Currently, the only assistance most homeless individuals have is from outreach workers, who may be able to provide assistance with registering for medical insurance (free for most homeless individuals but often not taken advantage of), arranging medical appointments, addressing medical issues, etc. However, the current infrastructure for outreach workers to reach out and stay connected with these individuals is either very unreliable or nonexistant. Often, these are one-time street encounters or buried in some excel-like platform unlikely to be revisited in the near future, if at all.

## What it does

HealthDisplaced is a platform designed to address this. We offer a platform for outreach workers and companies to record any and all health-related data from homeless encounters on a case-by-case basis. Our platform allows outreach workers to input data on important information like location, medical insurance status, date since last medical checkup, immediate health concerns, and more. It also flags contacts when pressing action is needed, such as when it has been more than a year since a particular contact's last medical check-up. It's easy to use, comprehensive, and great streamlines the case-recording process for outreach workers.

## How we built it

We built this using React as our frontend, and Convex as our backend. We used Convex to store all relevant data for homeless encounters, and powerful React component-based features allowed us to generate an easy-on-the-eye, organized, and aesthetic platform to record health-related homeless encounters.

## Challenges we ran into

This was our first time working with web development, so we found that there was a huge learning curve. We faced issues with intuitively thinking about design through code, debugging usage of state and context, and ensuring that everything we built could work in tandem with each other.

## Conclusion

All in all, we believe that HealthDisplaced meets a really strong, yet largely overlooked need. The plight of the homeless and the efforts of outreach workers is huge issue in our society and largely growing. Our platform provides the opportunity to increase the efficiency and ease at which this issue is being addressed, and I think that's pretty powerful.

## What's next for HealthDisplaced

First, we'd love to implement more features, such as a more comprehensive flagging feature, action item reminders, a map to track real-time encounters, and more.
After that, we'd love to get this into the hands of social outreach companies so that outreach workers can take advantage of the ease and convenience the platform offers.
## Inspiration

Our research into the lives of the disabled demonstrated how much the blind are forced into being dependent on others, so we thought what's an everyday task that can grant some autonomy the blind with, and we came up with shopping.

## What it does

Vise is an entrance to aisle and aisle to item android navigation app. Our user inputs their grocery list for

## How we built it

## Challenges we ran into

-Node-red limitations: Initially, we started as a web-app using node-red, but node-red Bluetooth limitations made it challenging to continue to use it. Therefore, we moved on to a Native Android, which made it much easier.
Finding the specific beacons of interest:

-Translating suggested path to ordinal directions: Our algorithm to calculate a path gives out an array of (row, col) coordinates, and translating that into ordinal directions was a bit challenging as we had to consider which direction the person is facing, as well as where that person headed to.

-Native android development was hard

-Triangulating location: Calculating the location of the person given distances to the 3 closest beacons

-Finding optimal route: There are multiple random variable inputs that coming up with an optimum shortest path algorithm was challenging. However, our algorithm gives a very good short path, even though it might not be the optimal one in some cases.

## Accomplishments that we're proud of

Finishing it

## What we learned

Native android development is hard
Algorithms are cool
Marketing matters
Companies have cool services

## What's next for Vise

Improvements:
-More optimal route calculation: we can definitely come up with a more efficient algorithm if given more time.
-Users will be able to use voice commands to input grocery list to the app
-Crowd Sourced Image recognition for a more accurate and updated location of items.

Alternate applications:
Navigation for environments that are generally random and static
## Inspiration

With the recent Corona Virus outbreak, we noticed a major issue in charitable donations of equipment/supplies ending up in the wrong hands or are lost in transit. How can donors know their support is really reaching those in need? At the same time, those in need would benefit from a way of customizing what they require, almost like a purchasing experience.

With these two needs in mind, we created Promise. A charity donation platform to ensure the right aid is provided to the right place.

## What it does

Promise has two components. First, a donation request view to submitting aid requests and confirm aids was received. Second, a donor world map view of where donation requests are coming from.

The request view allows aid workers, doctors, and responders to specificity the quantity/type of aid required (for our demo we've chosen quantity of syringes, medicine, and face masks as examples) after verifying their identity by taking a picture with their government IDs. We verify identities through Microsoft Azure's face verification service. Once a request is submitted, it and all previous requests will be visible in the donor world view.

The donor world view provides a Google Map overlay for potential donors to look at all current donation requests as pins. Donors can select these pins, see their details and make the choice to make a donation. Upon donating, donors are presented with a QR code that would be applied to the aid's packaging.

Once the aid has been received by the requesting individual(s), they would scan the QR code, confirm it has been received or notify the donor there's been an issue with the item/loss of items. The comments of the recipient are visible to the donor on the same pin.

## How we built it

Frontend: React  
Backend: Flask, Node  
DB: MySQL, Firebase Realtime DB  
Hosting: Firebase, Oracle Cloud  
Storage: Firebase  
API: Google Maps, Azure Face Detection, Azure Face Verification  
Design: Figma, Sketch

## Challenges we ran into

Some of the APIs we used had outdated documentation.
Finding a good of ensuring information flow (the correct request was referred to each time) for both the donor and recipient.

## Accomplishments that we're proud of

We utilized a good number of new technologies and created a solid project in the end which we believe has great potential for good.

We've built a platform that is design-led, and that we believe works well in practice, for both end-users and the overall experience.

## What we learned

Utilizing React states in a way that benefits a multi-page web app
Building facial recognition authentication with MS Azure

## What's next for Promise

Improve detail of information provided by a recipient on QR scan. Give donors a statistical view of how much aid is being received so both donors and recipients can better action going forward.

Add location-based package tracking similar to Amazon/Arrival by Shopify for transparency