Leaf serves as the 21st-century beacon that guides the world and welcomes them. We are a young group of college students that have seen first handly the harsh circumstances that many fellow New Yorkers are forced to live in.
-> The number of New Yorkers who struggle to put food on the table is larger than the whole population of SF, CA
-> 40% of New York City households are unable to cover for food, shelter or childcare.
Roughly 4,600 young people below the age of 25 are spending their nights on the streets or a shelter. Many times they are unable to eat. In addition to being homeless, they have to worry about having the essential to live whether that is a hot meal or a warm jacket.
Besides empowering our community, Leaf is also focused on helping save our Earth. 72 billion pounds of food are wasted every year, from that number a drastic 52 billion are wasted in grocery stores and restaurants. Shockingly enough 18% of the entire percentage comes from NYS. It is not only food but items such as clothing, which by itself makes 200 million pounds of trash every year IN NEW YORK STATE!
The recent events of COVID-19 really impacted the way our team thought about this project. This project is not only aimed at the underrepresented communities but instead to anyone in dire need of support. That is why we do not categorize profiles, you can donate or seek help at any time. We are aware of the conditions of our elderly community during this time of crisis and our app is here to help them!
Our goal can only be accomplished with the power of a united community, together we can bring light to people!
Disclaimer: all the data provided here are from valid external sources
What it does
- Notifies nearby users of donations via cloud-based sms text messages
- Leaf Map shows nearby public centers (shelters, food centers, youth centers), and nearby donation posts
- Donors can choose to donate anything, clothes,food, miscellaneous
Leaf serves as a beacon through SMS text messages and as a hub with the map that allows anyone to view where Donations are located.
- NYC Open Data
- Google Cloud
- Github Pages
How We Built It
- Developed login/register process and stored encrypted information in the database
- Created endpoints to efficiently connect to API's
- Hosted the front-end in github pages using react-gh-pages
- Hosted the back-end in Heroku and used MongoDB
- Used Google Cloud for the Leaf Map and developed customized Markers
- Markers pinpoint the user's live location and centers obtained from NYC Open Data datasets
- Each donation triggers OpenCage geolocation to find users within a 5 mile radius and then send SMS
- Used Twilio for the SMS service
- Developed a process to transform any address to latitude&longitude, even with just the zip code
- Used Figma to create a quick UI interface
- Used Git as version control system
Challenges We Ran Into
- Calculating the mile radius distance between 1:many coordinates
- Automatically sending SMS based on location
- Setting marker icons but received help from mentors
- Displaying InfoWindow on Leaf Map markers
- Posting using fetch but after some help from the mentors we were able to identify the issue.
Accomplishments that I'm proud of
Firstly, we are all happy to have met each other, we are a group made out of 2 seniors and 2 juniors, from BMCC, Queens College and Brooklyn College.
Collaboratively we are proud of tackling a real issue and successfully delivering a working prototype.
Individually, we are proud of automating SMS, getting a correct mile radius, and successfully Routering the app allowing us to navigate through the app flawlessly.
What's next for Leaf
Due to NYC being in "PAUSE" we are excited to keep working on this project and develop it to a point where we can deliver it to people that may need it during this crucial time.
What we want to accomplish is:
- Create an endorsement system to convince Restaurants to participate more often
- Fix filter bug within the Leaf Map
- Provide more assistive services
- Add voice control
- Dive deeper with CSS and make it look more user friendly