Inner Peas

Inspiration

In many parts of the world, the phenomenon known as “urban sprawl” has decimated native ecosystems and endangered many of the flora and fauna that reside there. Native plants, the foundation of our diverse ecosystems, have been threatened increasingly in recent years, further tipping these precariously balanced ecosystems into chaos and disaster. As an attempt to preserve the unparalleled diversity of our wildlife, we want to empower people to live a more effortlessly sustainable lifestyle. We envision a greener tomorrow.

What it does

We took a human-centered approach to address an intimidating sustainability issue. The cold statement “non-native plants are invading the ecosystem” won’t make people take action, as they might find it irrelevant or too broad to apply to their personal lives or actions. Instead, by providing users with an easy and straightforward way to find and plant native plants in gardens, we hope they will adopt a more sustainable and greener lifestyle, benefiting both themselves and the planet in the process.

How we built it

We first brainstormed in-person, initially throwing a bunch of ideas out to each other, researching existing solutions to those problems, and narrowing it down to a single topic we wanted to pursue. Some members then envisioned general app functionality and user scenarios and made a prototype UI using figma. Others worked on back-end, trying to read data from existing native plant databases using react.js and node.js. We then exported the figma prototype and added functionality using HTML and CSS.

Challenges we ran into

None of us had had experience with coding a website or an app beforehand, so we needed to figure out how to connect our design on Figma with our code and variable manipulation. We asked for help from a few of the mentors and realized that our vision was too ambitious for a short, day-long hackathon. Instead, we focused on presenting our ideas and vision in an appealing format, while still implementing some technical aspects that were more manageable challenges to complete in such a short time frame. We also struggled with gathering data in the back end. We tried both web scraping and pulling data from a plant API but were unsuccessful. Under the time restrictions, we decided to pivot and manually gathered a more limited data set.

Accomplishments that we're proud of

One accomplishment that we are very proud of is learning how to use Figma almost completely from scratch. Going into it with very little knowledge, we were able to create a visually appealing and functional prototype. Another accomplishment that we are proud of is learning javascript and figuring out how to use libraries like Cheerio and Axios. Before the hackathon, we had no experience with this, but after many online tutorials, we were able to figure out how to gather data that we could then use to support Inner Peas.

What we learned

Although we weren't able to implement webscraping into our project, we learned a lot about how it works, and were able to scrape from some other websites. We also learned React and some HTML to help merge the front and back-ends of our project. Although we did not get the opportunity to fully explore our options with React and HTML, we now have the knowledge of how to proceed if we were to continue developing this project. We learned how to use a search bar to access a sample API and narrow down search results based on what was put in.

What's next for Inner Peas

Inner Peas has many plans for the future. Firstly, we would like to connect it to a real native plant database (e.g. Audubon Native Plants) and a climate database based on the entered zip code. That way, people can get more customized results. Secondly, we wish to add features that we brainstormed initially but did not have the capacity to implement, such as an AR feature that allows user to scan their area and automatically identify space, sunlight, and shade. Another feature would be a garden planning feature, which would take in the area either through AR or manually inputting measurements and return a plan for what to plant in each plot based on sun requirements, companion plants, and amount of space needed.