## Inspiration

This project was inspired by my love of walking. We all need more outdoor time, but people often feel like walking is pointless unless they have somewhere to go. I have fond memories of spending hours walking around just to play Pokemon Go, so I wanted to create something that would give people a reason to go somewhere new. I envision friends and family sending mystery locations to their loved ones with a secret message, picture, or video that will be revealed when they arrive. You could send them to a historical landmark, a beautiful park, or just like a neat rock you saw somewhere. The possibilities are endless!

## What it does

You want to go out for a walk, but where to? SparkWalk offers users their choice of exciting "mystery walks". Given a secret location, the app tells you which direction to go and roughly how long it will take. When you get close to your destination, the app welcomes you with a message. For now, SparkWalk has just a few preset messages and locations, but the ability for users to add their own and share them with others is coming soon.

## How we built it

SparkWalk was created using Expo for React Native. The map and location functionalities were implemented using the react-native-maps, expo-location, and geolib libraries.

## Challenges we ran into

Styling components for different devices is always tricky! Unfortunately, I didn't have time to ensure the styling works on every device, but it works well on at least one iOS and one Android device that I tested it on.

## Accomplishments that we're proud of

This is my first time using geolocation and integrating a map, so I'm proud that I was able to make it work.

## What we learned

I've learned a lot more about how to work with React Native, especially using state and effect hooks.

## What's next for SparkWalk

Next, I plan to add user authentication and the ability to add friends and send locations to each other. Users will be able to store messages for their friends that are tied to specific locations. I'll add a backend server and a database to host saved locations and messages. I also want to add reward cards for visiting locations that can be saved to the user's profile and reviewed later. Eventually, I'll publish the app so anyone can use it!
## Inspiration

While video-calling his grandmother, Tianyun was captivated by her nostalgic tales from her youth in China. It struck him how many of these cherished stories, rich in culture and emotion, remain untold or fade away as time progresses due to barriers like time constraints, lack of documentation, and the predominance of oral traditions.

For many people, however, it can be challenging to find time to hear stories from their elders. Along with limited documentation, and accessibility issues, many of these stories are getting lost as time passes.

**We believe these stories are *valuable* and *deserve* to be heard.** That’s why we created a tool that provides people with a dedicated team to help preserve these stories and legacies.

## What it does

Forget typing. Embrace voice. Our platform boasts a state-of-the-art Speech-To-Text interface. Leveraging cutting-edge LLM models combined with robust cloud infrastructures, we ensure swift and precise transcription. Whether your narration follows a structured storyline or meanders like a river, our bot Ivee skillfully crafts it into a beautiful, funny, or dramatic memoir.

## How we built it

Our initial step was an in-depth two-hour user experience research session. After crafting user personas, we identified our target audience: those who yearn to be acknowledged and remembered.

The next phase involved rapid setup and library installations. The team then split: the backend engineer dived into fine-tuning custom language models and optimizing database frameworks, the frontend designer focused on user authentication, navigation, and overall app structure, and the design team commenced the meticulous work of wireframing and conceptualization.

After an intense 35-hour development sprint, Ivee came to life. The designers brought to life a theme of nature into the application, symbolizing each story as a leaf, a life's collective memories as trees, and cultural groves of forests. The frontend squad meticulously sculpted an immersive onboarding journey, integrating seamless interactions with the backend, and spotlighting the TTS and STT features. Meanwhile, the backend experts integrated technologies from our esteemed sponsors: Hume.ai, Intel Developer Cloud, and Zilliz Vector Database.

Our initial segregation into Frontend, Design, Marketing, and Backend teams soon blurred as we realized the essence of collaboration. Every decision, every tweak was a collective effort, echoing the voice of the entire team.

## Challenges we ran into

Our foremost challenge was crafting an interface that exuded warmth, empathy, and familiarity, yet was technologically advanced. Through interactions with our relatives, we discovered overall negative sentiment toward AI, often stemming from dystopian portrayals in movies.

## Accomplishments that we're proud of

Our eureka moment was when we successfully demystified AI for our primary users. By employing intuitive metaphors and a user-centric design, we transformed AI from a daunting entity to an amiable ally. The intricate detailing in our design, the custom assets & themes, solving the challenges of optimizing 8 different APIs, and designing an intuitive & accessible onboarding experience are all highlights of our creativity.

## What we learned

Our journey underscored the true value of user-centric design. Conventional design principles had to be recalibrated to resonate with our unique user base. We created an AI tool to empower humanity, to help inspire, share, and preserve stories, not just write them. It was a profound lesson in accessibility and the art of placing users at the heart of every design choice.

## What's next for Ivee

The goal for Ivee was always to preserve important memories and moments in people's lives. Below are some really exciting features that our team would love to implement:

* Reinforcement Learning on responses to fit your narration style
* Rust to make everything faster
* **Multimodal** storytelling. We want to include clips of the most emotion-fueled clips, on top of the stylized and colour-coded text, we want to revolutionize the way we interact with stories.
* Custom handwriting for memoirs
* Use your voice and read your story in your voice using custom voices

In the future, we hope to implement additional features like photos and videos, as well as sharing features to help families and communities grow forests together.
## Inspiration

Typically plants in nature have little control over their own fate; organism growth is constrained by physical and environmental factors. Based on ambient sensor data as well as plant-specific information, we can better understand the state of the organism and adjust its spatial position and water level.

## Implementation

#### Overview

The system consists of multiple parts, including:

* Arduino Nano, which receives and interprets sensor data
* Motor and wheel assembly, to move the plant to a suitable light source
* Photodiodes to measure ambient light levels at four equidistant points around the plant
* Moisture sensor to measure soil moisture levels, determining when the plant should receive water
* Ultrasonic sensors to determine the spatial position of the plant as well as to avoid collisions with stationary or incoming objects
* Wireless receiver and transmitter to send and receive plant sensor data for data analytics and analysis (not internet connected, although we have the option of doing so in the future)
* A React-based dashboard which can receive data from multiple plants and run data analytics to better understand current plant state at a glance as well as past trends
* Motion-sensitive RGB LED

#### Circuit Design

We took care to lay out the design of the circuit to accommodate the sensors we wanted, although what we created is a rough prototype. Photos are available below.

## What We Learned

As students primarily focused on studying software engineering, this project helped us push our boundaries and get a better understanding of both hardware and low-level software. We learned about circuit design and designing systems for various types of sensors.

## Challenges Faced

We weren't able to fit everything onto one single breadboard because we were lacking in some hardware resources required to make the circuit design more compact and efficient.

## Future

We're excited by a future where plants can integrate themselves more usefully into our man-made environment, and wish to improve the capabilities of the system, including using plants natively as sensors themselves.