GoBaby

Inspiration

When tasked to create an application that improves the user-experience in regards to driving, we decided to focus on the most important aspect - Safety. On average, 40 babies die each year from heat-stroke after being left in vehicles due to a lack of awareness by the parents. According to Dr. Diamond, a neuroscientist at the University of South Florida, the act of driving "outcompetes and suppresses" our conscious memory system. In other words, driving causes us to forget. Given this problem at hand, we felt motivated to build an application that realigns the drivers focus to what matters - getting their baby from point A to point B safely.

What it does

Our web app's mission is simple. Remind the driver of their baby's wellbeing during the duration of the journey and at its end. Upon starting the vehicle, an in-cabin camera capture an image and detect if a baby is on-board. From this point on, it will maintain a safe rear cabin temperature for the baby's comfort by adjusting accordingly. This prevents heat exhaustion during blistering summer months, and hypothermia during trips in the cold winter. It's not an easy feat putting a baby to sleep, and being able to know if your child has woken up or remains sleeping adds piece of mind. After detecting the baby is asleep, the vehicle will remind the driver to exercise greater caution on roads, while also activating blind spot and lane assist monitoring. In addition, it will play white noise to speakers at the rear to prevent the baby from awaking due to the many outside distractions. Arguably the most important feature, a way to detect and alert those nearby of a baby left unattended. This is done by detecting if a driver not present while a baby is. If left unattended for more than a minute, the car's alarm will sound.

How we built it

When building GoBaby, our team utilized Python, Flutter, Flask, and Hugging Face machine learning models. In the prototyping phase, we used Figma to display a sample of what the driver may see when our application is used in the real world.

Challenges we ran into

Given that is was most of our's first hackathon, there was a lot of obstacles we ran into. Each of us had to learn basic machine learning concepts and the ways it can be implemented into the user interface. We also had trouble when it came to time management. Often times time and energy was placed into efforts that didn't come to fruition or were scrapped after completion. For the next hackathon, this can be avoided by better planning in the initial stages of the project. Second, we struggled with the implementation of Flask to combine our frontend and backend. Better understanding and prior use of Flask would have made the process easier. Despite many challenges that loomed above us as we worked, we pushed through and created a finished product.

Accomplishments that we're proud of

This was all of ours first time putting together a project on this scale! As Freshman, we came into this not knowing much and unsure of what to expect, however; came out accomplishing much more than we expected. From implementing tech stacks we didn't know of prior to this hackathon, to understanding and using machine learning concepts for the first time, we now feel ready to create bigger things in the future.

What we learned

We learnt that despite your level of experience, having a team that can work together and that is willing to learn, a lot is possible in a short amount of time! We came out having a greater understanding how different technologies communicate and work with each other. Furthermore, we learnt first-hand how companies can utilize ever-changing and improving technologies to benefit user-experience.

What's next for GoBaby

In regards to whats next for GoBaby, we'd hope to keep on improving it. With actual real-world implementation, we believe this will benefit parents and allow for a safer experience. Far too many children have been victim to a tragedy that can be prevented with the help of this software. We hope to add improvements in regards to accurately predicting data, finalizing the front-end, as well as testing how it works in the real-world!