Our project, iSee, is inspired by a real-life experience of a teammate's cousin who had a damaged cornea from an accident and required an eye transplant. We aim to improve the current transplant system by incorporating monitoring elements and a smart classification system to prioritize patients in need of transplants.
What it does
iSee will be built into modern organ transplant ice boxes and use sensors such as temperature and humidity to update ambulance drivers or passengers on the vital signs of the organ. Additionally, we will use a machine learning algorithm to analyze thousands of rows of data from potential donors and recipients to create a list of the 10 most urgent patients based on factors such as time until the organ expires and distance between patients and hospitals.
How we built it
We built iSee using a Raspberry Pi sensor kit and a 3.5-inch touch screen for easy interaction with the system. However, we faced challenges in the hardware aspect, particularly with connecting the Raspberry Pi to our computer and networking issues.
Challenges we ran into
The main challenges we ran into were in the hardware area. Our first error was in the connection to the raspberry pi we ran into many network-related issues where our raspberry pi refused to connect to our computer through SSH due to network rules. Next when we were connecting our sensors to the thingspeak IOT bridge system to display our temperatures on a website to make it easier for doctors to access the data on the organ even if not in the ambulance or organ transport vehicle.
Accomplishments that we're proud of
We are proud of being able to work out differences in ideas of how the final product should be and the features it should have and being able to build a working product on our first Hackathon.
What we learned
We have learned a lot more on how to operate a linux terminal as a majority of the SSH process and file management was done through the terminal. We were also able to greatly develop our skills in integrating hardware and software elements by incorporating ML with a raspberry pi.
What's next for iSee
In the future, we plan to add GPS functionality to iSee so that it can provide directions to the recipient's hospital and also control the temperature of the organ using a smart plug-run mini cooling system.
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