STEM-In-Action Fall Follow Up: Team Artemis
We're back for STEM-In-Action Grant Fall Follow Ups, where we check in with our 2023-2024 STEM-In-Action Grant winners to see what they've accomplished since NJ&EE! If you're new to the STEM-In-Action Grant program, the U.S. Army Educational Outreach Program (AEOP) awards five STEM-In-Action Grants of up to $5,000 to eCYBERMISSION Regional Finalist teams wishing to further develop and implement their projects in their communities. First up, we're checking in with Team Artemis.
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Hello everyone! We are Team Artemis, a team of ninth graders based in Ashburn, Virginia. Our team consists of high schoolers Aarnav Trivedi, Praneel Mukherjee, Nihal Jupalli and Abhinav Yarlagadda. As recipients of the STEM-In-Action Grant, we are delighted to have been given the opportunity to make a meaningful impact on our community through the support of AEOP, and would like to inform everyone about our project. We first learned of the eCYBERMISSION program by a shared middle school teacher, and it has provided our team the resources necessary to solve a problem in our community. Through our research, we discovered that there is a Braille literacy crisis in the US, with only 10% of the over 1.2 million legally blind people being able to read Braille. Furthermore, we also found that 77% of blind individuals that do not know Braille face unemployment. Although Braille plays a large role in the availability of opportunities such as formal education, jobs or community involvement for blind people, a steady decline in the amount of Braille teachers significantly limits the Braille learning experience for youth.
To solve this issue, we created the Artemis Braille Glasses, an artificial intelligence powered headset that allows users to interactively learn from the Braille in their environment. A Braille learner using the headset is able to translate Braille in their nearby vicinity and talk to a personalized AI Braille Teacher, “Artemis”, in real time. By talking to Artemis, the user can perform operations such as translating Braille from anywhere, whether that be the library, school, or at the gym. It’s also able to turn any piece of Braille into a practice problem, users can scan the Braille in front of them and create tailored multiple-choice or free response questions regarding the piece of Braille in front of them. We are actively working to improve the CAD model, in addition to improving the scalability/efficiency of the computer algorithms to take advantage of recent vision/language foundation.
The grant funds have allowed us to purchase 3D printing equipment to develop the exterior of our headset, develop the hardware, and create software infrastructure. The main engineering developments have been aimed towards transitioning to more streamlined hardware. One step we took towards this was replacing the Raspberry Pi with a lighter and more power-efficient Pi Zero 2 W. We are putting the components into one module so that the only visible component will be the camera mounted on the glasses. In software development, our primary method of translating Braille images was with the use of a convolutional neural network (CNN), which is a type of predictive model that can be trained to analyze images. However, to prevent limitations due to open source data constraints, we have instead decided to use a Vision Language Model (VLM) in our computer vision algorithm, allowing for Braille translation with powerful pretrained models. Furthermore, our team has partnered with a Stanford based non-profit organization, OpenNLP Labs, which will provide us processing power to train the powerful computer vision algorithms our program uses as well as expert guidance on the development of internal AI models.
We are currently in communications with local blind facilities in the Virginia area, in an effort to prepare our prototype for testing and distribution, allowing blind learners to benefit from our work. Thank you for your support as we embark on a journey towards Braille literacy.
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