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Sgether with AI

AI Supervisor Remote Study Platform

Not all children can go to the class room in person.
They tend to lose their motivation because of their isolated situation.

Our Sgether team was launched to solve this situation using a non-face-to-face study platform and AI supervisor technology.

😎 Expectation

Children can feel connected to each other and motivated even when they use our Sgether platform.

In addition, AI's learning supervision allows you to objectively grasp your own learning status.

📄 Abstract

There are students in developing countries who, for various reasons, have difficulty attending classes in person.
To ensure the quality of education and equal learning opportunities for these students, a remote education system platform is necessary.

However, despite efforts to provide remote education, the quality of education may suffer due to the lack of on-site monitoring and the inability to gauge students' level of focus.
So, to address this issue, we have developed AI CamStudy, which combines AI proctoring and video conference study sessions.

📄 UN SDG

enter image description here According to UN, there are large disparities between the income groups in primary school completion rates Also, the pandemic has led to school closures affecting 90% of students.

Quality Education & Reduce Inequality

target

Children who, due to geographical or environmental limitations, cannot receive a certain level of education.

problem

Due to the difficulty of conducting face-to-face classes, remote classes need to be conducted. However, there are challenges in monitoring students' level of focus

resolve

We have addressed this issue by introducing AI proctoring.

🛣 Architecture

📚 Project overview

👍 Scalability of the project

Beyond self-study proctoring, we will collaborate with other large-scale education platforms to provide learning content. As a result, more users will be attracted, and more efficient and effective learning will be achieved through our project's technology.

We are also deploying the service using AWS EC2 cloud service. Therefore, scaling up based on the size of users can be easily performed and expansion can be prepared by dynamically increasing servers according to demand.

⚙️Tech Stack

🚏 Server - APP(BE)

service version
NodeJS v16.x
EXPRESS v4.x
REDIS v3.0.x
MySQL 5.7.x

📱 FE - APP

service version
Android Studio v4.2
Figma web_service
webRTC open-source

💻 ML - embedded

service version
python v3.11.2
Yolov5 v5

👪 Team Information

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