Privacy Protection Algorithm for AI Applications

Through continuous research and sound development practices, we aim to implement a lightweight, privacy-preserving algorithm that protects data in AI applications in IoT-cloud environments against emerging security threats. AI and IoT are transforming industries by making devices smarter, more connected, and efficient, but the increased connectivity creates security challenges. IoT devices often lack the resources for traditional security measures. Therefore, this creates the need for lightweight solutions that protect data without compromising performance.

Gaming Lower-Code Functionality

To empower aspiring game designers with an intuitive, flexible tool that streamlines the creation of immersive, procedurally generated room environments—unlocking creativity through automation and smart customization. Designed for use in the client’s college-level Godot course, this tool will help beginners quickly get hands-on experience with game development.

ClassifAI

ClassifAI is an online video/audio analysis platform to assist educators in understanding how their interactions with students impact real learning. It provides quantifiable metrics related to teacher-student interaction, such as talking time, difficulty of questions asked by a professor, and lecture summaries. These tools can be used by lecturers to review their lectures and improve the classroom experience for their students.

EurekaLabs

VISION Create an intuitive, robust, and scalable website that facilitates the access and management of educational labs while offering an admin-friendly interface for content creation and maintenance. This website should allow professors to create projects for students to better their computer science skills and allow students to search for labs that suit their needs for […]

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