Interaction Lab Study Website
Enpowering Cognitive Bevahioral Therapy Research with a Cloud-based, IoT-Connected Web Platform
Project Overview
The Interaction Lab Study Website is a research-focused web platform designed to guide users through structured CBT workflows while enabling seamless interaction with physical devices. Built using Next.js and deployed via AWS Amplify, the app integrates video collection, emotion tracking, secure user authentication, and IoT-based hardware communication, all within a cohesive and privacy-first experience.
Due to confidentiality requirements, the live site cannot be shared publicly - but the screenshots below demonstrate key UI and system workflows.
Technologies Used
Key Features
Interactive Therapy Interface
The platform features a sophisticated interface that guides participants through therapy sessions with smooth animations and intuitive interactions. The design ensures that users remain engaged while maintaining the professional atmosphere required for therapeutic interventions.
Secure Authentication with AWS Cognito
User identity and session management are handled entirely through AWS Cognito, ensuring robust security and seamless user experience.
Video Capture and storage
During parts of the session, users may record video reflections. These are securely stored in AWS S3 for later review and analysis by the researchers.
Survey Logic & User Flow
The app integrates structured pre- and post-surveys, with Likert scales, sliders, and multi-choice formats. These are conditionally rendered based on the user's flow state and stored in DynamoDB.
Real-Time IoT Device Integration
The platform communicates with a robot device via AWS IoT Core, enabling the system to send and receive messages in real time.
My Role and Responsibilities
As the lead developer for this project, I was responsible for architecting and implementing the entire web platform. This included:
• Designing and implementing the AWS infrastructure, including Cognito authentication, S3 storage, and IoT Core integration
• Developing the core application architecture using Next.js and TypeScript
• Creating responsive UI components and implementing smooth animations with Framer Motion
• Building secure data collection and storage systems for research data
Results & Takeaways
The project successfully achieved its goals and provided valuable insights:
• Successfully deployed a secure, scalable platform that handles sensitive research data
• Implemented real-time IoT communication that enhanced the research experience
• Created an intuitive interface that maintained participant engagement throughout sessions
• Established robust security measures that met university research compliance requirements
Confidentiality Note
Due to the sensitive nature of the research and participant data, this project is subject to strict confidentiality requirements. The live website and specific implementation details cannot be publicly shared. The screenshots and descriptions provided are carefully curated to demonstrate the technical aspects while maintaining participant privacy and research integrity.
Project Screenshots
