ATechM

Our inclusive ATM system uses facial, finger, and head gestures detection, plus voice control for users with disabilities. It also boosts security by identifying criminals through facial recognition.

Inspiration

The inspiration behind ATechM comes from our desire to make banking services more accessible, particularly for individuals with physical disabilities. Recognizing the lack of inclusivity in current ATM designs, we aimed to create a system that not only breaks down barriers for people with mobility issues but also enhances security for all users.

What it does

ATechM is a next-generation ATM system that uses advanced technology to deliver a seamless, touch-free, and secure experience. Key features include:

• Facial recognition for secure logins
• Finger movement detection using MediaPipe for touch-free navigation
• Head tracking to allow users to interact without touching the screen
• Voice command capabilities for hands-free operation
• Luxand integration to ensure only real faces are detected, preventing identity spoofing with photos
• Cross-referencing faces against criminal databases stored in MongoDB to deny access to flagged individuals

How we built it

We built ATechM using a combination of powerful tools and frameworks:

• Next.js for a fast, scalable web-based infrastructure
• MediaPipe for real-time finger and face tracking, and criminal detection
• Luxand for ensuring real-face detection and preventing identity spoofing
• MongoDB to store criminal face data and user account information in a highly scalable and secure database

These technologies were integrated into a cohesive, responsive system that prioritizes both user accessibility and security.

Challenges we ran into

We encountered several challenges along the way:

1. Ensuring the accuracy of facial recognition and preventing spoofing using Luxand required extensive testing.
2. Seamlessly integrating MediaPipe with Next.js to deliver real-time performance was technically demanding.
3. Managing and querying a large dataset of criminal faces in MongoDB while maintaining quick response times posed its own challenges.

Accomplishments that we're proud of

We’re proud of several key accomplishments:

• Building an inclusive system that empowers users with disabilities.
• Successfully integrating MediaPipe for finger tracking and Luxand for face authentication.
• Implementing a secure, efficient criminal detection feature that leverages MongoDB to enhance user safety at ATMs.

What we learned

Developing ATechM provided us with valuable lessons:

• Balancing user experience and security is crucial in creating inclusive technology.
• We learned how to integrate complex systems like MediaPipe, Luxand, and MongoDB within a web-based framework like Next.js.
• It’s essential to design solutions that are inclusive without compromising on security or efficiency.

What's next for ATechM

We have several exciting plans for the future of ATechM:

• Expanding voice recognition to support multilingual users.
• Collaborating with security agencies to refine and enhance our criminal detection algorithms.
• Scaling ATechM to become the global standard for ATM systems, ensuring secure and inclusive banking for everyone.