Surdas

Inspiration

The idea for Suradas was sparked by real-life interactions with visually impaired individuals who face daily challenges in navigation, safety, and independence. While traditional aids like white canes and guide dogs help, they have limitations. Advanced assistive devices exist, but their high cost and limited availability make them inaccessible to many. We set out to create a smart, affordable, and inclusive wearable to bridge this gap.

What it does

Suradas is an AI-powered wearable designed to:

• Detect obstacles, edges, stairs, and uneven surfaces in real time.
• Recognize nearby people and objects.
• Identify currency denominations for financial independence.
• Provide voice command support for hands-free control.
• Enable live GPS tracking, SIM-based emergency alerts, and fall detection.
• Offer intuitive navigation through haptic and audio feedback.

How we built it

• Stage: Currently in Proof of Concept (POC) phase.
• Research: Conducted interviews with visually impaired individuals and NGOs to determine essential features.
• Hardware: Selected ARM-based processors, BLE chips, GPS modules, and AI sensors for cost-effective performance.
• Software: Used OpenCV, TensorFlow, and PyTorch for object detection; NLP for voice commands; BLE integration for smartwatch sync.
• Prototype Testing: Early trials to test detection accuracy, feedback patterns, and ease of use.

Challenges we ran into

• Running real-time AI on affordable hardware without performance drops.
• Adapting to varied lighting and environmental conditions.
• Balancing battery efficiency with high responsiveness.
• Designing an intuitive experience for first-time tech users.

Accomplishments that we're proud of

• Developing a functional POC prototype that integrates multiple assistive features into one device.
• Achieving low-latency AI detection on edge hardware.
• Receiving positive initial feedback from potential users and accessibility advocates.

What we learned

• How user feedback shapes product design more than technical assumptions.
• Best practices for AI optimization on low-power devices.
• The importance of regulatory and accessibility compliance early in the development process.

What's next for Suradas

• Refine the POC into a pilot-ready prototype with improved ergonomics and battery life.
• Conduct extended field trials with visually impaired users.
• Secure funding and partnerships for large-scale testing and manufacturing.
• Begin regulatory certification for assistive technology approval.
• Prepare for market launch in India, with global expansion in later phases.

Built With

• opencv
• python
• tensorflow