Inspiration
I was inspired by the increasing need for proactive health interventions in daily life, especially in environments where people spend prolonged periods sitting or in static positions, such as offices or public waiting areas. The goal was to create a solution that encourages physical activity in these settings in a fun and interactive way, using technology to engage and remind users to maintain an active lifestyle.
What it does
StretchStation is an AI-powered interactive kiosk that detects a person's presence and engages them in short, guided stretching sessions. It uses computer vision to identify when a person is within view and then prompts them with audio and visual cues to begin a stretching routine. The session is displayed through a high-quality video, ensuring the user correctly follows the stretching exercises, enhancing both physical and mental wellness.
How we built it
I built StretchStation using Python, integrating several technologies:
- OpenCV for real-time video capture and person detection.
- Deep learning models to accurately recognize human presence and movements.
- ElevenLabs AI voice creation for audio cues
- Pygame for handling audio playback of instructions and feedback.
- MoviePy for controlling video playback of stretching routines.
I designed the system to be intuitive, using visual bounding boxes to guide users and audio cues to provide clear instructions.
Challenges we ran into
One of the biggest challenges was ensuring accurate person detection in diverse lighting conditions and environments. Integrating audio and video in real-time while maintaining system responsiveness also posed significant technical challenges.
Accomplishments that we're proud of
I am particularly proud of creating a fully functional prototype that seamlessly integrates various technologies to deliver a smooth user experience. The ability to detect a person and initiate an interactive session effectively, without user input, demonstrates the practical application of AI and computer vision in everyday health management.
What I learned
Through this project, I gained deeper insights into the application of computer vision and AI in real-world scenarios. I learned about the complexities of deploying AI models in public settings, including the need for robustness and adaptability to different environments and user behaviors. We also improved our skills in multimedia integration and user interface design, ensuring that technology serves to enhance human health and well-being.
What's next for StretchStation
Looking ahead, we plan to refine the detection algorithms to handle more complex scenarios, including multiple users simultaneously. We also want to expand the video content to include a variety of stretching routines tailored to different needs and time durations. Another key area of development is incorporating user feedback mechanisms to adapt and personalize the experience further. Finally, we aim to explore partnerships with public health organizations and commercial entities to bring StretchStation to a broader audience.
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