Digital device users, including students and professionals, experience a decrease in blink rate during screen time, leading to Computer Vision Syndrome (CVS) symptoms such as eye discomfort and dryness. Despite recommended interventions like regular breaks and ergonomic adjustments, CVS remains prevalent. Concurrently, poor posture from prolonged device use contributes to musculoskeletal issues. Addressing these concerns, WeCare aims to develop a smart system capable of predicting CVS through real-time eye data collection. By analyzing blink rates and posture, our solution seeks to provide timely interventions, including posture reminders and blink prompts, to mitigate CVS risk factors and promote ocular and musculoskeletal health.
Our hackathon journey introduced us to the complexities of Electron.js, challenging us to quickly grasp its fundamentals while developing a functional interface. Debugging was meticulous work, ensuring seamless UI integration. Crafting APIs demanded deep understanding and efficient design, while setting up the database required structured schema creation within a tight timeframe.
It also involved navigating the unfamiliar terrain of Figma for UI design, adding another layer of challenge as we learned to translate technical processes into an intuitive user experience.
Accurate upper-body pose estimation posed a significant challenge, as existing models were tailored for full-body recognition. Adapting these models required extensive testing and understanding of machine learning principles.
Team coordination was crucial amidst learning new tech and dividing tasks. Time management was essential to meet the deadline, necessitating tough decisions on feature scope. Designing an intuitive user interface for our innovative project was challenging, requiring iterative design and testing.
Despite these hurdles, the experience enhanced our skills and teamwork, resulting in a prototype we're proud of. It was a journey of resilience, adaptability, and innovation.
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