SnoozeMonitor

SnoozeMonitor is your go-to app for managing and improving your sleep habits. With features like personalized sleep recommendations, sleep tracking, and insights into your sleep patterns.

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Inspiration

The theme of SnoozeMonitor centers on promoting relaxation and well-being. Through its calming colors, smooth transitions, and user-friendly design, the app aims to create a serene environment that encourages better sleep habits. It emphasizes the importance of restful sleep for overall health and happiness.

What it does

  • Data Analysis: Analyze sleep-related data including gender distribution, disease counts by gender, sleep duration distribution by gender, stress level distribution by gender, and BMI distribution.
  • Interactive Plots: Visualize data with interactive plots for better insights.
  • Prediction: Predict sleep-related issues based on user input data.
  • Precautionary Measures: Provide precautionary measures based on predicted sleep-related issues.

How we built it

Libraries used

  • Taipy 3.1.0 (an open-source Python library for easy, end-to-end application development) bash - Taipy.Gui - Navbar - Input fields (text/number/sliders) - Buttons - Column Layout - Event-Triggered Notifications - Visualization charts (Pie chart/Bar graphs/Histogram/Area chart/Box plots) - Images `
  • Tensorflow (DL framework to build models)
  • Scikit-learn (used to implement machine learning models and statistical modeling) -Google-generativeai
  • Plotly (Python graphing library makes interactive, publication-quality graphs)
  • Beautifulsoup4 (a library that makes it easy to scrape information from web pages)
  • Markdown

Hosted the app on Taipy Cloud, try out the live app at https://snooozemonitor.taipy.cloud/

Challenges we ran into

In designing the UI and maintaining the layout and functioning of the app during the time of development and deployment

Accomplishments that we're proud of

The Neural Network trained on the data achieved 90% of accuracy in predicting Sleep Disorder using the user's sleep data and Gemini is at its best to recommend the user about the precautionary measures that are to be taken to improve their sleep health.

What we learned

Learning a new framework always brings excitement. Taipy is a handy Python library for developing end-to-end applications and can withstand large amounts of data for processing and even handles huge traffic requests when hosted on the Taipy cloud.

What's next for SnoozeMonitor

SnoozeMonitor could enhance its capabilities by integrating advanced sleep-tracking algorithms, syncing with wearable devices for more accurate data, and implementing personalized recommendations based on machine learning analysis. Additionally, features like sleep environment monitoring, community support, and medication tracking could further improve the app's effectiveness in promoting better sleep habits and overall well-being.

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