TECH Signal 311
Graphing sleep schedule through timestamped online activity
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This approach to tracking sleep patterns leverages existing online activity data instead of relying on wearable technology. It provides an alternative method for individuals who cannot use conventional tracking devices due to sensory issues. The method may inspire other engineers to think creatively about data collection and analysis.
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The individual uses timestamped data from Discord, Twitter, and other platforms to track sleep patterns.
Deno and TypeScript are utilized for scripting the data extraction and visualization process.
This method provides an innovative solution for those unable to use traditional sleep tracking devices.
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The event highlights a unique method of sleep tracking where an individual collects timestamps from various online activities instead of using a smartwatch. This method is particularly useful for people who have sensory sensitivities and cannot wear devices on their wrists.
Using Deno for scripting allows for a lightweight approach without extensive setup, which can be advantageous for quickly developing throwaway scripts. The use of TypeScript enhances type safety during the data processing.
The extraction process involves reading zip files containing data from platforms like Discord and Twitter, showcasing a technical understanding of how to manipulate and parse JSON data for analysis. The challenge of working with different data formats, especially when exporting from various services, adds complexity to the project.
This approach stops being effective if the user has limited online activity or if the data export formats change significantly. Furthermore, reliance on third-party platforms for data access may result in challenges regarding data availability and privacy.
The project demonstrates the potential for engineers to creatively combine existing digital footprints to derive personal insights, encouraging innovative thinking in data utilization for personal health tracking.
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