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Having a standing deck won’t have any health benefits unless it is used properly. I learned it hard way. First and foremost, I have had no idea if I use a standing position enough to justify the investment, so I decided to put IoT concepts to a test and build personal standing ‘motivator’ and ‘reporter’ to understand my working patterns and motivate myself using the standing position of the desk more often. My goal was to have it done in one weekend, with running costs minimized.

I was able to assemble the solution using AzureSphere Seeed’s MT3620 Development board and few Azure SaaS Applications in just a few days. I’ve selected AzureSphere for its ultra-security capabilities and ease of integration into the Azure ecosystem. Additionally, I used Azure Stream Analytics and ML algorithms to sanitize and aggregate sensor data in real-time. I’ve created Azure Logic app to create “motivator” logic by monitoring my work patterns in real-time and sending SMS messages. I used Power BI to analyze my daily usage of the standing desk over time.

High level data flow:

After running my App for a few weeks now, I was able to get a complete picture of my working patterns and make the necessary adjustments. I’ll continue to improve these metrics as I use the application on a daily basis.

This was a truly great experiment, not only I was able to develop my solution in just under two days, I really enjoyed developing Azure Sphere. I was able to develop the entire solution using VS Code, from developing C applications to integrating with Azure Stream Analytics – I finally see a platform that has the potential to take IoT to the next level even in low-budget scenarios.

Sample Code: https://github.com/brodbor/azure-sphere-standing-desk-analytics