The 3D Handyman shares an interesting technique to address the mask shortage in light of the COVID pandemic.

However, there are safety concerns you should take seriously. Highlights added.

I’m sharing this video here to inspire folks to use the tools and expertise at their disposal to fight this awful disease.

Your safety is no joke! Read all this information!

WARNING! The activated carbon layer of the MERV 16 filter used in this video appears to contain fiberglass!

Other home air filters may also contain Fiberglass! Do not use fiberglass based materials for breathing devices! One possible test is if you can melt the filter material into a plastic blob with a standard lighter it is likely a synthetic material. If the material can not be melted, there is a high likelihood that it is fiberglass. That said, it can be very difficult to determine what these filters are made of and some may be a small percentage fiberglass. Use extreme caution when making any type of breathing device! Emailing the manufacturer may be the only way to find out what the filter is made out of.

There are lots of materials that can be loaded into this and other 3D printed mask designs. According to “tests at Missouri University and University of Virginia, scientists found that vacuum bags removed between 60 percent and 87 percent of particles.” This article also mentions “A 600 thread count pillow case captured just 22 percent of particles when doubled, but four layers captured nearly 60 percent.” This may indicate that a double layer of a MERV 12 filter (or lesser rated filters) may have much better filtration performance than just a single layer. ALSO “The problem with air filters is that they potentially could shed small fibers that would be risky to inhale. So if you want to use a filter, you need to sandwich the filter between two layers of cotton fabric.” Good advice! https://www.nytimes.com/2020/04/05/well/live/coronavirus-homemade-mask-material-DIY-face-mask-ppe.html

It appears many 3D printed masks do not have enough filter surface area and negate the manufacturer filtration ratings and can actually lead to CO2 build up in the mask cavity and in your body. This particular design appears to have enough surface area to function without these issues. However, keep this in mind and if you choose to wear a device like this

REMOVE IT if you feel light headed, dizzy, headache, confusion, etc. (Carbon Dioxide Poisoning) and NEVER wear a mask while sleeping.

Time Index:

  • 0:00 – Intro and Basic Concept
  • 3:00 – Method and Materials
  • 8:38 – Design
  • 14:39 – 3D Print
  • 16:08 – Closer Look at the Design (Animation)
  • 17:07 – Finishing and Assembly
  • 20:27 – Testing and Review
  • 25:02 – Cost and Conclusions

Azure IoT Central, Microsoft’s IoT app platform, reduces the burden and costs associated with developing, managing and maintaining enterprise-grade IoT solutions.

With IoT Central you can provision an IoT application in 15 seconds, customize it in an hour and go to production the same day. Azure IoT recently announced a set of breakthrough features to help solution builders accelerate time-to-value. In this deep dive, Pamela Cortez and Ranga Vadlamudi will go into how to build with IoT Central with these latest features:

  • IoT Edge support, including management for edge devices and IoT Edge module deployments

Future deep dives will go through these areas in-depth:

  • 11 new industry-focused application templates to accelerate solution builders across retail, health care, government and energy
  • API support for extending IoT Central or integrating it with other solutions, including API support for device modeling, provisioning, lifecycle management, operations and data querying

Speakers

Deep Dives are hosted by Pamela Cortez from the Azure IoT Team.

Special guest

  • Ranga Vadlamudi

Resources

Frank and Andy talked about doing a Deep Dive show where they take a deep look into a particular data science technology, term, or methodology.  And now, they deliver!

In this very first Deep Dive, Frank and Andy discuss the differences between Data Science and Data Engineering, where they overlap, where they differ, and why so many C-level execs can’t seem to figure out the deltas.