Developer Mesh: Editor’s Picks March 2018

Every month I pick out a few projects from Developer Mesh that I find interesting and share them with you. There is a diverse array of projects on the site, so narrowing it down to just a few can be difficult! I hope you’ll take a few minutes to find out why each of these projects caught my eye and then hop over to mesh to see what other projects interest you.

Using Drones and IoT for Warehouse Monitoring

Taking the growth and available facilities into account, Innovator Shriram KV has attempted to use quad copters to enhance the efficiency in monitoring warehouses with a cost-effective approach. A lot of inventory loss involves inefficient, manual monitoring techniques, so an affordable, accurate, and viable option would be to use a drone to fly inside a warehouse and track goods providing updates and eliminating the chance for lost inventory.

Recursive ML at the Edge: Case Study – Training a Bird Species Identifier

Using an existing image recognition model, Innovator Paul Langdon, built a secondary seed library to extend the classifier to make a more specific model to identify specific bird species. The methodology easily adapts to any sub-classifications scenario and provides automation for model training while collecting field data at the edge using Amazon’s* DeepLens machine learning platform along with Amazon’s* Greengrass and Sagemaker programs.

IoEuropa Game

Conflict erupts between Jupiter’s moons, Io and Europa, as trade agreements and closer orbits bring them together in ways that are volatile to their environments. You have to find clues to make your way through this adventure game that’ll have you questioning war and social economic standards. Innovator Mark Stumbris is seeking collaborators to help incorporate virtual reality and artificial intelligence into this educational, open source game.

Pachyderm: Data Versioning and Pipelining

Pachyderm’s open source core is designed to enable sustainable data science workflows via a language-agnostic system for data versioning with data pipelining. Innovator Daniel Whitenack’s project uses containers for analysis, distributed processing, and data provenance for machine learning and artificial intelligence pipelining and data management on Kubernetes. Essentially, what Github does in terms of collaboration and reproducibility, for code, Pachyderm does for your data.

Garbage Sorting and Separation

Waste is a huge problem the world over and ambassador Antony Kariuki is focusing on how to use technology to create an efficient garbage sorting and monitoring system. Using image processing, characteristic extraction, and machine learning to sort the garbage from the recyclables and then go on to sort the various plastics, glass, and metals into their bins. Once sorted, the system will also monitor the garbage level and alert when it’s full.

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If you want to know more about Developer Mesh or the Intel® Software Innovator Program, contact Wendy Boswell.

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