AWS Machine Learning Blog

Announcing the winners of the AWS DeepLens Challenge

April 2023 Update: Starting January 31, 2024, you will no longer be able to access AWS DeepLens through the AWS management console, manage DeepLens devices, or access any projects you have created. To learn more, refer to these frequently asked questions about AWS DeepLens end of life.

At AWS re:Invent 2017 we announced the AWS DeepLens Challenge in conjunction with Intel. The AWS DeepLens Challenge gave attendees of the re:Invent DeepLens workshops an opportunity to put their skills to the test by building a machine learning (ML) project using their AWS DeepLens. The mission was to get creative with computer vision and deep learning, and learn in the process! All of the contestants put forward amazing entries. We were blown away by the incredible uses they found for AWS DeepLens.

The judging concluded this week, and we’re excited to announce the winners.

May I have the envelope please? (cue the drumroll)

The winners of the AWS DeepLens Challenge are:

  • First Place: “ReadToMe” by Alex Schultz
  • Second Place: “Dee” by Matthew Clark
  • Third Place: “SafeHaven” by Nathan Stone and Peter McLean

Congratulations to the winners and all of the entrants for their incredible innovations!

It was a closely run race with 23 eligible submissions competing for the top spots. These projects cover a range of categories including safety, education, security, health and wellness, and pets and animals. Quite a few friends and family members were recruited by the authors for the video demos. (A round of applause to the folks in the demos—the unsung heroes.)

To celebrate all of this great work we have created an AWS DeepLens Community Projects webpage to house the complete collection of projects contributed by the community of developers and to provide inspiration. The content for the projects comes from the developers themselves. Each project includes a short video demonstrating the innovation. In most cases the project also includes a detailed description and a link to the project GitHub repo or Bitbucket, so that you can download and experiment with the model yourself.

Over the coming weeks we will dive into each of the winning projects and walk through the details so you can get a view into what made these projects distinctive. Plus, you’ll be able to learn more about the technologies used to implement the solutions.

Here are some pictures from the winning projects:

ReadToMe: In this case reading Green Eggs and Ham, by Dr. Seuss. “ReadToMe” is a deep learning enabled application that is able to read books to kids.

Dee: “Dee” is an entertainer and an educator that is a fun AWS DeepLens interactive device for children. The device asks children to answer questions by showing Dee the right things.

SafeHaven: “SafeHaven” uses Alexa and AWS DeepLens to bring peace of mind to vulnerable people. Their supportive families receive doorstep photo alerts via SMS.

You can review more details on the winning projects, as well as, all of the submissions at: AWS DeepLens Community Projects. If you are curious on the details of DeepLens Challenge contest including resources, rules, prizes, and judges, you can review the original challenge website:

Hopefully, these projects have inspired you to want to learn more about AWS DeepLens. For more information, take a look at the AWS DeepLens Website or browse AWS DeepLens posts on the AWS Machine Learning blog.

About the Author

Sally Revell is a Senior Product Marketing Manager for AWS DeepLens. She loves to work on innovative products that have the potential to impact people’s lives in a positive way. In her spare time, she loves to do yoga, horseback riding and being outdoors in the beauty of the Pacific Northwest.