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In order to check out its technical feasibility to meet the Technical Requirement of the Project, Samsung Electronics has been incubating the internal project over a year. Since the Home Edge Project has been officially launched in January 2019, Samsung will contribute the seed code by the end of 1st half in 2019. Including this seed code publication, the Home Edge Project has established a plan to publish two major code releases in 2019. As with any open source projects, features that will be planned to the next major releases are based on priority and available developer resource bandwidth that will be transparently decided and directed by the Home Edge Project developer community in an open source manner "The more you contribute, the more you will get from the community". Therefore, you are always welcome to suggest, share, and revise any idea and code contributions to the Home Edge Project.


What you can expect from Home Edge? Timeline perspective

The below is an illustration for those who are interested in Home Edge project in LF Edge from our timeline perspective. 

We are open to collaborate with other open source projects as well as standard development organizations (SDOs) in upstream and downstream manners. When we are ready to fully construct the whole platform that satisfies our mission statement, it might be able to provide a meaningful flow as represented in the below figure, incorporating with cloud synchronization, machine learning framework, message protocol extensions, data analytics, and any other valuable aspects together. 

How could you play with this for your interesting use cases? Below is just an example for controlling of your HVAC system at home based on the number of people detected.

Alpha (June, 2019)

Edge orchestration : Edge device/service discovery and remote service execution among edge devices.

Baobab (October, 2019)

Orchestration on NAT environment( for home ), Custom edge device selection for service execution, Secure messaging 

Coconut (Target : Oct, 2020)

D-release (Target : Oct, 2021)

To be discussed. ( maybe Machine learning with cloud, or distributed parallel machine learning )

  • Wider Protocol Support
  • Machine Learning Module possibly
  • Github : to be updated
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