Difference between revisions of "BeagleBoard/GSoC/2020 Projects/Media IP Streaming"
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===Description=== | ===Description=== | ||
− | The BeagleBone AI is equipped with a high amount of processing power | + | The BeagleBone AI is equipped with a high amount of processing power due to the Dual Core ARM Cortex-A15 chip as a main computing unit and accompanying co-processors. |
− | A previous GSoC project ported a sound card driver from the BeagleBone Green/Black to the BeagleBoard-X15 (https://summerofcode.withgoogle.com/archive/2016/projects/5351212496977920/). This port will now be ported to the BegleBone AI. With the | + | This makes the AI a perfect fit for highly demanding applications regarding CPU consumption, like audio applications which have extremely strong realtime constraints. |
+ | Professional audio/video studios have to guarantee for small latencies when transmitting media signals between different devices and different media channels in a transmitted stream need to be synchronized. | ||
+ | Latency and Snychronicity is extremely important when transmitting e.g. a video channel together with the accompanying audio channel. | ||
+ | Those two channels have to be transmitted in a manner, that lip synchronicity can be guaranteed because humans are extremely sensitive to voice offset to accompanying video signals. | ||
+ | |||
+ | To bring media ip streaming capabilities to the Beaglebone AI, the following steps are planned: | ||
+ | A previous GSoC project ported a sound card driver from the BeagleBone Green/Black to the BeagleBoard-X15 (https://summerofcode.withgoogle.com/archive/2016/projects/5351212496977920/). | ||
+ | This port will now be ported to the BegleBone AI. With the sound card driver successfully ported, the next step would be to port the AVB protocol driver stack from [https://elinux.org/BeagleBoard/GSoC/BeagleBoneAVB Beagle Bone AVB] enabling media streaming over the network. | ||
+ | This would allow to use the Beaglebone AI as a media streaming device in professional audio/media applications and bring audio stream synchronisation features to the Beaglebone AI. | ||
+ | Thus allowing for tight synchronization between different audio and video streams which are transmitted over the network. | ||
===Timeline=== | ===Timeline=== |
Revision as of 02:45, 25 March 2020
Contents
ProposalTemplate
{{#ev:youtube|Jl3sUq2WwcY||right|BeagleLogic}}
A short summary of the idea will go here.
Student: [1]
Mentors: [2]
Code: [N/A]
Wiki: http://elinux.org/BeagleBoard/GSoC/MediaIpStreaming
GSoC: [N/A]
Status
This project is currently just a proposal.
Proposal
All requirements have been fullfilled, the Pull Request can be found here #139
About you
IRC: nwan
Github: NiklasWan
School: Kiel University of Applied Sciences
Country: Germany
Primary languages: German, English
Typical work hours: 8AM-5PM CET
Previous GSoC participation: I want to participate at GSoC because I want to gather experience in working within an open source community and try to apply theoretical knowledge into the practical domain. Also I hope to learn new awesome things. This would be my first time participating in GSoC.
About your project
Project name: Media Ip Streaming
Description
The BeagleBone AI is equipped with a high amount of processing power due to the Dual Core ARM Cortex-A15 chip as a main computing unit and accompanying co-processors. This makes the AI a perfect fit for highly demanding applications regarding CPU consumption, like audio applications which have extremely strong realtime constraints. Professional audio/video studios have to guarantee for small latencies when transmitting media signals between different devices and different media channels in a transmitted stream need to be synchronized. Latency and Snychronicity is extremely important when transmitting e.g. a video channel together with the accompanying audio channel. Those two channels have to be transmitted in a manner, that lip synchronicity can be guaranteed because humans are extremely sensitive to voice offset to accompanying video signals.
To bring media ip streaming capabilities to the Beaglebone AI, the following steps are planned: A previous GSoC project ported a sound card driver from the BeagleBone Green/Black to the BeagleBoard-X15 (https://summerofcode.withgoogle.com/archive/2016/projects/5351212496977920/). This port will now be ported to the BegleBone AI. With the sound card driver successfully ported, the next step would be to port the AVB protocol driver stack from Beagle Bone AVB enabling media streaming over the network. This would allow to use the Beaglebone AI as a media streaming device in professional audio/media applications and bring audio stream synchronisation features to the Beaglebone AI. Thus allowing for tight synchronization between different audio and video streams which are transmitted over the network.
Timeline
Provide a development timeline with a milestone each of the 11 weeks and any pre-work. (A realistic timeline is critical to our selection process.)
Mar 30 | Proposal complete, Submitted to https://summerofcode.withgoogle.com |
Apr 27 | Proposal accepted or rejected |
May 18 | Pre-work complete, Coding officially begins! |
May 25 | Milestone #1, Introductory YouTube video |
June 1 | Milestone #2 |
June 8 | Milestone #3 |
June 15 18:00 UTC | Milestone #4, Mentors and students can begin submitting Phase 1 evaluations |
June 19 18:00 UTC | Phase 1 Evaluation deadline |
June 22 | Milestone #5 |
June 29 | Milestone #6 |
July 6 | Milestone #7 |
July 13 18:00 UTC | Milestone #8, Mentors and students can begin submitting Phase 2 evaluations |
July 17 18:00 UTC | Phase 2 Evaluation deadline |
July 20 | Milestone #9 |
July 27 | Milestone #10 |
August 3 | Milestone #11, Completion YouTube video |
August 10 - 17 18:00 UTC | Final week: Students submit their final work product and their final mentor evaluation |
August 17 - 24 18:00 UTC | Mentors submit final student evaluations |
Experience and approach
During my bachelor's degree I had several courses like programming in c, programming in c++, operating systems and embedded system programming which layed down the basis for working with developing for hardware. Due to my additional bachelor's degree in audio production I have additional experience in audio applications and audio and media codecs, which will help me to understand the theory behind the different needed algorithms. With my previous development work for the Strämpler project I already have experience in working on complex embedded c projects and which potential pitfalls could occur.
Contingency
If I get stuck and my mentor is not around I will follow the following steps in displayed order:
- Search the internet for the problem.
- Serach through literature acquired during milestone #1.
- Ask in the GSoC IRC, if fellow students know a solution to the specific problem.
- If the problem is still not solved, postpone the problem until mentor is available again and work on another part of the project.
Benefit
If successfully completed, what will its impact be on the BeagleBoard.org community? Include quotes from BeagleBoard.org community members who can be found on http://beagleboard.org/discuss and http://bbb.io/gsocchat.
Misc
Link to pull request #139.
Suggestions
Is there anything else we should have asked you?