Difference between revisions of "BeagleBoard/GSoC/MediaIpStreaming"

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This project will equip the Beagleboard AI with Media IP Streaming capabilities, by porting the sound card drivers for [https://hackaday.io/project/9634-ctag-face-and-beast-multichannel-audio-systems CTAG face2|4 Audio Card] to the Beaglebone AI. Additionally the AVB protocol stack is ported from [https://elinux.org/BeagleBoard/GSoC/BeagleBoneAVB Beagle Bone AVB] to the Beaglebone AI.
 
This project will equip the Beagleboard AI with Media IP Streaming capabilities, by porting the sound card drivers for [https://hackaday.io/project/9634-ctag-face-and-beast-multichannel-audio-systems CTAG face2|4 Audio Card] to the Beaglebone AI. Additionally the AVB protocol stack is ported from [https://elinux.org/BeagleBoard/GSoC/BeagleBoneAVB Beagle Bone AVB] to the Beaglebone AI.
  
''Student'': [http://elinux.org/User:nwan]<br>
+
''Student'': [http://elinux.org/User:nwan nwan]<br>
''Mentors'': [https://elinux.org/User:Rma]<br>
+
''Mentors'': [https://elinux.org/User:Rma rma]<br>
 
''Code'': [N/A]<br>
 
''Code'': [N/A]<br>
 
''Wiki'': http://elinux.org/BeagleBoard/GSoC/MediaIpStreaming<br>
 
''Wiki'': http://elinux.org/BeagleBoard/GSoC/MediaIpStreaming<br>

Revision as of 07:08, 25 March 2020


Proposol of equipping the Beaglebone AI with Media IP Streaming capabilities

{{#ev:youtube|Jl3sUq2WwcY||right|BeagleLogic}}

This project will equip the Beagleboard AI with Media IP Streaming capabilities, by porting the sound card drivers for CTAG face2|4 Audio Card to the Beaglebone AI. Additionally the AVB protocol stack is ported from Beagle Bone AVB to the Beaglebone AI.

Student: nwan
Mentors: rma
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 in information technology I had several courses like programming in c, programming in c++, operating systems and embedded system programming which layed down the basis for developing embedded software. 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:

  1. Search the internet for the problem.
  2. Serach through literature acquired during milestone #1.
  3. Ask in the GSoC IRC, if fellow students know a solution to the specific problem.
  4. If the problem is still not solved, postpone the problem until mentor is available again and work on another part of the project.

Benefit

Equipping the Beaglebone AI with media ip streaming capabilities would allow the Beaglebone.org community to use those capabilities to implement the system in professional media applications. The community could also implement further media protocols like AES/Ravenna to allow the usage of the AI for even more media streaming tasks.

Misc

Link to pull request #139.

Suggestions

Is there anything else we should have asked you?