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The AI Edge – School/Education Video Security Monitoring Blueprint

Project Technical Lead:  Hechun Zhang, Baidu, Elected 10/21/19


Blueprint species:

Use Case Attributes

Description

Informational

Type

The AI Edge

 

Blueprint Family

New

 

Use Case

Safety, security, and surveillance

 

Blueprint proposed Name

The AI Edge

 

Initial POD Cost (capex)

Leverage Unicycle POD - less than $150K

 

Scale & Type

up to 4 servers, x86/ Arm server or deep edge class

With nVIDIA Telsa P4/T4 GPUs

 

Applications

1. Small scale IoT data aggregation and machine learning platform

2. Small scale deep learning models training for video data

3. Model training for AcumosApps

 

Power and memory restrictions

Less than 10Kw

K8s 1.12.5 or above- Container Orchestration

OS –CentOS 7.0 or above

 

Infrastructure orchestration

Docker 1.13.1 or above

 

SDN

Calico container networking, or OVS-DPDK

 

DataplaneVPP

Workload Type

Containers

 

Additional Details

Acumos and EdgeX interfaces will be connected in this case

 


Attachment: 


Committer

Affiliation

 Committer Contact Info

Committer Bio

Committer Picture

Self Nominate for PTL (Y/N)

Hechun Zhang

Baidu

zhanghechun@baidu.com

Seasoned MEC and 5G Solution Architect of Baidu, with impressive 9 years  experience in ICT industry.

Project Manager of ODCC Edge Computing Group.


                       Y

Dechao KongBaidukongdechao@baidu.com


Gang ChenBaiduchengang13@baidu.com


Zhenhua XuBaiduxuzhenhua02@baidu.com


Siyi HeBaiduhesiyi@baidu.com


Arm



@Yipan DengIntelyipan.deng@intel.com


PSU




N
Raviraj MahatmeArmraviraj.mahatme@arm.com



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2 Comments

  1. Gateway built on NXP LS1043, 1046 based on A53, A72 may be suitable for video security monitoring.

  2. The amount of compute required for this depends greatly on the desired sample rate of the video (e.g. real-time video processing at 30fps vs captured samples at 1 fps). More information on this is necessary before a suitable gateway architecture can be suggested.