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Akraino’s AI Edge-School/Education Video Security Monitoring Blueprint

Written by Hechun Zhang, Staff Systems Engineer, Baidu; Akraino TSC member, and PTL of the AI Edge Blueprint; and Tina Tsou, Enterprise Architect, Arm and Akraino TSC Co-Chair

In order to support end-to-end edge solutions from the Akraino community, Akraino uses blueprint concepts to address specific Edge use cases. A Blueprint is a declarative configuration of the entire stack i.e., edge platform that can support edge workloads and edge APIs. In order to address specific use cases, a reference architecture is developed by the community.

The School/Education Video Security Monitoring Blueprint belongs to the AI Edge Blueprint family. It focuses on establishing an open source MEC platform that combined with AI capacities at the Edge. In this blueprint, latest technologies and frameworks like micro-service framework, Kata container, 5G accelerating, and open API have been integrated to build a industry-leading edge cloud architecture that could provide comprehensive computing acceleration support at the edge. And with this MEC platform, Baidu has expanded AI implementation across products and services to improve safety and engagement in places such as factories, industrial parks, catering services, and classrooms that rely on AI-assisted surveillance.

Value Proposition

  • Establish an open-source edge infrastructure on which each member company can develop its own AI applications, e.g. video security monitoring.
  • Contribute use cases which help customers adopt video security monitoring, AI city, 5G V2X, and Industrial Internet applications.
  • Collaborate with members who can work together to figure out the next big thing for the industry.

Use cases

Improved Student-Teacher Engagement

 

Using deep learning model training for video data from classrooms, school management can evaluate class engagement and analyze individual student concentration levels to improve real-time teaching situations.

Enhanced Factory Safety and Protection

Real-time monitoring helps detecting factory workers who might forget security gadgets, such as helmets, safety gloves, and so on, to prevent hazardous accidents in the workplace. Companies can monitor safety in a comprehensive and timely way, and used findings as a reference for strengthening safety management.

Reinforced Hygiene and Safety in Catering

Through monitoring staff behavior in the kitchen, such as smoking breaks and cell phone use, this solution ensures the safety and hygiene of the food production process.

Advanced Fire Detection and Prevention

Linked and networked smoke detectors in densely populated places, such as industrial parks and community properties, can help quickly detect and alert authorities to fire hazards and accidents.

Network Architecture

OTE-Stack is an edge computing platform for 5G and AI. By virtualization it can shield heterogeneous characteristics and gives a unified access of cloud edge, mobile edge and private edge. For AI it provides low-latency, high-reliability and cost-optimal computing support at the edge through the cluster management and intelligent scheduling of multi-tier clusters. And at the same time OTE-Stack makes device-edge-cloud collaborative computing possible.

Baidu implemented video security monitoring blueprints on the Arm infrastructure, including cloud-edge servers, hardware accelerators, and custom CPUs designed for world-class performance. Arm and Baidu are members of the Akraino project and use edge cloud reference stack of networking platforms and cloud-edge servers built on Arm Neoverse. The Arm Neoverse architecture supports a vast ecosystem of cloud-native applications and combines AI Edge blueprint for an open source mobile edge computing (MEC) platform optimized for sectors such as safety, security, and surveillance.

“Open source has now become one of the most important culture and strategies respected by global IT and Internet industries. As one of the world’s top Internet companies, Baidu has always maintained an enthusiastic attitude in open source, actively contributing the cutting edge products and technologies to the Linux foundation. Looking towards the future, Baidu will continue to adhere to the core strategy of open source and cooperate with partners to build a more open and improved ecosystem.” — Ning Liu, Director of AI Cloud Group, Baidu

In the 5G era, OTE-Stack has obvious advantages in the field of edge computing:

  • Large scale and hierarchical cluster management
  • Support third cluster
  • Lightweight cluster controller
  • Cluster autonomy
  • Automatic disaster recovery
  • Global scheduling
  • Support multi-runtimes
  • Kubernetes native support

For more information about this Akraino Blueprint, click here.  For general information about Akraino Blueprints, click here.