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PoC Document

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InfiniEdge AI
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ONE summit CFP

ONE Summit Japan | LF Events
CFP Draft
How do Akraino and InfiniEdge AI contribute to the realization of Physical AI?

The convergence of AI and edge computing is poised to revolutionize various industries, driving unprecedented levels of automation, efficiency, and real-time decision-making. This presentation will delve into the rapid evolution of Edge AI and specifically focus on the burgeoning field of Physical AI. We will showcase how LF Edge projects, specifically Akraino and Infiniedge AI, enable these cutting-edge Edge AI use cases by providing a robust and comprehensive open-source reference stack covering infrastructure to the application layer.

The proliferation of IoT devices, the demand for ultra-low latency processing, and the increasing importance of data privacy and security are accelerating the adoption of Edge AI. By bringing AI capabilities closer to the data source, Edge AI enables real-time inference, reduces network traffic, and enhances data security. This paradigm shift allows applications in manufacturing, healthcare, smart cities, and autonomous vehicles, among others, to operate with greater autonomy and responsiveness.
Within Edge AI, Physical AI stands out as a particularly transformative domain. Physical AI refers to AI systems that directly interact with the physical world by perceiving the environment through sensors, processing information, and executing actions through actuators. This encompasses a wide range of applications, from robotic automation and predictive maintenance in industrial settings to intelligent surveillance and environmental monitoring. The ability of AI at the edge to directly influence and control physical processes opens new frontiers for innovation, enabling more adaptive, resilient, and intelligent systems.

Akraino and Infiniedge AI collaboratively provide a powerful open-source reference stack that addresses the end-to-end requirements for Physical AI at the edge.
This presentation will offer a detailed overview of how these projects work in concert to tackle the challenges and unlock the opportunities presented by Edge AI. Attendees will gain valuable insights into leveraging these open-source technologies to accelerate their Physical AI initiatives and contribute to the evolution of intelligent edge computing.

We can discuss these points in today’s meeting : Akraino–InfiniEdge AI Physical AI Blueprint : Joint collaboration: Objective

Akraino and InfiniEdge AI are jointly developing an open-source Physical AI at the Edge Blueprint to accelerate the adoption of intelligent, autonomous, secure, and resilient AI-driven systems across multiple industries.

The convergence of Artificial Intelligence, edge computing, and physical systems is poised to transform industries by enabling unprecedented levels of automation, operational efficiency, predictive intelligence, and real-time decision-making. This blueprint will provide a robust, end-to-end open-source reference architecture spanning the edge infrastructure, cloud-native platform, AI framework, data processing, security, and Physical AI application layers.

A key objective of the blueprint is to enable AI models to operate close to physical assets, sensors, machines, and industrial processes. By processing data and making decisions at the edge, the solution minimizes latency, reduces dependence on centralized cloud infrastructure, improves data privacy, and supports reliable operation even in environments with limited or intermittent connectivity.

Security will be incorporated directly into the Physical AI edge architecture to minimize cyber and operational risks. Security validation, workload assessment, trusted deployment, application gating, and continuous monitoring will be integrated throughout the lifecycle—from infrastructure provisioning and AI workload onboarding to runtime operations and lifecycle management.

By combining InfiniEdge AI’s Physical AI capabilities with Akraino’s proven edge architecture, open blueprints, automation, and lifecycle management principles, the joint blueprint aims to deliver maximum operational excellence through intelligent automation, predictive maintenance, and autonomous edge operations.

Key Capabilities

Secure Physical AI at the Edge
The blueprint will enable secure AI inference, real-time analytics, and autonomous decision-making directly at the edge. Security will be integrated into the infrastructure, platform, workloads, applications, and operational lifecycle to reduce attack surfaces and minimize risks associated with centralized data movement.

Real-Time, Low-Latency Intelligence
AI workloads will be deployed close to physical devices, sensors, machines, and operational environments. This enables low-latency data processing and rapid decision-making for time-sensitive Physical AI use cases.

Predictive Maintenance and Operational Excellence
By leveraging Akraino’s edge capabilities together with InfiniEdge AI’s Physical AI intelligence, the blueprint will support:

• Continuous monitoring of equipment and physical assets

• Early detection of anomalies and operational degradation

• AI-driven failure prediction

• Predictive and condition-based maintenance

• Reduced unplanned downtime

• Improved asset reliability and utilization

• Optimized maintenance schedules and operational costs

These capabilities will enable organizations to move from reactive maintenance to proactive and predictive operations, maximizing system availability and operational efficiency.

Autonomous and Zero-Touch Edge Operations
The blueprint will support autonomous, turnkey service enablement with:

• Zero-touch provisioning

• Automated deployment and configuration

• Automated operations and lifecycle management

• Continuous health and performance monitoring

• Automated maturity measurement

• Reduced operational complexity and OpEx

Support for Multiple Workload Types
The platform will support diverse edge workloads, including:

• Virtual Machines (VMs)

• Containers

• Microservices

• Cloud-native applications

• AI/ML inference workloads

• Physical AI applications

Application and Workload Assessment
The blueprint will provide mechanisms to assess and validate whether applications are suitable for edge deployment based on factors such as:

• Latency sensitivity

• Compute and resource requirements

• Data locality

• Code quality

• Security requirements

• Reliability and operational readiness

Scalable and Modular Architecture
Following Akraino’s design and build principles, the solution will provide:

• A finite and validated set of reference configurations to reduce deployment complexity

• Plug-and-play modular building blocks

• Cost-effective scalability

• Support for multiple cloud and edge management technologies

• Flexible deployment across diverse edge environments

High Availability, Resilience, and Continuity
The architecture will be designed around Akraino’s holistic principles of:

• Availability

• Capacity

• Security

• Resilience

• Business and service continuity

This will enable reliable Physical AI operations in distributed, remote, and mission-critical edge environments.

Open, Interoperable, and Hardware-Independent
The blueprint will leverage Akraino’s open-source and community-driven approach to provide:

• Open reference blueprints

• Hardware independence

• Cloud-provider independence

• Operating-system flexibility

• Interoperability across heterogeneous edge platforms

• Reduced vendor lock-in

Expected Industry Impact

The Akraino–InfiniEdge AI Physical AI Blueprint will enable intelligent and autonomous edge solutions across industries such as:

• Manufacturing and Industry 4.0

• Smart cities

• Energy and utilities

• Telecommunications

• Transportation and logistics

• Healthcare

• Retail

• Agriculture

• Critical infrastructure

By bringing secure AI intelligence closer to physical systems, the blueprint will enable faster decisions, improved safety, predictive maintenance, reduced downtime, optimized resource utilization, and higher operational efficiency.

Vision

The joint Akraino–InfiniEdge AI Physical AI Blueprint aims to establish a comprehensive, open-source reference stack that bridges edge infrastructure, cloud-native platforms, AI intelligence, security, and physical-world applications.

Through the combination of Akraino’s mature edge computing principles and InfiniEdge AI’s Physical AI capabilities, the blueprint will provide a secure, scalable, autonomous, and interoperable foundation for next-generation edge AI deployments—enabling organizations to achieve intelligent automation, predictive operations, and maximum operational excellence.

SL No.

Voting Member

Member Company

Y/N/A

1

@Ike Alisson

Alicon

2

@Jeff Brower

Signalogic

3

@Haruhisa Fukano

Fujitsu

4

@Yin Ding

Google

5

@thorking

Infortrend

6

@Vijay pal

PalC Networks

7

@Sujata Tibrewala

ByteDance 

8

@zhuguanyu

Huawei

9

10

11

12

13

14

15

16

17

18

19

20