BSP-Aware Framework for Edge AI on Industrial Embedded Platforms
A new paper argues that Edge AI deployment on industrial embedded platforms must be treated as a systems problem, not just a model packaging exercise. The framework is organized around five layers: hardware, BSP/OS adaptation, runtime/acceleration, application/inference, and operations/validation. The approach addresses challenges like vendor-specific kernels, heterogeneous accelerators, safety constraints, and complex I/O paths. The paper is grounded in vendor-specific implementations and emphasizes the role of the board support package (BSP) in the execution chain from sensor to production service loop. The work is published on arXiv with ID 2605.26119.
Key facts
- Paper ID: arXiv:2605.26119
- Title: Edge AI Deployment Beyond Models: A BSP-Aware Systems Framework for Industrial Embedded Platforms
- Argues Edge AI deployment is a systems problem
- Framework has five layers: hardware, BSP/OS adaptation, runtime/acceleration, application/inference, operations/validation
- Addresses vendor-specific kernels, heterogeneous accelerators, safety constraints, I/O paths
- Emphasizes BSP role in execution chain from sensor to production service loop
- Published on arXiv
- Type: cross
Entities
Institutions
- arXiv