Convenient for SI/DFSI (Domain-focused Solution Integrator) integration, WISE-PaaS/AFS can build the inference engine as a RESTful API and it supports Windows, Linux, and Android operating platforms to quickly interface with heterogeneous systems and customize the best AIoT application scenarios for customers. The AFS inference engine can be packaged as a Docker Image or EdgeX Foundry—both of which support remote deployment.
Since AFS runs on the WISE-PaaS industrial IoT platform
, it inherits WISE-PaaS and supports the characteristics of public, private, and hybrid clouds. For public clouds, it supports Azure, AWS, and Alibaba Cloud. For private clouds, it is based on Advantech WISE-STACK software and a hardware-integrated edge intelligence private cloud solution. For hybrid clouds, public clouds paired with the Advantech GPU server allows GPU computing to run on its own platform, thereby reducing computing costs.
Jamie Su emphasized that WISE-PaaS/AFS services contain a number of important functional modules. First, the multi-model training module is based on Hadoop Yarn and Kubernetes technologies to help users realize flexible dividing, scheduling, and management of computing resources. Secondly, AFS supports multiple databases such as PostgreSQL, InfluxDB, MongoDB, and Ceph. It can also interface with WISE-PaaS/APM data sources, enabling data scientists and AI engineers to quickly integrate various types of data for model building and training.
The Workspace module integrates the Jupyter Notebook framework in advance, making it easy for users to develop algorithms directly online. Secondly, it provides an offline development environment. Even if users write code in non-Python language, the code can still be packaged as a Docker Image and uploaded to AFS for online execution. Other modules such as Catalog, Task, Model Board, and Inference can help users to subscribe to third-party open source algorithms, set up automatic scheduling of model retraining and deployment, view model training performance through visual tools, and manage large numbers of models and multiple sources of information respectively.