Edge AI Station

My contribution

At EDGEMATRIX, I lead engineering around Edge AI Station while remaining involved in architecture and implementation. My work spans video pipelines, application packaging, device management, monitoring, remote operation, and supporting cloud services.

Edge AI Station is an EDGEMATRIX product developed through a team effort. This page describes my professional contribution alongside the product's public capabilities.

Beyond running a model

A deployed video AI system needs a way to configure inputs, install applications, understand resource use, and respond to events. These concerns connect product design with the engineering of video processing and operations.

EDGEMATRIX's public product documentation describes local operation, multiple camera inputs, application management, resource monitoring, and remote support. Together, these give operators ways to run and inspect the system after deployment.

Connecting AI to building systems

My background in building systems provides context for connecting video analysis to the software used to operate physical infrastructure. Building integration is one application of video AI, alongside uses in transport and other infrastructure.

A public example is the integration between Edge AI Station and Shimizu's DX-Core building platform. Node-RED receives inference events and publishes them through MQTT for use by the building system. The integration links video analysis with the systems that act on it.

Public product reference

For the product's features, interface examples, and configuration options, see EDGEMATRIX's documentation.