GRIDSMART is an edge computer vision system that uses omnidirectional imaging to detect and track objects through intersections to optimize traffic signal timing in response to traffic demands. The system comprises an IP fisheye camera mounted above the roadway, connected to an x86-based processor located in a roadside traffic cabinet. GRIDSMART is deployed in over 7,000 locations worldwide in about 1,300 communities. In this presentation, we describe how GRIDSMART implements some of its current capabilities using traditional computer vision and machine learning techniques. We also discuss recently developed capabilities for protecting vulnerable road users that employ deep, convolutional neural networks on the CPU using Intel’s OpenVINO toolkit. We also examine environmental requirements in the Intelligent Transportation Systems (ITS) application space as they relate to both computation and imaging, and the challenges these pose as we look to implement additional capabilities in the future.