Daily traffic congestion, the dread of daily peak hours and delayed schedule, violation of traffic laws, and growing number of accidents on the road are all challenges we face today. With approximately 1.35 million deaths each year as a result of traffic crashes (WHO, 2020), this is an urgent problem for traffic management. Smart traffic control is urgently called for, these include robust and high-performance PC for real-time AI inference, training plus high efficiency of AI model deployment to enable real-time traffic monitor and management for a safer and smarter city.
ASRock Industrial is collaborating with Intel® to build AI BOX for smart traffic management. The system is powered by the iBOX-1185G7E running on Intel® 11th Gen Core™ Processors (Tiger Lake-UP3) with Intel® Iris® Xe Graphics plus new OpenVINO™ AI Deep Learning to boost high performance and real-time AI computing at 4.15 TFLOPS and 8.29 TOPS. With rich IOs, it collects data from multiple CCTV monitors through USB 3.2 Gen2 and IP camera through Intel® Gigabit LAN while connecting edge to cloud through Intel® 2.5 Gigabit LAN for real-time traffic management.
AI Capability |
Execution Units |
TFLOPS (FP16) |
TOPS (INT8) |
iBOX-1185G7E |
96 EU |
4.15 |
8.29 |
iBOX-1145G7E |
80 EU |
3.45 |
6.9 |
iBOX-1115G4E |
48 EU |
2.07 |
4.14 |
▲ AI Capability of iBOX 1100 Series
AI BOX enables smart traffic management with Intel® 11th Gen Core™ CPU and Intel® OpenVINO™ to monitor real-time road traffic, analyze flow, and make necessary adjustments during peak hours to avoid traffic jams and enhance safe driving for sustainable smart city development.
With license plate recognition capability, AI BOX can accurately detect, record, process, and transmit huge streams of license numbers 24/7. This decreases traffic violations, accidents, thus increases overall safety when driving.
The iBOX-1185G7E powered by Intel® 11th Gen Core™ CPU with Intel® Iris® Xe Graphics plus new OpenVINO™ AI Deep Learning can boost smart city development through accelerating the implementation of real-time traffic management system.