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July 11, 2026SustainabilityOpen Access

SYTRAC: An Edge AI-Based Intelligent Traffic Signal Control System Using OPC UA and Deep Learning for Smart City Applications

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FBFares BouriachiNDNacereddine DjelalBKBadreddine Kanouni

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Overview

Randomized trial demonstrates improved traffic flow in urban environments, suggesting a new cost-effective solution for congestion.

Key Points

  • This research aims to improve traffic signal control systems to reduce congestion and emissions in urban areas.
  • Developed SYTRAC, a low-cost adaptive traffic control system for urban environments.
  • Utilized real-time vehicle detection with an NVIDIA Jetson Nano GPU and a Siemens PLC for safety execution.
  • Validated the system in hardware-in-the-loop field deployments at a live intersection.
  • Achieved a 22.1% reduction in average vehicle delay (p<0.001).
  • Microscopic simulations showed up to 28.0% delay suppression during lane-blockage incidents.
  • The system resulted in environmental savings of 53.5–72 kg of CO2 avoided per day.

Cite This Study

Bouriachi et al. (2026) studied this question.

synapsesocial.com/papers/6a51e0f5c18d7f28ca500ecchttps://doi.org/10.3390/su18147010
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