In traffic enforcement, every violation that goes undetected is a missed opportunity to improve road safety. But for Intelligent Transportation System (ITS) deployments, reliable license plate capture at highway speeds remains a formidable challenge.
Real-world conditions throw everything at these systems, such as high-speed motion blur, inconsistent plate formats across states, nighttime glare from headlights, and more.
So, when a U.S.-based provider of ALPR and traffic enforcement solutions needed to overcome these obstacles at scale, they turned to e-con Systems.
Their goal was to deploy a solution that could handle fixed and mobile enforcement, operate in challenging locations, and meet stringent U.S. procurement requirements.
What Challenges Were Faced By Our Client?
- Lack of capture accuracy at vehicle speeds and distances up to ~150 feet in multi-lane traffic
- Inability to precisely measure speed
- Too many infrastructure dependencies
- No integrated high-output IR illumination for nighttime and low-light operation
- Lack of support for remote deployments
Most readymade camera systems lacked the resilience, clarity, or integration capabilities required. The client needed a purpose-built solution designed from the ground up for the unique demands of American roadways.
How e-con Systems Offered a Custom Edge AI ALPR Solution
e-con Systems developed a complete edge-based ALPR camera system optimized for accuracy, reliability, privacy, and ease of deployment in infrastructure-constrained environments.
The highlights of the solution were:
- Dual-camera hardware architecture: The solution came with a 2MP color global shutter camera for daytime capture and vehicle attribute extraction. It was also equipped with a 2MP monochrome global shutter camera for IR-based night vision and license plate capture.
- ALPR accuracy optimization: e-con Systems worked closely with the client to improve real-world ALPR performance through ISP tuning to enhance plate contrast and image quality optimization.
- Edge processing platform: The cameras ran ALPR and vehicle analytics locally at the edge, reducing bandwidth and cloud dependency while enabling real-time alerts and enforcement workflows.
- Privacy and security: The solution incorporated on-device face anonymization, automatic blurring of pedestrians and driver faces, and selective object masking.
- Rugged, deployment-ready design: The IP68-rated enclosure with military-grade aluminum housing featured inert-gas filling for long-term internal stability – with dual power input and wired/wireless connectivity options.
Business Benefits of Our Edge AI ALPR Solution
- High-accuracy ALPR at highway speeds, including low-light and adverse weather conditions
- Faster time to market from a complete ODM solution combining camera hardware, edge processing, connectivity, and ALPR software
- BABA alignment support for U.S. transportation RFQs, improving readiness for federally funded projects
- Improved violation detection rates by reducing missed events and false positives by 10–20%
Want the deeper dive on this Edge AI ALPR solution for fixed and mobile traffic enforcement?
Read the full case study for the detailed walkthrough.
Exploring a similar imaging solution? Email camerasolutions@e-consystems.com to get in touch with our experts.
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Dilip Kumar is a computer vision solutions architect having more than 8 years of experience in camera solutions development & edge computing. He has spearheaded research & development of computer vision & AI products for the currently nascent edge AI industry. He has been at the forefront of building multiple vision based products using embedded SoCs for industrial use cases such as Autonomous Mobile Robots, AI based video analytics systems, Drone based inspection & surveillance systems.