Average Ratings 0 Ratings
Average Ratings 0 Ratings
Description
Carmen® Worker is an on-site Automatic Number Plate Recognition (ANPR) software that provides rapid, real-time vehicle identification tailored to your organization's infrastructure. Built to function without reliance on cloud platforms, it guarantees total data confidentiality and minimal processing delays, making it well-suited for sectors that demand stringent data governance, including access control, parking oversight, toll collection, and traffic regulation. This software can recognize license plates from over 160 countries and accommodates more than 38,000 different plate designs, enabling seamless integration with current systems via its Vehicle API and Transport API for straightforward implementation across diverse infrastructure configurations. Moreover, Carmen® Worker is fully adaptable, offering customizable options to satisfy the specific requirements of each deployment, which includes regional settings and parameter tweaks that enhance precision and effectiveness in various operational contexts. Additionally, the software's flexibility makes it a preferred choice for organizations looking to improve operational workflows while maintaining high standards of data security.
Description
SCOOT operates as an advanced proactive system that modifies traffic signal settings in real-time to accommodate vehicles approaching intersections. In contrast, alternative systems rely on data from departing traffic, which results in timing changes that are often implemented too late to achieve optimal effectiveness. At the core of SCOOT lies an online traffic simulation model that evaluates a variety of potential timing adjustments in real-time, selecting the most efficient option. Other systems typically make modifications based on set parameter thresholds, such as traffic volumes or the number of arrivals on green, which restricts them to a single potential adjustment without prior effectiveness testing. SCOOT, on the other hand, consistently optimizes cycle length, splits, and offsets with each cycle by executing small, controlled modifications. Many alternative systems opt for larger adjustments on a much longer schedule, sometimes up to every 10 minutes, and some do not even optimize cycle length at all. Consequently, these other systems are significantly less adept at responding to the rapidly fluctuating conditions of traffic. This responsiveness makes SCOOT particularly advantageous in urban environments with dynamic traffic patterns.
API Access
Has API
No
API Access
Has API
No
Screenshots View All
No images available
Integrations
No details available.
Integrations
No details available.
Pricing Details
No price information available.
Free Trial
Yes
Free Version
No
Pricing Details
No price information available.
Free Trial
No
Free Version
No
Deployment
Web-Based
No
On-Premises
Yes
iPhone App
No
iPad App
No
Android App
No
Windows
No
Mac
No
Linux
No
Chromebook
No
Deployment
Web-Based
Yes
On-Premises
No
iPhone App
No
iPad App
No
Android App
No
Windows
No
Mac
No
Linux
No
Chromebook
No
Customer Support
Business Hours
Yes
Live Rep (24/7)
No
Online Support
Yes
Customer Support
Business Hours
No
Live Rep (24/7)
No
Online Support
Yes
Types of Training
Training Docs
Yes
Webinars
Yes
Live Training (Online)
Yes
In Person
Yes
Types of Training
Training Docs
Yes
Webinars
No
Live Training (Online)
No
In Person
No
Vendor Details
Company Name
Adaptive Recognition
Founded
1991
Country
Hungary
Website
adaptiverecognition.com
Vendor Details
Company Name
Siemens
Founded
1989
Country
Germany
Website
www.mobility.siemens.com/us/en/portfolio/road/traffic-management/scoot-adaptive-traffic-control.html