gtechna’s smart parking management and enforcement solution is trusted by leading cities worldwide. Our cloud-based system empowers municipalities, transportation agencies, and universities with cutting-edge applications that increase parking revenue, cut operational costs, and improve the driver experience.
By choosing gtechna for your parking management and enforcement needs, you're partnering with an industry leader known for constant innovation. Cities like Washington, D.C., Boston, Pittsburgh, Toronto, and Vancouver have already transformed their parking infrastructure with gtechna—now it's your turn to experience the future of parking.
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Elecard Boro is a professional software solution designed to monitor video stream health and track QoS/QoE parameters across distributed networks. By providing centralized access to statistics and automated reporting, Boro enables telecom professioals to build a powerful monitoring ecosystem from scratch or easily scale existing infrastructure to ensure flawless broadcast quality.
How it works:
Boro utilizes distributed software probes to monitor UDP, RTP, HTTP, HLS, DASH, SRT, and RTMP streams. By aggregating multi-point measurements on a centralized server, operators can instantly isolate quality degradation across the entire delivery chain. The platform provides network-wide visibility and real-time alerts for ETSI TR 101 290 errors via Email, SNMP, Webhook, PagerDuty, and Telegram.
Key Features:
• Rapid Deployment & Scalability: Launch a monitoring probe in just 30 minutes. Easily scale your infrastructure by adding new probes to the unified Boro ecosystem on any hardware.
• Proactive Issue Resolution: Monitor over 50 QoS and QoE parameters (including full ETSI TR 101 290 compliance) and use triggers to localize network anomalies before they impact viewers.
• Advanced Diagnostics: Use comprehensive analysis of SCTE-35 ad-insertion cues and PCAP stream recording for in-depth delivery troubleshooting.
• Effortless Integration & Access: Access monitoring data from any device via an intuitive web interface. Seamlessly integrate Boro into your existing workflow using WebHook, SNMP, and ControlAPI.
• Operational Efficiency: Reduce the workload on QA and network engineers through automated regular reporting, advanced visualization dashboards, and smart threshold tuning that eliminates false alarms.
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Carmen FreeFlow
Carmen FreeFlow is a powerful AI-driven automatic numberplate recognition (ANPR), designed for high-speed and high-accuracy license plates reading across a wide range of applications, from traffic monitoring through to tolling. Its robust performance under various lighting and weather conditions provides exceptional flexibility in free-flow traffic environments. Carmen FreeFlow integrates seamlessly with existing system and supports various plate types. It delivers real-time data that improves operational efficiency. It's perfect for businesses looking for a scalable and reliable ANPR system that can adapt to changing traffic conditions.
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Carmen Cloud
Carmen® Cloud is an innovative cloud-based solution for Automatic Number Plate Recognition (ANPR) that utilizes cutting-edge machine learning techniques to accurately identify license plates, as well as the make, model, and color of vehicles in more than 200 nations. The system's algorithms are designed to be dynamic, allowing them to continuously evolve and maintain dependable performance even in challenging environments.
With the convenience of a single API call, it enables easy access to ANPR, Make and Model Recognition (MMR), and Hazard Identification Number Recognition (ADR), facilitating quick implementation in various contexts such as traffic surveillance, parking systems, and security measures. Carmen® Cloud's robust and scalable architecture can handle varying operational demands, ensuring rapid insights without any delays or bottlenecks.
The solution's worldwide applicability and flexible deployment options make it an ideal choice for organizations that require reliable and precise vehicle recognition solutions, ultimately enhancing their operational efficiency and security measures. Furthermore, its adaptability to different scenarios underscores its significance in modern vehicle management systems.
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