IAV Merida

IAV Merida provides a robust platform for intelligently storing, managing, and analyzing vehicle data, delivering comprehensive real-time insights. It addresses the challenge of increasing data volume in automotive development and fleet testing.

Key components include:

• IAV Merida Hub: The core for secure, structured measurement data management with flexible storage and high security standards.
• IAV Merida Analyzer: A scalable framework for real-time and predictive analytics using AI and ML.
• IAV Merida Transmitter: Ensures secure, automated data upload from various sources, preventing redundancy and enabling remote updates.
• IAV Merida Signals and Signals Web: For direct visualization and analysis of measurement data in various formats.
• IAV Merida Finder: Enables complex searches across all measurements, presenting visualized results and correlations within seconds.
• IAV Merida Dashboards: Offers intuitive, interactive data visualization with comprehensive filter functions for targeted analysis.

IAV Merida is applicable in fleet testing, real-time fault analysis, and weather-dependent notifications. It supports long-term fleet management optimization, efficient vehicle and test bench management, data-driven development with AI-supported anomaly detection, and live vehicle data display. The platform is adaptable for any data-producing units.

Key benefits include:

• Real-time insights: Collect, store, and analyze data for an overview of vehicles and measurement technology status.
• Powerful analysis frameworks: Process diverse data formats quickly to shorten development cycles.
• Efficient administration: Organize measuring devices, configurations, and metadata for effective fleet management.
• Full control: Manage permissions, visibility, and track changes with high data protection standards.
• Data handling made easy: Supports common data formats and provides worldwide data access.
• Flexible storage options: Choose between public, hybrid, or private cloud models with unlimited scalability.