Modular Visualization Framework for Telematics Data

The Information Networking Institute capstone project at Carnegie Mellon University focuses on creating a modular visualization framework for telematics data. This project developed an interactive dashboard designed to display and process telematic trajectory data, making complex datasets more useful and accessible. The framework integrates various tools and plugins, allowing users to visualize data through an interactive map, analyze trajectories with detailed overlays, and access a time slider for historical data playback. With a customizable and modular design, the framework supports the integration of future plugins, catering to specific analysis needs in telematics.

A core feature of the project is the interactive map that provides a detailed view of telematics data. Users can visualize vehicle trajectories, with the ability to zoom in on specific areas for more detailed analysis. The map includes overlays for speed, distance, and other relevant metrics, enabling users to gain insights into the movement patterns and behaviors of vehicles. This functionality can be useful for urban planners, logistics companies, and researchers who need to analyze large volumes of telematics data.

The dashboard also includes a time slider feature that allows users to playback historical telematics data. This capability is essential for identifying trends and patterns over time, adding a temporal dimension to the data analysis. Users can track changes in vehicle trajectories, speed variations, and other metrics over specific periods, helping them understand how certain factors influence vehicle behavior. This feature enhances the analytical capabilities of the framework, making it suitable for long-term studies and evaluations.

Customization is a significant aspect of the modular visualization framework. The project team designed the dashboard to be flexible, allowing users to add or remove plugins based on their specific needs. This modular approach ensures that the framework can adapt to various use cases and requirements, from simple data visualization tasks to more complex analytical functions. The ability to integrate new plugins also means the framework can evolve with advancements in telematics and data visualization technologies.

The development of this modular visualization framework involved a collaborative effort from a diverse team of students, each contributing their expertise in different areas. The project utilized technologies such as NextJS, SUMO (Simulation of Urban Mobility), A/B Street, and Grafana. Over 16 weeks, the team aimed to create a framework that meets current needs and anticipates future demands in telematics data analysis. Through this project, the team has provided a tool that enhances the way telematics data is analyzed and utilized, benefiting various stakeholders in the industry.