While outdoor maps are ubiquitous, navigating large and complex indoor venues like shopping malls and airports remains a significant challenge for users. Traditional solutions, often static image-based maps provided by facility operators, lack the flexibility required for modern applications. These image maps are difficult to update and do not support crucial features like interactive search or real-time data integration, as the locational information is not structured as usable data.

This presentation tackles these challenges head-on. We will demonstrate how to build a powerful, data-driven indoor mapping solution using open-source tools.

First, we will introduce the Indoor Mapping Data Format (IMDF), an international standard by Apple, and explain how to model a venue's floors, units, and points of interest.

Next, we will walk through the technical implementation of parsing this IMDF data and rendering it as an interactive, multi-layered indoor map with MapLibre.

Finally, going beyond simple map display, we will detail the implementation of a practical search feature. Attendees will learn how to leverage the structured IMDF data to allow users to find specific points of interest, such as stores that are currently open or the nearest available restroom, transforming the map from a static image into a dynamic and genuinely useful tool.

Key Takeaways for the Audience:

• A solid understanding of the Indoor Mapping Data Format (IMDF) structure and how to apply it to a real-world venue.
• A step-by-step guide to processing IMDF data and rendering it as a multi-level indoor map using MapLibre.
• Actionable techniques for implementing dynamic search and filtering functionalities based on real-time data (e.g., business hours, facility status) over the indoor map.