CAIRO.thws Research Team Introduces a New Approach to Indoor Position Estimation

Würzburg, Germany

The Center for Artificial Intelligence (CAIRO.thws) at Technical University of Applied Sciences Würzburg-Schweinfurt (THWS) is pleased to share the publication of a new study in the Sensors Journal (CiteScore 2024: 8.2, Q1 ranking), titled "Unified Probabilistic and Similarity-Based Position Estimation from Radio Observations." This work, conducted by Max Werner, Markus Bullmann, Dr. Toni Fetzer, and Prof. Dr. Frank Deinzer, explores enhancements in Indoor Localization technology.

Recognizing the challenges faced by traditional GNSS/GPS systems indoors, the CAIRO.thws research team has developed a probabilistic model that leverages Wi-Fi and Bluetooth signals for more reliable position estimation in complex environments.

Highlights of the Study:

• The model offers position estimates as probability densities, which can seamlessly integrate with other sensor data for continuous tracking. 
• It operates without specific radio physics assumptions, making it applicable to various signal measurements, including signal strength and round-trip time.
• The approach is resilient, providing accurate position estimates even when only a few access points are available.

Testing conducted with commercially available smartphones has shown promising results, delivering average positioning errors of less than 2 meters, with accuracy potentially reaching up to 1 meter under certain conditions.

Explore the full paper for more detailed insights: https://www.mdpi.com/1424-8220/25/13/4092

This study illustrates CAIRO.thws's commitment to tackling real-world challenges in indoor navigation and enhancing the reliability of location-based services in complex settings.

For more updates, stay connected with CAIRO.thws (e.g. on LinkedIn).