Infrastructure-Free Indoor Localization for Cultural Heritage Sites

Indoor positioning systems are crucial for preserving and promoting cultural heritage sites by providing visitors with accurate location information and real-time exhibit details. These systems also offer valuable insights into visitor behavior for museums and cultural institutions to optimize their offerings and enhance the overall visitor experience. Their importance lies in driving engagement, fostering deeper connections with visitors, and providing data for future decision-making. This study proposes a magnetic field-based pedestrian localization algorithm as a solution to the challenge of providing accurate location information for visitors in indoor environments during virtual tours. The proposed approach uses magnetic field sequences to identify unique landmarks and a deep neural network (VGG-16) to analyze magnetic signal features and determine the visitor's location based on the nearest landmark. The study's results indicate that this magnetic field-based approach can be reliable for providing location information in indoor environments.