HYBRID BLE–PDR LOCALIZATION SYSTEM FOR SMART RETAIL ENVIRONMENTS
Abstract
Accurate indoor user localization is a key component in the development of cashier-free smart stores, enabling advanced customer experiences, security monitoring, and behavioral flow analysis. This paper presents a hybrid localization approach that combines inertial motion tracking (Pedestrian Dead Reckoning – PDR) with Bluetooth Low Energy (BLE) tag signals. Unlike systems that require dedicated infrastructure, the proposed solution uses existing BLE electronic shelf labels (ESLs) as reference points. Their identification signals are used to correct the PDR drift, thereby reducing the cumulative error typical of purely inertial methods. The mobile application continuously measures the Received Signal Strength Indicator (RSSI) from BLE tags and applies threshold-based position corrections, while the PDR module, based on the Scarlett step-length model, maintains continuous tracking between tags. The system additionally integrates map-based spatial constraints that eliminate physically impossible paths through a particle-filter mechanism. Experimental evaluation in a retail environment demonstrated an average error of 0.4 m for linear movement and 1.3 m for a complex circular trajectory, confirming meter-level localization accuracy without the need for cloud processing. All computations are performed locally on the user’s device, ensuring privacy protection and enabling real-time movement analysis and context-aware retail interaction.
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