Conference Paper

Bluetooth Low Energy (BLE) has emerged as a promising technology for Location-Based Services (LBSs), driving demand for localization datasets, particularly for AI/ML applications. However, existing BLE datasets are predominantly indoor and static. They rely solely on the Received Signal Strength Indicator (RSSI) and lack key BLE 5.1 features, such as the Angle of Arrival (AoA). In this paper, we highlight the need for dynamic BLE 5.1-based localization datasets in public transportation. To bridge this gap, we introduce a BLE data collection setup featuring "SessionLogger", an open-source Android app for dataset labeling, and a flexible, centralized system architecture. The proposed application and system architecture lay the foundation to collect a dynamic outdoor BLE 5.1 dataset incorporating RSSI and AoA. Experiments validated the effectiveness of our setup to collect data, demonstrating its potential to facilitate the first outdoor BLE 5.1 dataset for public transportation research.