Estimating Indoor Behavior Using Sensor Fusion with BLE Beacons and Wearable Devices for Information Presentation.

This paper presents a work on estimating user indoor behavior with multi-sensor to use for information presentation. The authors have developed a mobile app to capture user’s indoor physical movement and collect their temporal feedback for comparison with BLE (Bluetooth Low Energy) beacons and wearable devices. The authors tested our estimation method on students and visitors at the museum and the library. The authors estimated the user position with BLE beacons and user motion with wearable devices using neural network from data collected by the app. Therefore, the user behavior is estimated integrated user position and motion information with 60% of precision at the museum and 85% at the library.