Early Steps in Automated Behavior Mapping via Indoor Sensors

Area of Science:

• Spatial data collection
• Indoor positioning systems
• Behavioral analysis

Background:

• Behavior mapping (BM) is a spatial data collection technique.
• Indoor positioning technologies like Wi-Fi, BLE beacon, and ultra-wide band (UWB) sensors are popular for tracking user location and behavior.
• Investigating the applicability of these technologies in BM is crucial for enhancing spatial data accuracy.

Purpose of the Study:

• To evaluate the accuracy of Wi-Fi, BLE beacon, and UWB sensor technologies for behavior mapping.
• To compare the error ranges of different indoor positioning systems in a controlled environment.
• To demonstrate the effectiveness of UWB sensors for real-time behavior mapping in an active learning classroom setting.

Main Methods:

• Tested Wi-Fi, BLE beacon, and UWB sensor technologies for error ranges in defined test areas.
• Collected behavioral data from an active learning classroom to simulate real-time location applicability.
• Utilized two UWB tags with a custom ceiling system in a new test area, collecting data from 26 observation points.

Main Results:

• Wi-Fi showed an average error of 1.39 m, BLE beacon 0.86 m, and UWB sensors 0.24 m in initial tests.
• In a simulated real-time scenario using UWB, an average error of 0.2072 m was achieved for points within the test area.
• UWB sensor technology demonstrated high accuracy and suitability for behavior mapping.

Conclusions:

• Ultra-wide band (UWB) sensor technology is highly accurate and suitable for behavior mapping.
• UWB offers a significant improvement in spatial data collection accuracy compared to Wi-Fi and BLE beacons.
• The findings support the use of UWB for precise, real-time behavior mapping in various environments.