Department of Computer Engineering, Kadir Has University, 34083 Istanbul, Turkey.
Department of Interior Architecture and Environmental Design, Kadir Has University, 34083 Istanbul, Turkey.
Sensors (Basel). 2017 Dec 16;17(12):2925. doi: 10.3390/s17122925.
Behavior mapping (BM) is a spatial data collection technique in which the locational and behavioral information of a user is noted on a plan layout of the studied environment. Among many indoor positioning technologies, we chose Wi-Fi, BLE beacon and ultra-wide band (UWB) sensor technologies for their popularity and investigated their applicability in BM. We tested three technologies for error ranges and found an average error of 1.39 m for Wi-Fi in a 36 m² test area (6 m × 6 m), 0.86 m for the BLE beacon in a 37.44 m² test area (9.6 m × 3.9 m) and 0.24 m for ultra-wide band sensors in a 36 m² test area (6 m × 6 m). We simulated the applicability of these error ranges for real-time locations by using a behavioral dataset collected from an active learning classroom. We used two UWB tags simultaneously by incorporating a custom-designed ceiling system in a new 39.76 m² test area (7.35 m × 5.41 m). We considered 26 observation points and collected data for 180 s for each point (total 4680) with an average error of 0.2072 m for 23 points inside the test area. Finally, we demonstrated the use of ultra-wide band sensor technology for BM.
行为映射 (BM) 是一种空间数据采集技术，用于记录用户在研究环境的平面布局中的位置和行为信息。在众多室内定位技术中，我们选择 Wi-Fi、BLE 信标和超宽带 (UWB) 传感器技术，因为它们具有普及性，并研究了它们在 BM 中的适用性。我们测试了三种技术的误差范围，发现 Wi-Fi 在 36 m²测试区域（6 m × 6 m）中的平均误差为 1.39 m，BLE 信标在 37.44 m²测试区域（9.6 m × 3.9 m）中的平均误差为 0.86 m，超宽带传感器在 36 m²测试区域（6 m × 6 m）中的平均误差为 0.24 m。我们通过使用从主动学习教室收集的行为数据集模拟了这些误差范围对实时位置的适用性。我们在一个新的 39.76 m²测试区域（7.35 m × 5.41 m）中同时使用两个 UWB 标签，并结合了一个定制的天花板系统。我们考虑了 26 个观测点，并为每个点收集了 180 秒的数据（总共 4680 个数据点），在测试区域内的 23 个点的平均误差为 0.2072 m。最后，我们展示了超宽带传感器技术在 BM 中的应用。
