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A platform for research: civil engineering, architecture and urbanism
Detection of Pause in a Pedestrian's Movement on a Linear Walkway using Bluetooth Low Energy Received Signal Strength Indicator
In recent years, Bluetooth Low Energy (BLE) has amassed significant attention in several applications. Its potential, however, remains largely unexplored for understanding pedestrian behaviour. This study focuses on investigating the potential of BLE in identifying pedestrian activity in an outdoor linear walkway. We specifically examine the likelihood of detecting pauses in the movement of pedestrians on a linear walkway using the strength of the signals obtained from a BLE device carried by the pedestrian. To accomplish this, a volunteer pedestrian intentionally pauses at selected points on the chosen walkway for varying predetermined intervals. The obtained data was conditioned using a polynomial curve to reduce the impact of anomalous data and was subsequently used to detect flatness in the trend of the signals to identify a pause. This flatness was identified using a sliding window standard deviation (SD) calculation over the curve obtained through polynomial fitting. Our results indicate a strong likelihood of detecting long pauses in a pedestrian's journey.
Detection of Pause in a Pedestrian's Movement on a Linear Walkway using Bluetooth Low Energy Received Signal Strength Indicator
In recent years, Bluetooth Low Energy (BLE) has amassed significant attention in several applications. Its potential, however, remains largely unexplored for understanding pedestrian behaviour. This study focuses on investigating the potential of BLE in identifying pedestrian activity in an outdoor linear walkway. We specifically examine the likelihood of detecting pauses in the movement of pedestrians on a linear walkway using the strength of the signals obtained from a BLE device carried by the pedestrian. To accomplish this, a volunteer pedestrian intentionally pauses at selected points on the chosen walkway for varying predetermined intervals. The obtained data was conditioned using a polynomial curve to reduce the impact of anomalous data and was subsequently used to detect flatness in the trend of the signals to identify a pause. This flatness was identified using a sliding window standard deviation (SD) calculation over the curve obtained through polynomial fitting. Our results indicate a strong likelihood of detecting long pauses in a pedestrian's journey.
Detection of Pause in a Pedestrian's Movement on a Linear Walkway using Bluetooth Low Energy Received Signal Strength Indicator
Parmar, Mayank (author) / Kelly, Paula (author) / Berry, Damon (author)
2023-09-24
1421684 byte
Conference paper
Electronic Resource
English
Measurements of pedestrian's ioad using smartphones
| British Library Online Contents | 2017