TY - GEN
T1 - Detection of Pause in a Pedestrian's Movement on a Linear Walkway using Bluetooth Low Energy Received Signal Strength Indicator
AU - Parmar, Mayank
AU - Kelly, Paula
AU - Berry, Damon
N1 - Publisher Copyright:
© 2023 IEEE.
PY - 2023/9/24
Y1 - 2023/9/24
N2 - 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.
AB - 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.
KW - Bluetooth Low Energy
KW - Privacy Preservation
KW - Walking
UR - http://www.scopus.com/inward/record.url?scp=85178349387&partnerID=8YFLogxK
U2 - 10.1109/ISC257844.2023.10293694
DO - 10.1109/ISC257844.2023.10293694
M3 - Conference contribution
AN - SCOPUS:85178349387
T3 - Proceedings of 2023 IEEE International Smart Cities Conference, ISC2 2023
BT - Proceedings of 2023 IEEE International Smart Cities Conference, ISC2 2023
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 9th IEEE International Smart Cities Conference, ISC2 2023
Y2 - 24 September 2023 through 27 September 2023
ER -
