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Two-Step k -means Clustering Based Information Entropy for Detecting Environmental Barriers Using Wearable Sensor

Author

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  • Bogyeong Lee

    (Department of Architectural Engineering, Dankook University, 152 Jukjeon-ro, Suji-gu, Yongin-si 16890, Korea)

  • Hyunsoo Kim

    (Department of Architectural Engineering, Dankook University, 152 Jukjeon-ro, Suji-gu, Yongin-si 16890, Korea)

Abstract

Walking is the most basic means of transportation. Therefore, continuous management of the walking environment is very important. In particular, the identification of environmental barriers that can impede walkability is the first step in improving the pedestrian experience. Current practices for identifying environmental barriers (e.g., expert investigation and survey) are time-consuming and require additional human resources. Hence, we have developed a method to identify environmental barriers based on information entropy considering that every individual behaves differently in the presence of external stimuli. The behavioral data of the gait process were recorded for 64 participants using a wearable sensor. Additionally, the data were classified into seven gait types using two-step k -means clustering. It was observed that the classified gaits create a probability distribution for each location to calculate information entropy. The values of calculated information entropy showed a high correlation in the presence or absence of environmental barriers. The results obtained facilitated the continuous monitoring of environmental barriers generated in a walking environment.

Suggested Citation

  • Bogyeong Lee & Hyunsoo Kim, 2022. "Two-Step k -means Clustering Based Information Entropy for Detecting Environmental Barriers Using Wearable Sensor," IJERPH, MDPI, vol. 19(2), pages 1-16, January.
    • Handle: RePEc:gam:jijerp:v:19:y:2022:i:2:p:704-:d:720570
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    References listed on IDEAS

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    1. Bradley Bereitschaft, 2018. "Walk Score® versus residents’ perceptions of walkability in Omaha, NE," Journal of Urbanism: International Research on Placemaking and Urban Sustainability, Taylor & Francis Journals, vol. 11(4), pages 412-435, October.
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    4. Bogyeong Lee & Sungjoo Hwang & Hyunsoo Kim, 2021. "The Feasibility of Information-Entropy-Based Behavioral Analysis for Detecting Environmental Barriers," IJERPH, MDPI, vol. 18(21), pages 1-14, November.
    5. Jihwan Yoon & Jaeyoul Chun & Hyunsoo Kim, 2020. "Investigating the Relation between Walkability and the Changes in Pedestrian Policy through Wearable Sensing," Sustainability, MDPI, vol. 12(24), pages 1-19, December.
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