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The Feasibility of Information-Entropy-Based Behavioral Analysis for Detecting Environmental Barriers

Author

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  • Bogyeong Lee

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

  • Sungjoo Hwang

    (Department of Architectural and Urban Systems Engineering, Ewha Womans University, 52 Ewhayeodae-Gil, Seodaemun-Gu, Seoul 03760, Korea)

  • Hyunsoo Kim

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

Abstract

The enhancement of physical activity is highly correlated with the conditions of the built environment. Walking is considered to be a fundamental daily physical activity, which requires an appropriate environment. Therefore, the barriers of the built environment should be identified and addressed. Barriers can act as external stimuli for pedestrians, so pedestrians may diversely respond to them. Based on this consideration, this study examines the feasibility of information-entropy-based behavioral analysis for the detection of environmental barriers. The physical responses of pedestrians were collected using an inertial measurement unit (IMU) sensor in a smartphone. After the acquired data were converted to behavioral probability distributions, the information entropy of each grid cell was calculated. The grid cells whereby the participants indicated that environmental barriers were present yielded relatively high information entropy values. The findings of this study will facilitate the design of more pedestrian-friendly environments and the development of diverse approaches that utilize citizens for monitoring the built environment.

Suggested Citation

  • 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.
    • Handle: RePEc:gam:jijerp:v:18:y:2021:i:21:p:11727-:d:674709
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    References listed on IDEAS

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    1. Andrew F. Clark & Darren M. Scott, 2016. "Barriers to Walking: An Investigation of Adults in Hamilton (Ontario, Canada)," IJERPH, MDPI, vol. 13(2), pages 1-12, January.
    2. Zihao Wen & Hui Zhang & Ronghui Zhang, 2021. "Safety-Critical Event Identification on Mountain Roads for Traffic Safety and Environmental Protection Using Support Vector Machine with Information Entropy," Sustainability, MDPI, vol. 13(8), pages 1-15, April.
    3. 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.
    4. Arlie Adkins & Jennifer Dill & Gretchen Luhr & Margaret Neal, 2012. "Unpacking Walkability: Testing the Influence of Urban Design Features on Perceptions of Walking Environment Attractiveness," Journal of Urban Design, Taylor & Francis Journals, vol. 17(4), pages 499-510.
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    1. 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.

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