IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v13y2021i17p9993-d630216.html
   My bibliography  Save this article

Built Environment Characteristics, Daily Travel, and Biometric Readings: Creation of an Experimental Tool Based on a Smartwatch Platform

Author

Listed:
  • Robin C. O. Palmberg

    (Integrated Transport Research Lab., School of Industrial Technology and Management, KTH Royal Institute of Technology, 100 44 Stockholm, Sweden)

  • Yusak O. Susilo

    (Institute for Transport Studies, Department of Landscape, Spatial, and Infrastructure Sciences, University of Natural Resources and Life Sciences (BOKU), 1090 Vienna, Austria)

  • Győző Gidófalvi

    (Integrated Transport Research Lab., School of Industrial Technology and Management, KTH Royal Institute of Technology, 100 44 Stockholm, Sweden
    Division of Geoinformatics, Department of Urban Planning and Environment, School of Architecture and The Built Environment, KTH Royal Institute of Technology, 100 44 Stockholm, Sweden)

  • Fatemeh Naqavi

    (Division of Systems Analysis and Economics, Department of Urban Planning and Environment, School of Architecture and The Built Environment, KTH Royal Institute of Technology, 100 44 Stockholm, Sweden)

Abstract

Travel surveys can uncover information regarding travel behaviour, needs, and more. Collected information is utilised to make choices when reorganising or planning built environments. Over the years, methods for conducting travel surveys have changed from interviews and forms to automated travel diaries in order to monitor trips made by travellers. With the fast progression of technological advancements, new possibilities for operationalising such travel diaries can be implemented, changing from utilising mobile to wearable devices. Wearable devices are often equipped with sensors which collect continuous biometric data from sources that are not reachable from standard mobile devices. Data collected through wearable devices range from heart rate and blood pressure to temperature and perspiration. This advancement opens new possible layers of information in the collection of travel data. Such biometric data can be used to derive psychophysiological conditions related to cognitive load, which can uncover in-depth knowledge regarding stress and emotions. This paper aims to explore the possibilities of data analysis on the data collected through a software combining travel survey data, such as position and time, with heartrate, to gain knowledge of the implications of such data. The knowledge about the implications of spatial configurations can be used to create more accessible environments.

Suggested Citation

  • Robin C. O. Palmberg & Yusak O. Susilo & Győző Gidófalvi & Fatemeh Naqavi, 2021. "Built Environment Characteristics, Daily Travel, and Biometric Readings: Creation of an Experimental Tool Based on a Smartwatch Platform," Sustainability, MDPI, vol. 13(17), pages 1-21, September.
    • Handle: RePEc:gam:jsusta:v:13:y:2021:i:17:p:9993-:d:630216
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/13/17/9993/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/13/17/9993/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Lai, T. L. & Robbins, Herbert & Wei, C. Z., 1979. "Strong consistency of least squares estimates in multiple regression II," Journal of Multivariate Analysis, Elsevier, vol. 9(3), pages 343-361, September.
    2. Kay Axhausen & Andrea Zimmermann & Stefan Schönfelder & Guido Rindsfüser & Thomas Haupt, 2002. "Observing the rhythms of daily life: A six-week travel diary," Transportation, Springer, vol. 29(2), pages 95-124, May.
    3. Liu, Chengxi & Susilo, Yusak O. & Dharmowijoyo, Dimas B.E., 2018. "Investigating intra-household interactions between individuals' time and space constraints," Journal of Transport Geography, Elsevier, vol. 73(C), pages 108-119.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Edmond Daramy-Williams & Jillian Anable & Susan Grant-Muller, 2019. "Car Use: Intentional, Habitual, or Both? Insights from Anscombe and the Mobility Biography Literature," Sustainability, MDPI, vol. 11(24), pages 1-17, December.
    2. Heinen, Eva & Chatterjee, Kiron, 2015. "The same mode again? An exploration of mode choice variability in Great Britain using the National Travel Survey," Transportation Research Part A: Policy and Practice, Elsevier, vol. 78(C), pages 266-282.
    3. Wang, Xiaoxi & Zhang, Yaojun & Yu, Danlin & Qi, Jinghan & Li, Shujing, 2022. "Investigating the spatiotemporal pattern of urban vibrancy and its determinants: Spatial big data analyses in Beijing, China," Land Use Policy, Elsevier, vol. 119(C).
    4. Makoto Chikaraishi & Akimasa Fujiwara & Junyi Zhang & Kay Axhausen, 2011. "Identifying variations and co-variations in discrete choice models," Transportation, Springer, vol. 38(6), pages 993-1016, November.
    5. Benjamin Motte-Baumvol & Julie Fen-Chong & Olivier Bonin, 2023. "Immobility in a weekly mobility routine: studying the links between mobile and immobile days for employees and retirees," Transportation, Springer, vol. 50(5), pages 1723-1742, October.
    6. R. M. Balan & Ioana Schiopu-Kratina, 2004. "Asymptotic Results with Generalized Estimating Equations for Longitudinal data II," RePAd Working Paper Series lrsp-TRS398, Département des sciences administratives, UQO.
    7. He, Brian Yueshuai & Zhou, Jinkai & Ma, Ziyi & Wang, Ding & Sha, Di & Lee, Mina & Chow, Joseph Y.J. & Ozbay, Kaan, 2021. "A validated multi-agent simulation test bed to evaluate congestion pricing policies on population segments by time-of-day in New York City," Transport Policy, Elsevier, vol. 101(C), pages 145-161.
    8. Fabian Märki & David Charypar & Kay Axhausen, 2014. "Agent-based model for continuous activity planning with an open planning horizon," Transportation, Springer, vol. 41(4), pages 905-922, July.
    9. Jariyasunant, Jerald & Carrel, Andre & Ekambaram, Venkatesan & Gaker, DJ & Kote, Thejovardhana & Sengupta, Raja & Walker, Joan L., 2011. "The Quantified Traveler: Using personal travel data to promote sustainable transport behavior," University of California Transportation Center, Working Papers qt9jg0p1rj, University of California Transportation Center.
    10. Zhai, Wei & Bai, Xueyin & Peng, Zhong-ren & Gu, Chaolin, 2019. "From edit distance to augmented space-time-weighted edit distance: Detecting and clustering patterns of human activities in Puget Sound region," Journal of Transport Geography, Elsevier, vol. 78(C), pages 41-55.
    11. Andre De Palma & Fay Dunkerley & Stef Proost, 2010. "Trip Chaining: Who Wins Who Loses?," Journal of Economics & Management Strategy, Wiley Blackwell, vol. 19(1), pages 223-258, March.
    12. Jiri Zuzanek, 2009. "Time use research in Canada – History,critique, perspectives," electronic International Journal of Time Use Research, Research Institute on Professions (Forschungsinstitut Freie Berufe (FFB)) and The International Association for Time Use Research (IATUR), vol. 6(2), pages 178-192, September.
    13. María Yáñez & Patricio Mansilla & Juan de Ortúzar, 2010. "The Santiago Panel: measuring the effects of implementing Transantiago," Transportation, Springer, vol. 37(1), pages 125-149, January.
    14. Ahmad Termida, Nursitihazlin & Susilo, Yusak O. & Franklin, Joel P., 2016. "Observing dynamic behavioural responses due to the extension of a tram line by using panel survey," Transportation Research Part A: Policy and Practice, Elsevier, vol. 86(C), pages 78-95.
    15. Marki, Fabian & Charypar, David & Axhausen, Kay, 2014. "Location choice for a continuous simulation of long periods under changing conditions," The Journal of Transport and Land Use, Center for Transportation Studies, University of Minnesota, vol. 7(2), pages 1-18.
    16. Norbert Christopeit & Michael Massmann, 2013. "A Note on an Estimation Problem in Models with Adaptive Learning," Tinbergen Institute Discussion Papers 13-151/III, Tinbergen Institute.
    17. William Michelson, 2009. "Variations in the rational use of time – The travel pulse of commutes between home and job," electronic International Journal of Time Use Research, Research Institute on Professions (Forschungsinstitut Freie Berufe (FFB)) and The International Association for Time Use Research (IATUR), vol. 6(2), pages 269-285, September.
    18. Echeverría, Lucía & Gimenez-Nadal, J. Ignacio & Molina, José Alberto, 2021. "Carpooling: User profiles and well-being," Nülan. Deposited Documents 3568, Universidad Nacional de Mar del Plata, Facultad de Ciencias Económicas y Sociales, Centro de Documentación.
    19. Tsoleridis, Panagiotis & Choudhury, Charisma F. & Hess, Stephane, 2022. "Utilising activity space concepts to sampling of alternatives for mode and destination choice modelling of discretionary activities," Journal of choice modelling, Elsevier, vol. 42(C).
    20. Benjamin Motte-Baumvol & Olivier Bonin & Carlos David Nassi & Leslie Belton-Chevallier, 2016. "Barriers and (im)mobility in Rio de Janeiro," Urban Studies, Urban Studies Journal Limited, vol. 53(14), pages 2956-2972, November.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jsusta:v:13:y:2021:i:17:p:9993-:d:630216. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.