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Exploring the use of IoT Data for Heightened Situational Awareness in Centralised Monitoring Control Rooms

Author

Listed:
  • Flávio Horita

    (Federal University of ABC
    University of Warwick)

  • João Baptista

    (University of Warwick)

  • João Porto Albuquerque

    (University of Warwick)

Abstract

This paper traces the expansion of a network of IoT sensors to improve the effectiveness of a centralised control room in Brazil in anticipating natural hazards. This centralised model relies on using IoT data by highly qualified experts replacing previous smaller local structures. We draw on the notion of Situational Awareness to carry out the study. Results show that although the operators were not always familiar with the characteristics of locations, the use of IoT data heightened their situational awareness in the centralised control room by improving perception and comprehension. However, they still relied on local knowledge and learned experiences to support projection and anticipation of risks. The study highlights that although data analytics systems are capable of expanding operators’ perception of local elements, they must be complemented by local richer forms of information, needed to anticipate risks and make critical decisions with major impact on local population.

Suggested Citation

  • Flávio Horita & João Baptista & João Porto Albuquerque, 2023. "Exploring the use of IoT Data for Heightened Situational Awareness in Centralised Monitoring Control Rooms," Information Systems Frontiers, Springer, vol. 25(1), pages 275-290, February.
  • Handle: RePEc:spr:infosf:v:25:y:2023:i:1:d:10.1007_s10796-020-10075-8
    DOI: 10.1007/s10796-020-10075-8
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    References listed on IDEAS

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    1. Judd Cramer & Alan B. Krueger, 2016. "Disruptive Change in the Taxi Business: The Case of Uber," American Economic Review, American Economic Association, vol. 106(5), pages 177-182, May.
    2. Dimiter G. Velev, 2011. "Internet of Things – Analysis and Challenges," Economic Alternatives, University of National and World Economy, Sofia, Bulgaria, issue 2, pages 99-109, July.
    3. J. Piet Hausberg & Kirsten Liere-Netheler & Sven Packmohr & Stefanie Pakura & Kristin Vogelsang, 2019. "Research streams on digital transformation from a holistic business perspective: a systematic literature review and citation network analysis," Journal of Business Economics, Springer, vol. 89(8), pages 931-963, December.
    4. Lo, Fang-Yi & Campos, Nayara, 2018. "Blending Internet-of-Things (IoT) solutions into relationship marketing strategies," Technological Forecasting and Social Change, Elsevier, vol. 137(C), pages 10-18.
    5. Yang, L. & Yang, S.H. & Plotnick, L., 2013. "How the internet of things technology enhances emergency response operations," Technological Forecasting and Social Change, Elsevier, vol. 80(9), pages 1854-1867.
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