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The Role Of Iot Data Aggregators For Optimising Object Tracking And Kpi Monitoring

Author

Listed:
  • Robert Idlbek

    (Faculty of Tourism and Rural Development, Croatia)

  • Verica Budimir

    (Faculty of Tourism and Rural Development, Croatia)

Abstract

The Internet of Things (IoT) is an innovative technology that has completely transformed how different devices communicate. This includes sensors, actuators, GPS trackers, and other intelligent equipment. Among its many applications, one of the most important is its role in object tracking and monitoring Key Performance indicators (KPI). These functions are particularly crucial for logistics, manufacturing, agriculture, and retail industries. The main objective of this paper is to explore the significance of IoT data aggregators in optimising these business processes. IoT data aggregators have a vital role to play as they gather, process, and analyse data from multiple IoT devices. This comprehensive approach allows a thorough understanding of the monitored objects and their performance. Moreover, the paper investigates how software designed for data aggregation can enhance the accuracy and efficiency of object tracking. This improvement facilitates real-time tracking of objects indoors and outdoors, analysis of past movements and events, and even predictive maintenance. Additionally, the paper examines how data aggregators contribute to improved KPI monitoring by providing real-time performance metrics. These metrics enable proactive decision-making and enhance operational efficiency. However, addressing some technical challenges associated with object monitoring and data aggregation is essential, such as interoperability and vendor-free technology.

Suggested Citation

  • Robert Idlbek & Verica Budimir, 2023. "The Role Of Iot Data Aggregators For Optimising Object Tracking And Kpi Monitoring," Business Logistics in Modern Management, Josip Juraj Strossmayer University of Osijek, Faculty of Economics, Croatia, vol. 23, pages 451-467.
    • Handle: RePEc:osi:bulimm:v:23:y:2023:p:451-467
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    References listed on IDEAS

    as
    1. Fiorenzo Franceschini & Maurizio Galetto & Domenico Maisano, 2019. "Designing a Performance Measurement Systemperformance measurement system," Management for Professionals, in: Designing Performance Measurement Systems, chapter 5, pages 133-205, Springer.
    2. Gandomi, Amir & Haider, Murtaza, 2015. "Beyond the hype: Big data concepts, methods, and analytics," International Journal of Information Management, Elsevier, vol. 35(2), pages 137-144.
    3. Fiorenzo Franceschini & Maurizio Galetto & Domenico Maisano, 2019. "Designing Performance Measurement Systems," Management for Professionals, Springer, number 978-3-030-01192-5, December.
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