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An Alertness-Adjustable Cloud/Fog IoT Solution for Timely Environmental Monitoring Based on Wildfire Risk Forecasting

Author

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  • Athanasios Tsipis

    (Department of Informatics, Ionian University, 49100 Corfu, Greece)

  • Asterios Papamichail

    (Department of Informatics, Ionian University, 49100 Corfu, Greece)

  • Ioannis Angelis

    (Department of Informatics, Ionian University, 49100 Corfu, Greece)

  • George Koufoudakis

    (Department of Informatics, Ionian University, 49100 Corfu, Greece)

  • Georgios Tsoumanis

    (Department of Informatics and Telecommunications, University of Ioannina, 45110 Arta, Greece)

  • Konstantinos Oikonomou

    (Department of Informatics, Ionian University, 49100 Corfu, Greece)

Abstract

Internet of Things (IoT) appliances, especially those realized through wireless sensor networks (WSNs), have been a dominant subject for heavy research in the environmental and agricultural sectors. To address the ever-increasing demands for real-time monitoring and sufficiently handle the growing volumes of raw data, the cloud/fog computing paradigm is deemed a highly promising solution. This paper presents a WSN-based IoT system that seamlessly integrates all aforementioned technologies, having at its core the cloud/fog hybrid network architecture. The system was intensively validated using a demo prototype in the Ionian University facilities, focusing on response time, an important metric of future smart applications. Further, the developed prototype is able to autonomously adjust its sensing behavior based on the criticality of the prevailing environmental conditions, regarding one of the most notable climate hazards, wildfires. Extensive experimentation verified its efficiency and reported on its alertness and highly conforming characteristics considering the use-case scenario of Corfu Island’s 2019 fire risk severity. In all presented cases, it is shown that through fog leveraging it is feasible to contrive significant delay reduction, with high precision and throughput, whilst controlling the energy consumption levels. Finally, a user-driven web interface is highlighted to accompany the system; it is capable of augmenting the data curation and visualization, and offering real-time wildfire risk forecasting based on Chandler’s burning index scoring.

Suggested Citation

  • Athanasios Tsipis & Asterios Papamichail & Ioannis Angelis & George Koufoudakis & Georgios Tsoumanis & Konstantinos Oikonomou, 2020. "An Alertness-Adjustable Cloud/Fog IoT Solution for Timely Environmental Monitoring Based on Wildfire Risk Forecasting," Energies, MDPI, vol. 13(14), pages 1-35, July.
    • Handle: RePEc:gam:jeners:v:13:y:2020:i:14:p:3693-:d:386260
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    References listed on IDEAS

    as
    1. Lee, In & Lee, Kyoochun, 2015. "The Internet of Things (IoT): Applications, investments, and challenges for enterprises," Business Horizons, Elsevier, vol. 58(4), pages 431-440.
    2. Naser Hossein Motlagh & Mahsa Mohammadrezaei & Julian Hunt & Behnam Zakeri, 2020. "Internet of Things (IoT) and the Energy Sector," Energies, MDPI, vol. 13(2), pages 1-27, January.
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    Cited by:

    1. Ahmed Saad & Samy Faddel & Osama Mohammed, 2020. "IoT-Based Digital Twin for Energy Cyber-Physical Systems: Design and Implementation," Energies, MDPI, vol. 13(18), pages 1-21, September.

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