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

Athanasios Tsipis, Asterios Papamichail, Ioannis Angelis, George Koufoudakis, Georgios Tsoumanis and Konstantinos Oikonomou
Additional contact information
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

Energies, 2020, vol. 13, issue 14, 1-35

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.

Keywords: environmental monitoring; precision agriculture; Internet of Things; wireless sensor networks; cloud/fog computing; fire risk forecasting; Chandler burning index; wildfires (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
https://www.mdpi.com/1996-1073/13/14/3693/pdf (application/pdf)
https://www.mdpi.com/1996-1073/13/14/3693/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jeners:v:13:y:2020:i:14:p:3693-:d:386260

Access Statistics for this article

Energies is currently edited by Ms. Agatha Cao

More articles in Energies from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().