Enhancing Wildfire Risk Management Through Sensor-Based AI Integration in Social IoT Frameworks

The search for solutions aimed at environmental protection is still an open and increasingly topical challenge. Information and communication technology is playing an increasing role in the research and development of innovative solutions. In this paper, a widespread and scalable solution for forest fire detection based on LoRa technology, a wireless sensor network (WSN), and the development and training of a feed-forward neural network is proposed. Data analysis and alert management are handled through the Social Internet of Things (SIoT) paradigm. The proposed method is validated on a real forest scenario and provides a validated configuration for the early detection of forest fires.

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Publication Details

Published
2024-12-11
DOI
https://doi.org/10.3390/engproc2024078004
Citations
2
Primary Topic
Fire Detection and Safety Systems
Type
article
Field-Weighted Citation Impact
0.73
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article

Enhancing Wildfire Risk Management Through Sensor-Based AI Integration in Social IoT Frameworks

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2 citations
Fire Detection and Safety Systems
0.73
article

Enhancing Wildfire Risk Management Through Sensor-Based AI Integration in Social IoT Frameworks

Matteo Anedda, Mariella Sole, Daniele Giusto, Martina Putzu, A Ledda, Francesco Carta, Daniele Loru, Alessio Chirigu
article en
2 citations

Abstract

The search for solutions aimed at environmental protection is still an open and increasingly topical challenge. Information and communication technology is playing an increasing role in the research and development of innovative solutions. In this paper, a widespread and scalable solution for forest fire detection based on LoRa technology, a wireless sensor network (WSN), and the development and training of a feed-forward neural network is proposed. Data analysis and alert management are handled through the Social Internet of Things (SIoT) paradigm. The proposed method is validated on a real forest scenario and provides a validated configuration for the early detection of forest fires.

University of Cagliari (IT)
Climate action
Openalex Percentile: Top 28%
Fire Detection and Safety Systems
0.73
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