Assessing the Efficacy of IoT-based Forest Fire Detection: a Practical Use Case

TL;DR

This paper evaluates the practical effectiveness of a 6G-enabled IoT-based forest fire detection system using real-world data, aiming to develop guidelines for future deployment in rural areas.

Contribution

It presents a case study analyzing real sensor data to assess the efficacy of IoT-based fire detection, providing initial insights and practical guidelines for system design.

Findings

Preliminary evidence of IoT sensor effectiveness in fire detection

Identification of challenges in distributed sensor network deployment

Guidelines for designing practical 6G-enabled fire detection systems

Abstract

The implementation of early warning mechanisms that can be used to detect forest fires in rural areas is essential to mitigate their deleterious effects, in particular by notifying local fire authorities to mount timely emergency responses. 6G-enabled Internet of Things (IoT) infrastructures are promising technological developments in that direction. However, in practice, the ability to detect forest fires in an effective way using distributed sensor nodes is challenging to achieve. In this short paper, we exemplify this challenge based on a case study that uses real data collected from the Low-Cost Internet of Things Sensor of Haze Air Quality Disasters in Communities in Thailand and Southeast Asia (SEA-HAZEMON) platform. The work is a preliminary step towards assessing the efficacy of a real-life fire detection system based on distributed sensor nodes. More generally, the objective is to develop a set of practical guidelines for the design of a 6G-enabled IoT-based fire detection mechanism.