A review on early forest fire detection using IoT-enabled WSN
Amira Sairi, Said Labed, Badreddine Miles, Akram Kout
Abstract
Forest fires start in natural settings such as forests and spread unchecked, destroying millions of hectares of land worldwide and causing economic and environmental destruction in addition to human deaths. Traditional techniques of forest fire surveillance and detection include personnel to monitor the environment, which can be unsafe and costly in terms of the human resources required. In this field, to reduce such losses, technology that can detect any fire hazard in real time is required. Many techniques are used, like the Internet of Things (IoT), wireless sensor networks (WSN) and drone systems. This article provides a thorough examination of the various indications used to identify and detect forest fires. Also included are the communication protocols employed, as well as the various artificial intelligence techniques. Furthermore, this study summarizes a review conducted to identify directions and research issues in forest fire control and discusses the benefits and drawbacks of this strategy in order to aid in future studies aimed at the creation of early-warning systems for fire detection.