Forest fire risk monitoring using fuzzy logic and IoT technology - Sahour, Abdelhakim; Boumehrez, Farouk; Maamri, Fouzia; Djellab, Hanane; Abdelali, Bakhouche (IAES Indonesian Section, 2024)
Forest fire is one of the leading causes of ecological damage and environmental problems. This work aims to develop a forest fire risk monitoring system in which an artificial intelligence technique, fuzzy logic, has been used to determine the forest method risk (temperature, relative humidity, and wind speed). Fuzzy set theory implements categories or groupings of data whose boundaries are not clearly defined (i.e. fuzzy), consisting of rule bases, membership functions, and inference methods. We also use wireless sensor networks (WSN) and Internet of Things (IoT) technologies. In order to collect environmental information through WSN based environmental sensors, the collected information is transmitted to a database on a server through an Internet connection. Users can monitor the saved data using an internet browser in each whey. This provides the ability to analyze detailed data and then take the necessary precautions to protect threatened forests.