Hybridized Model for Early Detection and Smart Monitoring of Forest Fire
Journal Title: Transactions on Machine Learning and Artificial Intelligence - Year 2017, Vol 5, Issue 4
Abstract
The demand for wireless sensor network technology has been increasingly needed in recent years for several major applications, including environmental monitoring, where nodes deployed in nature detect, process and transfer the environmental data in an autonomous way. However, the performance of early detection of the fire event after data fusion processed by this WSN’s system will be less reliable since the majority of the other nodes do not detect the fire yet (at the beginning of event). That is why the present work is conducted. It proposes an intelligent strategy of data fusion of temperature and humidity sensors hybridized with an intelligent scanning technique. This model will allow the early detection of alarm from the beginning of fire event and guarantee a good monitoring of area state with an ongoing localization of fire zone. The result proves a very good performance in terms of reliability of the early detection and tracking fire propagation.
Authors and Affiliations
Mohammed Anas El abbassi, Abdelilah Jilbab, Abdennaser Bourouhou
Keywords
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- EP ID EP309124
- DOI 10.14738/tmlai.54.3206
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