Fog supported wireless sensor networks for forest fire detection
Author
Amira, Fouad
Advisor
Ulusoy, Özgür
Date
2018-09Publisher
Bilkent University
Language
English
Type
ThesisItem Usage Stats
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Abstract
Fog computing is a new paradigm that aims to extend the concept of cloud computing
to the edge of the network, providing the end users network with extra
storage and processing power. One big contribution of Fog computing is in the
context of Wireless Sensor Networks (WSNs). WSNs consist of cheap, battery
powered and simple processing devices that make it fall short in handling relatively
complex processes.Therefore, applying fog computing to WSNs will fill
the gap between the cloud and the network and by that, it will enable computationally
extensive operations which were earlier possible only at the cloud side.
In our work, we exploit the processing power provided by the Fog to minimize
the power consumption of WSNs for forest fire detection through the use of data
mining techniques. The Fog layer uses the data generated by the network such
as temperature, humidity, rain, etc., to train a model that predicts the probability
of forest fires. Next, the Fog layer uses this model to predict the mode
of operation of the network based on the current condition of the environment.
While a high predicted probability of forest fire results in an increased activity
of the WSN, a low fire probability results in a reduced network activity. As a
result, our proposed model optimizes the energy consumption within the WSN
and improves the detection time of forest fires.
Keywords
Wireless Sensor NetworksForestfire Detection
Forestfire Prediction
Machine Learning
Fog Computing