• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.6
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• pp.1506-1514
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• 2015

In this paper, we proposed a forest fires prediction and detection system. It could provide a situation of fire prediction and detection methods using context awareness sensor. A fire occurs wide range of sensing a fire in a single camera sensor, it is difficult to detect the occurrence of a fire. In this paper, we propose an algorithm for real-time by using a temperature sensor, humidity, Co2, the flame presence information acquired and comparing the data based on multiple conditions, analyze and determine the weighting according to fire in complex situations. In addition, it is possible to differential management of intensive fire detection and prediction for required dividing the state of fire zone. Therefore we propose an algorithm to determine the prediction and detection from the fire parameters as an temperature, humidity, Co2 and the flame in real-time by using a context awareness sensor and also suggest algorithm that provide the path of fire diffusion and service the secure safety zone prediction.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.11 no.5
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• pp.203-210
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• 2011

The current sensor network analyzes the data collected by the sensing of fixed sensor nodes and provides a service. However, this method cannot actively handle the state and the change in the position of people, 'the target for sensing and the change in the environment', including home automation, building automation and real-time road & weather information, and healthcare environment, etc. To support a dynamic situation which is appropriate for an individual in this diverse environment, it is necessary to provide actively differentiated specific information according to the movement of people and the changes in the environment. In this study, a individualized sensor mobile agent middleware which provides the individualized information (the location of fire incidence and the trace for the path of spread), has been realized through the sensor network environment constructed by the installation of wireless sensor nodes mounted with mobile agent middlewares in buildings.