Forest fire detection system
As we all know, the forest is considered as one of the most important and indispensable resources and Forest fires represent a constant threat to ecological systems, infrastructure and environmental aspects of a community, forest fire detection is a very important issue in the pre-suppression process. This gives rise to the urgent need to detect forest fires as fast as possible. This paper highlights the powerful feature of wireless sensor networks as a potential solution to the challenge of early detection of forest fires. The device presented makes use of various sensors attached and wireless data transmission, to fulfill the task in question. These collected data are transmitted to the small satellite and the satellite transmits the data to the ground station where they are analyzed. The proposed scheme based on wireless sensor networks performs early detection of any fire threat.
A Forest fire is an uncontrolled fire in an area of combustible vegetation that occurs in the countryside or in forest area. India witnessed the most severe forest fires in the recent time during the summer of 1995 in the hills of Uttar Pradesh and Himachal Pradesh. The Forest Survey of India’s data on forest fire attributes around 50% of the forest areas as fire prone. They pose a threat not only to the forest wealth, but also to the entire regime of fauna and flora, seriously disturbing the bio-diversity, ecology and the environment of a region. During summer, when there is no rain for months, the forests become littered with dry senescent leaves and twinges, which could burst into flames ignited by the slightest spark. The Himalayan forests, particularly, Garhwal Himalayas have been burning regularly during the last few summers, with colossal loss of vegetation cover in that region.
Forest is considered as one of the most important and indispensable resource, furthermore, as the protector of the Earth’s ecological balance. However, forest fire, affected by some human uncontrolled behaviour in social activities and abnormal natural factors, occurs occasionally. Forest fire was considered as one of the severest disasters.
In forest fire detection, it is essential to know how fire affects the soil mantle, stems and treetops, as well as how to detect underground fires. The sensor network must cover large areas, distributing high amount of sensing nodes, inexpensive sensors are needed to achieve cost reduction. Video cameras sensitive in visible spectrum based on smoke recognition during the day and fire flame recognition during the night, Infrared thermal imaging cameras based on detection of heat flux from the fire, IR spectrometer which identifies the spectral characteristics of smoke gases, and “Light detection and ranging” system which measures laser light backscattered by smoke particles. Infrared and laser-based systems have higher accuracy than the other systems.
General1y if the infrared level exceeds a predetermined threshold, an alarm 1s sent; but this methodology has some drawbacks that affect detection capability and reliability. Detection capabilities 1s negatively influenced by the fact that often fires are not directly visible from the sensor because during the first phases they grow up in the underbrush and are occluded from the vegetation. On the other hand the smoke (water vapour plus carbon monoxide), copiously produced during the wood drying process, is perfectly transparent in the infrared region (3-7 pm) so it cannot be detected by means of IR sensors. To become directly IR-visible, generally a fire must be at the tree top, so that when it can be detected is already widely extended from the fire starting instant.
Handling uncertainty due to data aggregation and missing information requires space-time synthesis in rigorous formalism. Information granulation is at the heart of rough set theory. Rough set theory offers an attribute reduction algorithm and the dependency metric for feature selection. Meteorological data and images are parameters that change over space and time with relatively high frequency. The change of meteorological data could be recognized in hour scale, and the change of image data, taking into account only information connected to forest fires, in minute scale. Also for the forest fire prediction system, meteorological data history (archive values) is quite important. In order to monitor meteorological parameters and collect imagesin real time, the sensory network has to be established.The most critical issue in a forest fire detection system is immediate response in order to minimize the scale of the disaster. This requires constant surveillance of the forest area. Current medium and large-scale fire surveillance systems do not accomplish timely detection due to low resolution and long period of scan. Therefore, there is a need for a scalable solution that can provide real-time fire detection with high accuracy. We believe that wireless sensor networks can potentially provide such solution. Recent advances in sensor networks support our belief that they make a promising framework for building near real time forest fire detection systems. Currently, sensing modules can sense a variety of phenomena including temperature, relative humidity, and smoke which are all helpful for fire detection systems.
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