False alarm reduction in forest fires detection with low-cost commercial sensors

2011 ◽  
pp. 75-86
Author(s):  
Andrea Losso ◽  
Lorenzo Corgnati ◽  
Giovanni Perona
1997 ◽  
Vol 30 (7) ◽  
pp. 275-280
Author(s):  
A. Ollero ◽  
B.C. Arrúe ◽  
J.R. Martinez ◽  
J.J. Murillo

The frequency of the forest fires that have occurred in the different parts of the world, In recent decades significant population problems and causing the death if the wild animals as the impact of these fires extend beyond the destruction of the natural habitats. The proliferation of the Internet of Things industry, resolutions for initial fire detection should be developed. The valuation of the fire risk of an area and communication of this realities to the population could reduce the amount of fires originated by accident or due to carelessness of the public user. This paper proposes a low-cost network based on NXP Rapid IOT kit and Long Range (Lora) technology to autonomously estimate the level of fire risk in the forest. The system comprises of NXP Rapid IOT kit which humidity, air quality and detection of the tree fall. The data from each node stored and processed in a in a web server or the mobile application that sendsthe recorded data to a web server for graphical conception of collected data.


2019 ◽  
Vol 2019 ◽  
pp. 1-15 ◽  
Author(s):  
Mohammed Sadek ◽  
Xuxiang Li

Natural hazards are indeed counted as the most critical challenges facing our world, represented in floods, earthquakes, volcanoes, hurricanes, and forest fires. Among these natural hazards, the flash flood is regarded the most frequent. In this work, we utilized two Sentinel-2 satellite images, before and after the flash flood, SRTM and photos captured by using a helicopter. This paper aims at three prime objectives. Firstly, the flood influence is determined on the city of Ras Ghareb, Egypt, based on analyzing free satellite data (Sentinel-2 images). Secondly, fuzzy the analytical hierarchy process (FAHP) method and a geographical information system (GIS) are integrated for flood risk analysis and evaluation in the flood-prone area. Finally, such a flood vulnerability map is used as an index to assist the decision-makers prepare for probable flooding. FAHP is preferable as it can cater to the uncertainties in data and analysis. As a result, FAHP is appropriate to determine the flood-vulnerable area in cities especially due to the matching with the most destroyed areas identified by the change detection between the two Sentinel-2 images. Then, the decision-maker can depend on Sentinel-2 images to estimate the flood influence through a regional scale or applying the FAHP on cities susceptible to flash floods in case of unavailable satellite images to contribute in establishing an early warning system enough to the evacuation of the risky areas.


2019 ◽  
Author(s):  
Alexandre Campos ◽  
Ricardo Molin ◽  
Mats Pettersson ◽  
Renato Machado

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