Field Experiment Testbed for Forest Fire Detection using Wireless Multimedia Sensor Network

Author(s): Houache Noureddine*, Kechar Bouabdellah.

Journal Name: International Journal of Sensors, Wireless Communications and Control

Volume 10 , Issue 1 , 2020

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Abstract:

Forest fire disasters have arisen each year due to a number of factors. The main interest of the authorities is to fight against these fires as early as possible with a minimum of damage, by exploiting recent technologies suitable for this field. In this paper, we present the design and the implementation of a forest fire detection system based on the Wireless Multimedia Sensor Networks (WMSN) technology applied to our region (M'sila forest, Oran city - Algeria) using a field experiment testbed with low cost hardware and software. In our previous study, the designed system detects the fire using a mono modal approach (the sensed data was scalar in nature such as the temperature and humidity). In this work, we enhanced this system by collecting, in addition, richer information sources using cameras as data sources (by capturing images) to eliminate the false alarms which present the main weakness of the first system. We call this new system as Multimedia Forest Fire System (M2FS). Field experiments that we have carried out using the testbed under different scenarios by evaluating the image compression, time constraint and energy consumption, allowed us to validate our chosen technology (Arduino mote) for any application (scalar or multimedia), and also revealed the supremacy of the multimodal approach to mitigate efficiently false alarms.

Keywords: Energy consumption, environmental monitoring, forest fire detection, multimodal approach, testbed, wireless multimedia sensor networks.

[1]
Kechar B, Houache B, Sekhri L. Using wireless sensor networks for reliable forest fires detection.The 3rd Int Conf Sustainable Energy Info Tech SEIT, Canada, June 24, 2013.
[3]
Mohamed A. Problématique des feux de forêts en AlgerieInt Course on management climate risk, 2012. Available from:. https: //rs.umc.edu.dz/umc/s%C3%A9menaire/cours%20Internatio nal%20Risques%20Majeurs%20-nov.2012/ABBAS%20M.pdf
[4]
Statistics related to forest fires [cited: 23 August 2018] available from: https: //www.planetoscope.com/forets/903-hectares-de-terres-detruits-dans-le-monde-par-des-incendies.html [accessed 10 June 2018].
[5]
WWF: The leading organization in wildlife conservation and endangered species [cited: 23 August 2018]. Available from: https://www.worldwildlife.org/ [accessed 10 june2018]
[6]
Vijayalakshmi SR, Muruganand S. Real time monitoring of wireless fire detection node Int Conf Emerging Trends Engr (ICETEST- 2016), India, July 9,. 2016.
[7]
Ganesh U, Anand M, Arun S, Dinesh M, Gunaseelan P, Karthik R. Forest fire detection using optimized solar - powered zigbee wireless sensor networks. Int J Sci Eng Res 2013; 4: 586-96.
[8]
Cruz H, Eckert M, Meneses J, Martínez J. Efficient forest fire detection index for application in Unmanned Aerial Systems (UASs). Sensors 2016; 16: 893.
[9]
Erdelj M, Krol M, Natalizio E. Wireless sensor networks and multi-UAV systems for natural disaster management. Comput Netw 2017; 124: 72-86.
[10]
Dutta M, Bhowmik S, Giri C. Fuzzy logic based implementation for forest fire detection using wireless sensor network. The 2nd Int Conf Adv Comput (ICACNI-2014), Switzerland: Springer. 2014.
[11]
Roy S, Bose R, Sarddar D. Self-servicing energy efficient routing strategy for smart forest. Braz J Sci Technol 2016; 3: 13.
[12]
Alkhatib AA. Sub-network coverage method as an efficient method of wireless sensor networks for forest fire detection. Proc Int Conf Internet Things Cloud Comput Cambridge, United Kingdom, ACM. 2016 March; 22-3.
[13]
Gao DM, Yin XF, Liu YF. Prediction of forest fire using wireless sensor network. J Trop For Sci 2015; 27: 342-50.
[14]
Kosucu B, Irgan K, Kucuk G, Baydere S. FireSenseTB: A wireless sensor networks testbed for forest fire detection. Proc Int Conf Wireless Commun Mobile Comput Connect World Wirelessly (IWCMC) Leipzig, Germany: ACM. 2009; June 21-24.
[15]
Cantuna JG, Bastidas D, Solorzano S, Clairand JM. Design and implementation of a wireless sensor network to detect forest fires. IEEE 4th Int Conf eDemoc eGovernment (ICEDEG), Ecuador. 2017 April ; 19-21.
[16]
Ramírez AD, Tafoya LA, Atempa JA, Mejía-Alvarez P. Wireless sensor networks and fusion information methods for forest fire detection The 2012 Iberoamerican Conf Electron Engr Comp Sci. 2012.
[17]
Bhosle AS, Gavhane LM. Forest disaster management with wireless sensor network. IEEE Int Conf Electr, Electron, Optimiz Tech (ICEEOT) Chennai, India, IEEE. 2016; March 3-5.
[18]
Documentation sent by the Meteorological Service of Canada [Obtained by post, March 2010].
[19]
Dowdy AJ, Mills GA, Finkele K, Groot WD. Australian fire weather as represented by the McArthur forest fire danger index and the Canadian forest fire weather index. The Centre for Australian Weather and Climate Research a partnership between CSIRO and the Bureau of Meteorology, ISBN: 9781921605185. 2009.
[20]
Son B, Her Y, Kim J. A design and implementation of forest-fires surveillance system based on wireless sensor networks for South Korea mountains. Int J Comp Sci Netw Secur 2006; 6: 124-30.
[21]
Zululand fire protection association [homepage on the Internet]. Kwambonambi3915 South Africa 2015.[cited: 10-06-2018] available from: . http: //zfpa.co.za
[22]
Sharples JJ, McRae RHD, Weber RO, Gill AM. A simple index for assessing fire danger rating. J Environmental Model Software 2009; 4: 764-74.
[23]
Deutschland Forest fire index [homepage on the Internet]. A public institution with partial legal capacity under the Federal Ministry of transport and digital infrastructure [cited:10-06-2018], available from: https: //www.dwd.de/DE/leistungen/waldbrandgef/waldbrand gef.html
[24]
Csontos P, Cseresnyés I. Fire-risk evaluation of Austrian pine stands in Hungary-effects of drought conditions and slope aspect on fire spread and fire behavior. Carpath J Earth Environ Sci 2015; 10: 247-54.
[25]
Makkaoui L. Compression d’images dans les réseaux de capteurs sans filAutomatic: Signal Process Comp Engr from IAEM Lorraine, 2012.Available from: . https: //tel.archives-ouvertes.fr/tel-00795503
[26]
Mammeri A. Compression et transmission d’images avec énergie minimale Application aux capteurs sans filDepartment of Electrical Engr Comp Engineering Sherbrooke Canada, 2010.Available from:. https: //savoirs.usherbrooke.ca/handle/11143/5800
[27]
Faundez C. Transmission d’images sur les réseaux de capteurs sans fil sous la contrainte de l’énergie. Automatic, Signal Process Comp Engr from Henri Poincaré, Nancy 1 university, 2009.Available from :. https: //tel.archives-ouvertes.fr/tel-00417505
[28]
Pham C. Communication performances of IEEE 802.15.4 wireless sensor motes for data-intensive applications: A comparison of WaspMote, Arduino MEGA, TelosB, MicaZ and iMote2 for image surveillance. J Netw Comput Appl 2014; 46: 48-59.
[29]
Kelhä V, Herland EA, Lohi A. Satellite based forest fire detection and automatic alert system-pilot experiment. Early Warn Syst Natural Disast Reduct, Springer Ed: Germany . 2003.
[30]
Trapeze integration method [homepage on the Internet] Wikimedia Foundation, Inc [updated 10 oct 2018; cited 24 oct 2018]. Available from: https: //en.wikipedia.org/wiki/Trapezoidal_rule
[31]
Simpson integration method web page. [homepage on the Internet] Wikimedia Foundation, Inc [updated 16 oct 2018; cited 24 oct 2018]. Available from: https: //en.wikipedia.org/wiki/Simpson%27s_rule.


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Article Details

VOLUME: 10
ISSUE: 1
Year: 2020
Page: [3 - 14]
Pages: 12
DOI: 10.2174/2210327909666190219120432
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