Preventing forest fires using a wireless sensor network L. (2020): Preventing forest fires using a wireless sensor network. J. For. Sci., 66: 97-104.
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Forest fire is a natural phenomenon in many ecosystems across the world. The forecasting of fire danger conditions resembles one of the most important parts in forest fire management. A ZigBee-based wireless sensor network was proposed for monitoring fire danger and predicting the behaviour of fire after occurrence. This technique is intended for real-time operation, given the urgent need for forest protection against fires. The architecture of a wireless sensor network for forest fire detection is described. From the information collected by the system, decisions on firefighting or fire prevention can be made more quickly by the relevant government departments. We believe that by making the sensor network able to reconfigure rapidly in response to changes in the local conditions upon which the network is dependent, we will generate an adaptable weather monitoring and fire detection system.

Abdollahi M., Islam T., Gupta A., Hassan Q. (2018): An advanced forest fire danger forecasting system: Integration of remote sensing and historical sources of ignition data. Remote Sensing, 10: 923.
Abdullah S., Bertalan S., Masar S., Coskun A., Kale I. (2017): A wireless sensor network for early forest fire detection and monitoring as a decision factor in the context of a complex integrated emergency response system. In: 2017 IEEE Workshop on Environmental, Energy, and Structural Monitoring Systems (EESMS), IEEE: 1–5.
Chowdhury E.H., Hassan Q.K. (2015): Operational perspective of remote sensing-based forest fire danger forecasting systems. ISPRS Journal of Photogrammetry and Remote Sensing, 104: 224–236.
Coen J.L., Schroeder W. (2017): Coupled weather-fire modeling: from research to operational forecasting. Fire Management Today, 75: 39–45.
Dihissou A., Diallo A., Le Thuc P., Staraj R. (2017): Technique to increase directivity of a reconfigurable array antenna for wireless sensor network. In 2017 11th European Conference on Antennas and Propagation (EUCAP), IEEE: 606–610.
Jameii S.M., Faez K., Dehghan M. (2015): Multiobjective optimization for topology and coverage control in wireless sensor networks. International Journal of Distributed Sensor Networks, 11: 363815.
Javadnejad F., Gillins D.T., Parrish C. E., Slocum R.K. (2019): A photogrammetric approach to fusing natural colour and thermal infrared UAS imagery in 3D point cloud generation. International Journal of Remote Sensing, 41: 211–237.
Khamukhin A.A., Bertoldo S. (2016): Spectral analysis of forest fire noise for early detection using wireless sensor networks. In: 2016 International Siberian Conference on Control and Communications (SIBCON), IEEE: 1–4.
Khamukhin A.A., Demin A.Y., Sonkin D.M., Bertoldo S., Perona G., Kretova V. (2017): An algorithm of the wildfire classification by its acoustic emission spectrum using Wireless Sensor Networks. Journal of Physics: Conference Series, 803: 012067
Kumar A. (2017): Energy Efficient Clustering Algorithm for Wireless Sensor Network, Doctoral dissertation, Lovely Professional University: 28.
Murray A.T. (2016): Maximal coverage location problem: impacts, significance, and evolution. International Regional Science Review, 39: 5–27.
Sá A.C., Benali A., Fernandes P.M., Pinto R.M., Trigo R.M., Salis M., Pereira J.M. (2017): Evaluating fire growth simulations using satellite active fire data: Remote sensing of environment, 190: 302–317.
Saldamli G., Deshpande S., Jawalekar K., Gholap P., Tawalbeh L., Ertaul L. (2019): Wildfire Detection using Wireless Mesh Network. In: 2019 Fourth International Conference on Fog and Mobile Edge Computing (FMEC), IEEE: 229–234.
Sudha B. S., Yogitha H. R., Sushma K. M., Bhat P. (2018): Forest Monitoring System Using Wireless Sensor Network: International Journal of Advances in Scientific Research and Engineering, 4.
The state of food and agriculture (2007): FAO Agriculture Series No. 38 Rome, Italy: 135. Available at (accessed Sep 20, 2006).
Vetter S., Haffer S., Wagner T., Tiemann M. (2015): Nanostructured Co3O4 as a CO gas sensor: Temperature-dependent behavior. Sensors and Actuators B: Chemical, 206: 133–138.
Wang X., Wotton B.M., Cantin A.S., Parisien M.A., Anderson K., Moore B., Flannigan M.D. (2017): cffdrs: an R package for the Canadian forest fire danger rating system. Ecological Processes, 6: 5.
Watts J.M., Hall J.R. (2016): Introduction to fire risk analysis. In SFPE Handbook of Fire Protection Engineering, Springer, New York, NY: 2817–2826.
Yang J., Zhou J., Lv Z., Wei W., Song H. (2015): A real-time monitoring system of industry carbon monoxide based on wireless sensor networks. Sensors, 15: 29535–29546.
Ye T., Wang Y., Guo Z., Li Y. (2017): Factor contribution to fire occurrence, size, and burn probability in a subtropical coniferous forest in East China. PloS one, 12: e0172110.
Zhang M.M., Yang K.Y., Zhou R. L. (2015): Relational Model among Dead Combustible Moisture Content, Temperature and Humidity under Keteleeria evelyniana Forest: Journal of Anhui Agricultural Sciences, 2015: 89.
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