![](bg8.png)
(a) Zoomed view of the region with
fire hazard 4 values over the gener-
ated dot mask.
(b) Zoomed view of the region with
fire hazard 5 values over the gener-
ated dot mask.
Figure 15: Magnified view of each chosen region with dis-
tance measurements between each point made via QGIS.
transmitting the acquired data to the central process-
ing. As future work, the forest data will be collected
and analysed with artificial intelligent algorithm in or-
der to identify data patterns and alerts to the control
servers, triggering in the case of an ignition detection.
ACKNOWLEDGEMENTS
This work has been supported by Fundac¸
˜
ao La Caixa
and FCT — Fundac¸
˜
ao para a Ci
ˆ
encia e Tecnologia
within the Project Scope: UIDB/5757/2020.
REFERENCES
Adorno, D., Soares, S., Lima, J., and Valente, A. (2019).
Evaluation of lp-wan technologies for fire forest de-
tection systems. In ALLSENSORS 2019, The Fourth
International Conference on Advances in Sensors, Ac-
tuators, Metering and Sensing, pages 49–53. IARIA
Conference.
Alkhatib, A. A. (2014). A review on forest fire detection
techniques. International Journal of Distributed Sen-
sor Networks, 10(3):597368.
Aslan, Y. E., Korpeoglu, I., and Ulusoy,
¨
O. (2012). A frame-
work for use of wireless sensor networks in forest fire
detection and monitoring. Computers, Environment
and Urban Systems, 36(6):614–625.
Baranov, A., Spirjakin, D., Akbari, S., and Somov, A.
(2015). Optimization of power consumption for gas
sensor nodes: A survey. Sensors and Actuators A:
Physical, 233:279–289.
Chen, T.-H., Wu, P.-H., and Chiou, Y.-C. (2004). An early
fire-detection method based on image processing. In
2004 International Conference on Image Processing,
2004. ICIP’04., volume 3, pages 1707–1710. IEEE.
Copernicus (2019). European union’s earth observation
programme. https://www.copernicus.eu. Accessed
November, 2019.
ICNF (2019). Instituto de conservac¸
˜
ao da natureza e das
florestas. https://www.icnf.pt. Accessed November,
2019.
Katayama, H., Naitoh, M., Suganuma, M., Harada, M.,
Okamura, Y., Tange, Y., and Nakau, K. (2009). De-
velopment of the compact infrared camera (circ) for
wildfire detection. In Remote Sensing System Engi-
neering II, volume 7458, page 745806. International
Society for Optics and Photonics.
Lloret, J., Garcia, M., Bri, D., and Sendra, S. (2009).
A wireless sensor network deployment for rural
and forest fire detection and verification. sensors,
9(11):8722–8747.
LoRa Alliance Technical Marketing Workgroup, L. (2019).
technical overview of lora and lorawan. help@
lora-alliance.org. November, 2019.
QGIS (2019). A free and open source geographic infor-
mation system. https://qgis.org. Accessed November,
2019.
Singh, P. K. and Sharma, A. (2017). An insight to forest fire
detection techniques using wireless sensor networks.
In 2017 4th International Conference on Signal Pro-
cessing, Computing and Control (ISPCC), pages 647–
653. IEEE.
Verde, J. C. (2010). Avaliac¸
˜
ao da perigosidade de inc
ˆ
endio
florestal. PhD thesis, University of Lisbon.
Zhang, J., Li, W., Yin, Z., Liu, S., and Guo, X. (2009).
Forest fire detection system based on wireless sensor
network. In 2009 4th IEEE conference on industrial
electronics and applications, pages 520–523. IEEE.