**Author details**

This chapter aims to provide an alternative view for early fire detection based on

Part of the architecture is already validated under real-world conditions, and the results are promising. The overall system performance is expected to be further

This work was performed within the AF3 Project (Advanced Forest Fire Fight-

ing), with the support of the European Commission by means of the Seventh

Framework Programme (FP7), under Grant Agreement No. 607276.

There are no "conflict of interest" issues regarding this chapter.

ð Þ *f* ∗ *g* ðÞ¼ *t*

*h*0

The mathematical definition of the convolution process between two onedimensional signals *f*(*t*) and *g*(*t*) follows in Eq. (9). The mathematics behind LSTM layer architecture follows in Eqs. (10)–(13). Functions *σ* and *tanh* represent the sigmoid and hyperbolic tangent function, respectively. Parameter W corresponds to

> ðþ<sup>∞</sup> �∞

*Ot* ¼ ð Þ 1 � *zt* ∗ *Ot*�<sup>1</sup> þ *zt* ∗ *h*<sup>0</sup>

*f*ð Þ*τ g t*ð Þ � *τ dτ* (9)

*<sup>t</sup>* (13)

*zt* ¼ *σ Wz* � *Ot*�<sup>1</sup>*; Ot* ð Þ ½ � (10)

*rt* ¼ *σ Wr* � *Ot*�<sup>1</sup>*; Ot* ð Þ ½ � (11)

*<sup>t</sup>* ¼ tanh *W* � *rt* ∗ *Ot*�<sup>1</sup>*; Ot* ð Þ ½ � (12)

twitter posts, instead of expensive sensors and other infrastructures. A hybrid system architecture is introduced which combines a deep learning process for the detection of valid twitter posts regarding fire bursts and a NLP process which extracts the crucial information (place, time, etc.) from the valid tweets. Finally, risk assessment, based on analytics, is performed which derives the geographical

places threatened by fire at the current time.

**Acknowledgements**

*Cyberspace*

**Conflict of interest**

weighting matrices:

**92**

**A. Appendices and nomenclature**

improved once the deep learning scheme is entirely utilized.

Konstantinos-George Thanos\*, Andrianna Polydouri, Antonios Danelakis, Dimitris Kyriazanos and Stelios C.A. Thomopoulos Integrated Systems Laboratory (ISL), Institute of Informatics and Telecommunications, National Center for Scientific Research "Demokritos", Athens, Greece

\*Address all correspondence to: giorgos.thanos@iit.demokritos.gr

© 2019 The Author(s). Licensee IntechOpen. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/ by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
