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Based on comment from this question, and coments from the other related question (Fire/Flame Detection using OpenCV):

@stevenputtemans: "Another way could be to use the fact that fire actually involves motion between frames in a video input"

@guanta "You could train a cascade-classifier with LBPs since LBPs are also often used for texture detection/recognition this would be worth trying"

@red-viper
"is there any other way that uses machine learning?"

@pklab "The example shows that in the visible spectrum, the flame visibility depend on context. In the IR, the context is less relevant. After this you could use ML on IR image too."

I would like to complete the proposed hardware answer with a software one that i think could work together.

In this paper: "Early Fire Detection Using HEP and Space-time Analysis" [1] motion (as suggested by @stevenputtemans) and texture analysis (as suggested by @guanta) are involved.

You could also check "Video Fire Detection - Review" [2], Real-time Fire Detection for Video Surveillance Applications using a Combination of Experts based on Color, Shape and Motion [3], Automatic fire pixel detection using image processing: A comparative analysis of Rule-based and Machine Learning-based methods [4]

[1] http://arxiv.org/pdf/1310.1855.pdf

[2] http://signal.ee.bilkent.edu.tr/Publications/Video%20Fire%20Detection-Review.pdf

[3] https://www.researchgate.net/profile/Alessia_Saggese/publication/271704566_Real-time_Fire_Detection_for_Video_Surveillance_Applications_using_a_Combination_of_Experts_based_on_Color_Shape_and_Motion/links/54d09bef0cf20323c217f7b9.pdf

[4] https://hal.archives-ouvertes.fr/hal-01181626/document