Improvement of firebrand tracking and detection software

Burning and glowing firebrands generated by wildland and urban fires may lead to the initiation of spot fnes and the ignition of structures. One of the ways to obtain this infonnation is to process tliennal video files. Earlier, a number of algorithms were developed for the analysis of the characteristics of fu'ebrands under field conditions. However, they had certain disadvantages. In this regard, this work is devoted to the development of new algorithms and their testing

Particle tracking and detection software for firebrands characterization in wildland fires

Detection and analysis of the objects in a frame or a sequence of frames(video) can be used to solve a number of problems in various fields, including the fieldof fire behaviour and risk. A quantitative understanding of the short distance spotting dynamics, namely the firebrand density distribution within a distance from the fire front and how distinct fires coalesce in a highly turbulent environment, is still lacking. To address this, a custom software was developed in order to detect the location and the number of flying firebrands in a thermal image then determine the temperature and sizes of each firebrand. The software consists of two modules, the detector and the tracker. The detector determines the location of the firebrands in the frame, and the tracker compares the firebrand in different frames and determines the identification number of each firebrand. Comparison of the calculated results with the data obtained by the independent experts and experimental data showed that the maximum relative error does not exceed 12% for the low and medium number of firebrands in the frame (less than 30) and software agrees well with experimental observations for firebrands > 20 9 10-5 m. It was found that fireline intensity below 12,590 kW m-1 does not change significantly 2D firebrand flux for firebrands bigger than 20 9 10-5 m, while occasional crowning can increase the firebrand flux in several times. The developed software allowed us to analyse the thermograms obtained during the field experiments and to measure the velocities, sizes and temperatures of the firebrands. It will help to better understand of how the firebrands can ignite the surrounding fuel beds and could be an important tool in investigating fire propagation in communities

Use of computer vision in assessment of air quality in city transportation system

An approach to the formation of a description of the city's transport system is considered in order to identify the most polluted road spans with vehicle exhaust gases. The quantitative characteristics of pollution are determined in accordance with the standard Russian GOST R 56162-2019. When estimating emissions from road transport, information presented on the web in graphical form about traffic jam is used. In addition, the information on the number of cars, average speed and type of transport obtained by analyzing the video stream from web cameras by the YOLO neural network (version 4) is also used. The binding of pollution results to the transport system is formalized using the transport system ontology. The results can be used in dynamic models of pollution in urbanized area

Improvement of firebrand tracking and detection software

Burning and glowing firebrands generated by wildland and urban fires may lead to the initiation of spot fnes and the ignition of structures. One of the ways to obtain this infonnation is to process tliennal video files. Earlier, a number of algorithms were developed for the analysis of the characteristics of fu'ebrands under field conditions. However, they had certain disadvantages. In this regard, this work is devoted to the development of new algorithms and their testing

Investigation of firebrand production during prescribed fires conducted in a pine forest

This paper represents a study on the characterization of firebrand production which was carried out, using experimental fires conducted as prescribed fires in the New Jersey Pine Barrens, USA in March of 2013–2015. Several preliminary techniques were tested to characterize the firebrand production. Firebrands were collected from three plots for each year and analyzed for mass and size distribution. Thermal imagery was used to measure the velocity, size and number of firebrands in 2014 and 2015. The distribution of firebrands was evaluated in a monitored volume during the experiment. It was found that not less than 70% of collected particles were bark fragments and the rest were pine and shrub branches. The number of firebrands decreases with increasing the cross section area of firebrands. The mass of the particles varied from 5 to 50 mg, and the maximum number of the particles was observed for the mass range of 10–20 mg. About 80% of firebrands were particles with the cross section area of (5–20) × 10−5 m2. These results are consistent with the available observations of real fires [1], [2]. Processing of infrared video showed that starting from a distance of 13 m from fire front, an increasing number of firebrands were observed in a controlled volume, increasing in number up to 180 per second. Relationships describing the time-variation of the number of particles that dropped on a 1.4 m2 surface and the number of particles that flew through a 1 m3 volume were obtained. Comparing the experimental and calculated data, we can conclude that these relationships allow us to describe the two numbers with an acceptable accuracy (adj. R2 0.74 and 0.86, respectively). In addition, the velocity of the particles, which depended on the wind velocity, was in the 0.1–10.5 m/s range, with an average value of 2.5 m/s