Summary Reader Response Draft #3

 

According to the article "Drones Take Their Place on the Cutting Edge of Wildfire Fighting" (Patterson, 2021) states, though life-saving backpack technology such as drones is not new, firefighters do not have access to it. As a result, Georgia State University researchers are working to improve drones to better combat wildfires. Patterson claims that their drone KHawk is designed to fly autonomously while transmitting weather data, including forecasts of where the flames will spread next.

 

Patterson also states, "The U.S. Department of Interior (DOI) started flying drone missions in 2010 with about 200 total flights." DOI plans to expand the drone fleeting mission and began the first use of UAS for aerial ignition operations. The fundamental idea behind employing the intentional ignition strategy is to start a fire that burns back towards the main fire line, eventually starving the flames and putting them out by depriving the main fire line of adequate fuel to go forward. Drone Amplified, a company based in Lincoln, Nebraska, developed this IGNIS drone payload system.

 

Drones have been playing a crucial role in the community by fighting fires. I believe that in the near future, drones will be able to locate hotspots for wildfire, initiate controllable fires, and plant seeds for forestry.

 

In the past few years, the utilization of artificial intelligence (AI) in drones and small-scale unmanned aircraft systems (UAS) have become popular in helping to fight forest fires by detecting their hotspots. (Ambrosia et al., 2003) showed that small-scale unmanned aircraft systems (UAS) could help monitor wildfires, and this technological innovation could significantly reduce the cost of wildfire management response. For instance, drones and other small-scale UAS utilize infrared radiation to help first responders find human heat signatures and fire hotspots, which indicate where flames are most likely to spread (Burke et al., 2019). This shows that drones are beneficial for forest fires that quickly get out of control. This article supports the argument that drones will soon locate hotspots for wildfires. 

 

Research has shown drones are not just used to fight wildfires; they also manage forest fires, and lately, drones have been used to assist in prescribed fires. A good example is the IGNIS system, which is amplified by drones and contains many chemical spheres loaded with glycol that burst shortly after impacting the ground, lighting a small fire (Surya, 2020). The idea behind this tactic is that once the fuel has been burned, it cannot be burned again. Thus, if a grass fire travels in one direction and the drone starts a fire from that point onwards towards the fire, there will be no fuel left to burn, and the fire will go out (Liu et al., 2016), decreasing the fuel load. These drone-based rescue interventions would eventually make the task of the fire rescue team much more effective and contribute to reducing the overall damage.

 

Aside from drones' utility in fire management, they are also utilized in plant health by planting seeds for forestry. Following an ice storm that impacted 11 states in the United States back in January 2016, McElwee (2021) discovered that West Virginia's Division of Forestry began using drones to monitor current logging jobs and post-harvest activities to ensure that best management practices are being followed. The blizzard destroyed most of the plantations in the cities and had to be replanted. Routine inspections that once took several hours to complete could now be done under an hour with a drone, emphasizing another benefit of using drones. 

 

While there are many advantages to drones in fire management and forestry, there are also several limitations. First, is the challenge of equity and probability. No matter how much experts study using AI to predict fires, technology is still a bright shiny object, and fires might be more complex than they seem (Edlinger et al., 2019). Moreover, another challenge is dealing with the different variables that influence fire behaviour in wildland and urban environments. For instance, human behaviour, ignition sources, weather etc. ​​(Velencoso et al., 2018). Thus, it remains favourable to use predictive analytics to improve the efficacy of fire preparedness, prevention, and mitigation remains a good option (Yfantis, 2017).

 

In conclusion, with various infrastructure developments and more deployment of smart cities, fire detection and extinguishing are becoming a concern for nations. These drone-based rescue interventions would eventually make the task of the fire rescue team much more effective and contribute to reducing the overall damage.  

 

 

References

Ambrosia, V. G., Wegener, S. S., Sullivan, D. V., Buechel, S. W., Dunagan, S. E., Brass, J. A., Stoneburner, J., & Schoenung, S. M. (2003). Demonstrating UAV-Acquired Real-Time Thermal Data over Fires. Photogrammetric Engineering & Remote Sensing, 69(4), 391–402. https://doi.org/10.14358/pers.69.4.391

Burke, C., Wich, S., Kusin, K., McAree, O., Harrison, M., Ripoll, B., Ermiasi, Y., Mulero-PázmányM., & Longmore, S. (2019). Thermal-Drones as a Safe and Reliable Method for Detecting Subterranean Peat Fires. Drones, 3(1), 23. https://doi.org/10.3390/drones3010023

Christensen, B., Herries, D., Hartley, R. J. L., & Parker, R. (2021). UAS and smartphone integration at wildfire management in Aotearoa New Zealand. New Zealand Journal of Forestry Science, 51. https://doi.org/10.33494/nzjfs512021x127x

Edlinger, R., Zauner, G., & Zauner, M. (2019). Hazmat label recognition and localization for rescue robots in disaster scenarios. Electronic Imaging, 2019(7), 463–461463–466. https://doi.org/10.2352/issn.2470-1173.2019.7.iriacv-463

Liu, P., Yu, H., Cang, S., & Vladareanu, L. (2016). Robot-assisted smart firefighting and interdisciplinary perspectives. 2016 22nd International Conference on Automation and Computing (ICAC). https://doi.org/10.1109/iconac.2016.7604952

McElwee, E. (2021, December 8). Drones Use in Forestry 2021 https://dukespace.lib.duke.edu/dspace/bitstream/handle/10161/24060/Drone%20Use%20in%20Forestry_McElwee_20211208.pdf?sequence=1. Dukespace. https://dukespace.lib.duke.edu/dspace/bitstream/handle/10161/24060/Drone%20Use%20in%20Forestry_McElwee_20211208.pdf?sequence=1

Patterson, T. (2021, October 7). Drones Take Their Place on the Cutting Edge of Wildfire Fighting. FLYING Magazine. https://www.flyingmag.com/drones-wildfire-fighting/

Smithsonian, M. (2021, August 20). From Supercomputers to Fire-Starting Drones, These Tools Help Fight Wildfires. Smithsonian Magazine. https://www.smithsonianmag.com/innovation/from-supercomputers-to-fire-starting-drones-these-tools-help-fight-wildfires-180978421/

Surya, L. (2020, October 10). Fighting fire with AI: Using deep learning to help predict wildfires in the US. Research Gate. https://deliverypdf.ssrn.com/delivery.php?ID=025078121121077079086103064028102009116008031085056044126102097009101074075088126065033020049102118033018088017122124067093104105041060022013118093117074109102000066006050071071103009003124081127116083085064123084125100120104121005081121015097091105111&EXT=pdf&INDEX=TRUE

Velencoso, M. M., Battig, A., Markwart, J. C., Schartel, B., & Wurm, F. R. (2018). Molecular Firefighting—How Modern Phosphorus Chemistry Can Help Solve the Challenge of Flame Retardancy. Angewandte Chemie International Edition, 57(33), 10450–10467. https://doi.org/10.1002/anie.201711735

Yfantis, E. A. (2017, October 5). An Autonomous UAS with AI for Forest Fire Prevention, Detection, and Real Time Advice and Communication To... ResearchGate; unknown. https://www.researchgate.net/publication/321290336_An_Autonomous_UAS_with_AI_for_Forest_Fire_Prevention_Detection_and_Real_Time_Advice_and_Communication_To_and_Among_Firefighters

 

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