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Drones in wildfire management

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An MQ-9 Reaper remotely piloted aircraft assigned to the 163d Attack Wing soars over Southern California skies on a training flight to March Air Reserve Base, California, in this Sept. 15, 2016, file photo. The wing is flying MQ-9s in support of civil authorities battling deadly wildfires in Northern California. (Air National Guard Photo by Tech. Sgt. Neil Ballecer)
This infrared video is from above the North Umpqua Fire by Marcus Tobey, BLM. That southwest Oregon blaze burned about 43,000 acres.

Drones, also known as Unmanned Aerial Systems/Vehicles (UAS/UAV), or  Remotely Piloted Aircraft, are used in wildfire surveillance and suppression.[1][2] They help in the detection, containment, and extinguishing of fires faster and with greater safety.[3] They are also used for locating a hot spot, firebreak breaches, and then to deliver water to the affected site.[4] In terms of maneuverability, these are superior to a helicopter or other forms of manned aircraft.[5] They give firefighters a bird’s-eye view of the terrain and help them determine where a fire will spread through tacking and mapping fire patterns.[1][6][7] These empower scientists and incident personnel to make informed decisions. These devices can fly when and where manned aircraft are unable to fly.[8] They are associated with low cost and are flexible devices that offer a high spatiotemporal resolution.[9]

The data gathered through these devices is unique and accurate as they fly low, slow, and for a long period. They can also collect high-resolution imagery and sub-centimeter data in smoke and at night. It provides firefighters access to real-time data without putting the lives of pilots at risk.[8][10][5] Managing a 24/7-drone fleet over any huge forestland is challenging. Firefighting agencies have carried out several experiments with firefighting drones, but they are far from the perfect solution.[3] Public drones pose a danger to wildfire and can cost lives. Fire response agencies are forced to ground their aircraft to avoid the potential for a midair collision.[11] Policies in the United States, Canada, and Australia discourage the use of public drones near wildfires.[12][13][14]

History

Wildfires are one of the costliest and deadliest natural disasters across the globe.[15] Between the years 2006 to 2016, manned aircraft crashes accounted for 24% of deaths attributed to firefighting, according to the U.S. Forest Service.[3] Ground sensors, remotely piloted vehicles (RPV), or satellite imaging have been tested as a firefighting tool, but these methods do not offer a fast and reliable solution for wildfire detection and monitoring.[16][12] Delayed fire detection due to missing small fires at early stages, relatively long time lag for satellites to overpass the field and infeasibility of deploying sensors with limited sensing distance ranges are current problems in firefighting.[15] According to a Wall Street Journal report, the non-military drone use began in the year 2006, when government agencies began using them for disaster relief, border surveillance, and wildfire fighting, while corporations started using drones to inspect pipelines and spray pesticides on farms.[17] The technology has been used in fires for years, but they are now becoming a critical tool to fight wildfires.[7]

Description

Thermal-infrared imaging sensors on NASA's Ikhana unmanned research aircraft recorded this image of the Grass Valley/Slide Fire near Lake Arrowhead/Running Springs in the San Bernardino Mountains of Southern California just before noon Oct. 25. The 3-D processed image is a colorized mosaic of images draped over terrain, looking east. Active fire is seen in yellow, while hot, previously burned areas are in shades of dark red and purple. Unburned areas are shown in green hues.

Drones or UAVs are an emerging technology that has been utilized in a wide range of civilian and military applications, including environmental monitoring, and precision agriculture. They have been tested in several fire monitoring missions.[12] These devices allow firefighters accurate data by providing a bird’s-eye view of the terrain. By using the real-time data, firefighters can determine where a fire will move next, assisting them in making swift decisions and draw up a strategic plan about movement and evacuation.[3][6] UAVs that are designed specifically for extinguishing forest fires have the potential to eliminate virtually 100% of the devastating fires.[3] These devices have been deployed on fires in Nebraska and Oregon, setting backburns meant to limit the spread of wildfire.[18]

Unmanned aerial systems can operate after dark, and in dangerous, smoky conditions.[18] Manufacturers equip these devices with infrared cameras that capture high-resolution imagery even in smoke and sensors for wind direction and other weather variables that affect how wildfires spread. They can fly in canyons and other cramped spaces where helicopters can’t fly and glide low enough to capture high-resolution footage. The capability to operate at a low elevation allows firefighters to use UAVs to identify quick escape routes.[6] Some drones are capable of floating in a stationary position for hours to monitor geography through streaming video or thermal imaging travel of embers and fire spread. It allows them to analyze the condition of evacuation corridors, and act as aerial weather stations by measuring wind speed and direction, helping firefighters with containment strategies.[2] These are used in approving flights to monitor massive wildfires in the US Pacific Northwest and near the Perth metropolitan complex in Australia.[9]

These devices can identify locations of potential fire breaks, water sources available for restocking vehicles, monitor weather, and air- quality conditions. It helps in prioritizing firefighting tactics by assessing fuels around homes or infrastructure ahead of the fire.[9]

The use of UAVs limits exposure and reduces risk to pilots and wildland firefighters. Easily packable and able to fly in remote locations.[8] These can fly as fast as 40 miles an hour. The drone pilots can operate the devices at varying speeds to help people better see what is happening. The transmission from drones or UAVs can be viewed on a laptop computer in a mobile ground station. A drone weighing 15 pounds and a six-foot wingspan, has a range of about eight miles and can stay in the air for an hour without recharging. The aircraft can be programmed to fly on its own, but a safety pilot will monitor operations during the tests.[19] These also serve as tools for starting planned, controlled fires to clear out hard-to-kill underbrush.[4] Drones are a part of fire research and management.[20]

Spotfire detection and suppression using drones pave the way for improved allocation of personnel and resources by avoiding false identification of new fires. It also provides a continuous mapping of a fire’s perimeter, size, spread, and intensity, and offers enhanced visibility in high smoke and low light conditions.[9]

Dragon egg systems

Drones have also been studied as tools for starting planned, controlled fires to clear out hard-to-kill underbrush.[4] It is called the “Dragon Egg System.” It consists of self-igniting plastic spheres filled with potassium permanganate. These are similar to ping-pong balls but are injected with glycol. These glycol-filled balls are dropped. The glycol reacts and sets them ablaze in less than 30 seconds. In this duration, the ball bounces through a thick forest canopy and land on the ground.[21][22] These are prescribed burns in climates that allow firefighters more control over the flames.[18] Drones cannot put out fires, but they can start them, which reduces flammable materials that could fuel an oncoming wildfire.[15][6][22] A master's students from the University of Idaho was the first person to pilot an “unmanned aerial system plastic sphere dispenser” to deploy fire on a federally managed wildfire near Flagstaff, Arizona.[23]

Ignis system

The first successful research over prescribed burners through the unmanned aerial system was carried out by a team at the University of Nebraska. It carries a load of the fire-ready balls, automatically pierce each and inject the glycol, and complete the drop. The system was called the “Ignis System” developed by Drones Amplified, a private company, in partnership with the Department of Interior. In this system, the payloads of dragon eggs are programmed to only drop within a designated geographic area. In the year 2018, the interior department trained firefighters to pilot the drones, after they purchased eight Ignis Systems.[18]

Throwflame aerial flamethrower

Throwflame is Quinn Whitehead’s company, and it entered the market of prescribed burners in July. It developed the drone-mounted flamethrower to its catalog of handheld incendiary devices for professional and recreational use. The system by the company contains a gallon of gasoline and shoots a hefty stream of fire at vegetation, wasp nests, trash on power lines, or anything else a user might deem a suitable target.[18]

Integration

Drones are gradually becoming an integral part of the fight against wildfires in the United States, Canada, Australia, Europe, and Thailand.[3][12][24][25]

United States

The United States is experiencing longer wildfire seasons. According to the U.S. Forest Service, the changing climate has led to longer wildfire season. It has extended by an average of 78 days per year since the 1970s. In the year 2017, the cost of fighting U.S. wildfires topped $2 billion. U.S. government agencies, Department of the Interior, and the forest service are encouraging the use of unmanned aircraft to battle fires by setting them first.[3] In the year 2018, the President passed an executive order on wildfire management called for maximizing the use of drones. The support from the White House and data showing increasing interest in federal drone usage.[18][15][21]

NASA’s remotely-piloted Ikhana aircraft, based at the agency’s Armstrong Flight Research Center, is flown in preparation for its first mission in public airspace without a safety chase aircraft.

In the year 2008, NASA's Ikhana unmanned aerial vehicle (UAV) was used in the battle against more than 300 wildfires raging in California.[26] Matrice 600 (M600) was used during the Woodbury Fire on June 8, 2019, about 5 miles northwest of Superior, Arizona.[15] In the year 2018, the Bureau of Land Management had 531 drones and 359 operators in its service and provided support during earthquakes, wildfires, hurricanes, volcanic eruptions, animal migrations, and search and rescues.[15]

A BQM-167A Subscale Aerial Target is ready to be launched from Tyndall Air Force Base Launch Facility for the 104th Fighter Wing, Massachusetts Air National Guard, on April 13, 2011. Deployed to Tyndall Air Force Base in Florida, the 104th is participating in the Weapons System Evaluation Program (WSEP).

In the year 2013, the National Guard used a drone for the first time in Yosemite National Park to find a crew that lost connection to the commander. The drones helped in finding the crew in five minutes.[27][7] In the same year, the USFS used a UAS from the U.S. Department of Defense for 24- hour monitoring of the California Rim Fire. The USFS has identified ways to use UAS to monitor ground crews in low visibility conditions and to respond faster to changes in fire movement and behavior.[9]

Los Angeles Fire Department stated that it would use firefighting drones for the first time in its history to coordinate the effort to help extinguish a pair of fires threatening homes in the city on November 16, 2017.[6] In the same year, the federal firefighters used UAVs on 340 wildfires in Oregon. The firefighters made use of drones in 12 states, according to the Department of Interior.[10] Drones were used in thick smoke to find small fires that otherwise wouldn’t have been detected until they had become much harder to contain in the 2016 summer in California.[6] The drones are being used by Forest Service crews, Bureau of Land Management and the Oregon Department of Forestry.[28]

Wildfire Management Technology Advancement Act

In March 2019, the Wildfire Management Technology Act was signed into law as Section 1114 by President Trump. The bill encouraged the use of drones in managing and fighting wildfires by the federal agencies. It directed the Department of the Interior to set up or expand a research, development, and testing program to study the use of unmanned aircraft systems or drones is wildfire management operations.[29] The goal of the bill is to “develop consistent protocols and plans for the use of wildland fires of unmanned aircraft system technologies, including for the development of real-time maps of the location of wildland fires.”[29]

The bill was introduced in 2015 after the Carlton Complex Fire burned nearly 150,000 acres in one day. It supported the four-year effort led by Sen. Maria Cantwell of Washington to formalize how UAS can fulfill that promise for firefighters on the ground.[2][30]

FUEGO

An astrophysicist, Carlton Pennypacker from the University of California Berkeley, proposed the development of the Fire Urgency Estimator in Geosynchronous Orbit (FUEGO) in the year 2013. The design uses drones and satellite technology to spot wildfires in their early stages.[3]

Call When Needed contract

On May 15, 2018, the U.S. Department of the Interior had awarded a Call When Needed contract to four U.S. companies for small-unmanned aircraft systems services. It was an attempt to combat wildfires. It is a $17 million, one-of-its-kind on-call contract. It allows the agency to obtain fully contractor-operated and maintained small ready-to-be-deployed drones when needed to support wildland fire operations, search and rescue, emergency management in the Contiguous 48 States and Alaska. The companies included in the contract are Bridger Aerospace of Bozeman, Montana, Insitu of Bingen, Washington, Pathways2Solutions of Nashville, Tennessee, and Precision Integrated of Newberg, Oregon.[10][31]

Canada

In November 2015, the British Columbia Wildfire Service tested drones to fight and map wildfires. It also tested thermal imaging to look for hotspots that could flare again.[32] The wildfire service contracted two commercial drone companies in July and August. They flew their drones above the Boulder Creek and Elaho fires near Pemberton and the Rock Creek fire just north of the Canada-U.S. border.[33] The Alberta government-contracted Elevated Robotic Services, which deploys drones for mining companies to assist firefighters in spotting the location of the blaze.[34] In December 2017, researchers at the University of British Columbia used drones to survey the aftermath of the wildfires in British Columbia.[35]

China

A computer engineering researcher at Guangdong College of Business and Technology in Zhaoqing, China, Dr. Songsheng Li is working on an autonomous early warning system for wildfires. It uses small drones that patrol forests, gather environmental data, and analyze the threat of fires. The key components of his system include GPS systems, unmanned aerial vehicles (UAVs), and Intelligent Flight Modes.[36]

Europe

Real-Time Coordination and Control of Multiple Heterogeneous UAVs (COMETS) is a European project that focuses on utilizing a fleet of heterogeneous drones for forest surveillance, and forest fire detection and observation. The project aims to reduce the operational cost using less costly small drones and enhancing the imaging resolution. The drones for this project are controlled by humans that endangers their lives and limits the use of the system in remote and hard-to-reach regions.[12] A Spanish project led by Telefónica, a telecommunications corporation, involves researchers from the Universidad Carlos III de Madrid, drone-tech startup Divisek Systems, and drone-operations company Dronitec. It incorporates a network of communications towers that are equipped with a thermal camera and a quadcopter drone. After detection of fire, the computer system at the tower determines the geographical location of the blaze, and then forwards a signal to the drone with an email with location coordinates. It also sends an email to a firefighting crew at a base station. The drone is guided by the GPS and autonomously flies out to the fire, using its own thermal and optical cameras to obtain and transmit visuals back to the firefighters.[37] In the year 2019, two Shark Robotics' Colossus drones were used by firefighters standing outside Notre Dame in Paris when a fire ripped through the 850-year old cathedral. Aerones, a Lativian company, has created a drone that can fly up to 984 feet, but this has to be controlled by a pilot on the ground and has a short battery life, providing only 30 minutes of flight time from a 90-minute charge.[24]

Thailand

Natural Resources Minister Warawuth Silpa-archa is planning to have the Department of National Parks, Wildlife and Plant Conservation (DNP) use heat-detecting drones as a measure for forest fire prevention.[25]

Types

2016 model DJI Phantom 4 quadcopter with a gimbal stabilised 4K UHD camera, GPS stabilization and automatic obstacle avoidance
Members of the 163d Aircraft Maintenance Squadron,163d Attack Wing, California Air National Guard, conduct a preflight check on the wing's MQ-9 Reaper remotely piloted aircraft before a fire support mission, Aug. 1, 2018, at March Air Reserve Base, California. The wing is supporting state agencies who are battling numerous wildfires in Northern California, including the Carr Fire and Mendocino Complex Fire.

The types of drones range from tiny quadcopters to big fixed-wing aircraft. Some drones are equipped with infrared cameras, which allow them to safely fly through the smoke while using sensors for wind direction. The tiny drones can fly through confined spaces and capture necessary high-resolution footage. The surveillance drones will likely be a separate operation from the fire-suppression drones.[3] There are fire-starting drones that help in limiting the damage caused by wildfires.[18] The hobbyist drones are those piloted by the public. The use of these drones over wildfires is prohibited by the authorities in the United States and Canada. These drones hinder the firefighting operations and prevent the agencies from using aerial techniques.[16]

The UAS has four types based on their capabilities. The type 1 UAS is the most capable, and type 4 is the least complex but the most portable. Type 3 or type 4 is operated by agencies because they can be stored in a backpack and launched from the fireline. These operate at low altitudes, below 400 feet, have a battery life less than an hour. These can only be operated within visual line of sight. If a fireline supervisor needs to get a better vantage point while on the line, they can launch these smaller UAS from their location and get the information back in real-time.[38]

Type 1 and type 2 UAS are complex systems and require 3 to 9 crew members on designated areas for launching. The responsibilities of these crew members include flying the aircraft, coordinating with the ground and air resources, and interpreting data. These larger systems can fly to heights over 10,000 feet and operate for multiple hours. They can fly beyond visual line of sight while carrying multiple cameras for mapping. On larger wildfires, the Incident Management Team can utilize these larger “drones” for quicker turnaround times on infrared flights to identify heat along the fire perimeter.[38]

Challenges

Drones assist in wildfire management, but managing a 24/7-drone fleet over huge and extinguishing a fire under several layers of tree canopy are major challenges. Different trees require a unique navigation strategy. Some drones take time to fly through densely covered grounds. Operating drones day and night in harsh weather requires an enormous effort. The inability to communicate with ground crews and other aircraft increases the chances of interfering with other air traffic, such as air tankers, helicopters, and additional firefighting aircraft that are necessary to suppress wildland fires.[3]

A hobbyist drone over a fire puts firefighting risks at a halt and creates a high risk of accidents.[16] Public drones disrupted wildfire operations in several locations.[39] It also forces fire response agencies to ground their aircraft to avoid the potential for a midair collision. Public drones had caused firefighters to shut down a few of operations when there was an unidentified drone spotted.[7][40] There have been more than 100 documented cases of unauthorized drones flying over wildfires.[11] During the Bocco Fire, firefighters had to stop their efforts when an unauthorized civilian drone flew into their airspace.[41] A drone has invaded the airspace above a Minnesota wildfire in each of the last four years since 2016. Interference of public drones create problems for firefighting aircraft, firefighters on the ground, and the public.[42]

Accidents

Image of firefighters using water to douse an edge of the Kendrick Wildfire.

A drone reportedly caught fire after it crashed, igniting dry grasses in an area called Kendrick Park near Flagstaff, Arizona, in March 2018. The owner of the drone was charged with starting a fire that destroyed 300 acres of grassland in Arizona’s Coconino National Forest.[3]

Policies

United States

For public

US Department of Agriculture poster warning about the risks of flying drones near wildfires

The authorities have banned the use of UAVs during operations in wildfire zones due to potential collisions with aircraft flying at low altitudes.[12] It is against the law to fly a drone near a wildfire, and if caught, the drone could be confiscated by law enforcement, and hefty fines can be imposed in the U.S.[16] Temporary Flight Restrictions (TFRs) are typically put in place during wildfires. It requires aircraft, manned or unmanned, that are not involved in wildfire suppression operations to obtain permission from fire managers to enter specified airspace. It’s a federal crime to interfere with firefighting efforts on public lands, and it can lead to 12 months in prison. Congress has authorized the FAA to impose a civil penalty of up to $20,000 against any drone pilot who interferes with wildfire suppression, law enforcement, or emergency response operations. The FAA treats these violations seriously and will immediately consider swift enforcement action for these offenses.[39][11]

Members of media

As per the law, the media is not allowed to fly drones near wildfires and never interfere with aviation operations or firefighting missions. Media personnel needs to have a special approval, and to qualify for the special approval process, the operations must directly support a response, relief, or recovery activity benefiting a critical public good. They should be a part of the existing Part 107 Remote Pilot and have the support of the on-scene commander on the ground before application submission. After receiving approval, the media personnel must work with the on-site authority, and never interfere with aviation operations or firefighting missions.[11]

Australia

Australia’s Civil Aviation Safety Authority (CASA) has issued a warning about the drone. The action was taken after viewing footage taken during the Blue Mountains fires in the year 2013. It was against the regulations laid down in CASA regulations.[13]

Canada

Transport Canada and the British Columbia Wildfire Service banned the use of UAVs or drones near a wildfire. All wildfire zones become “flight restricted,” according to the federal Canadian Aviation Regulations. The restrictions stretches to a radius of five nautical miles around the fire and an altitude of 3,000 feet above ground level. As of 2016, interference with wildfire control efforts, including flying drones or UAVs, can face penalties up to $100,000 and up to one year in jail.[14]

References

  1. ^ a b Coops, Nicholas; Goodbody, Tristan R. H. "Drones help track wildfires, count wildlife and map plants". The Conversation. Retrieved 2020-05-01.
  2. ^ a b c "What to know about the Wildfire Management Technology Advancement Act". FireRescue1. Retrieved 2020-05-01.
  3. ^ a b c d e f g h i j k Frey, Thomas (2018-08-22). "Using Drones to Eliminate Future Forest Fires". Futurist Speaker. Retrieved 2020-05-01.
  4. ^ a b c Divis, Dee Ann (2019-02-05). "Feds Directed to Use Drones to Fight Wildfires". Inside Unmanned Systems. Retrieved 2020-05-01.
  5. ^ a b "Drones and Wildfires: How New Tech is Shaping Wildfire Response - Wildfires, Drones, and Emergency Management". veoci.com. Retrieved 2020-05-01.
  6. ^ a b c d e f "Drones are fighting wildfires in some very surprising ways". NBC News. Retrieved 2020-05-01.
  7. ^ a b c d Lapastora, Charlie (2019-06-24). "Drones the latest critical tool to fight wildfires". Fox News. Retrieved 2020-05-01.
  8. ^ a b c "Drones on Wildfires." doi.gov. Retrieved 2020-05-01
  9. ^ a b c d e D. Twidwell et al. "Smokey comes of age: unmanned aerial systems for fire management" The Ecological Society of America. Retrieved 2020-05-01.
  10. ^ a b c Courier, JEFF DUEWEL AND SCOTT STODDARD, The Daily (2018-08-17). "'The best friend a firefighter could have': How drones help battle Oregon wildfires". KVAL. Retrieved 2020-05-01.{{cite web}}: CS1 maint: multiple names: authors list (link)
  11. ^ a b c d "Drones & Wildfires Digital Toolkit." Federal Aviation Administration. Retrieved 2020-05-01.
  12. ^ a b c d e f Fatemah Afgah et al. "Wildfire Monitoring in Remote Areas using Autonomous Unmanned Aerial Vehicles" Northern Arizona University & University of Alabama. Retrieved 2020-05-01.
  13. ^ a b "Drones on the Fire Ground - Australia Update". International Association of Wildland Fire. Retrieved 2020-05-01.
  14. ^ a b "Drones and UAVs" gov.bc.ca. Retrieved 2020-05-01.
  15. ^ a b c d e f By (2019-07-19). "Drones equipped with infared cameras monitor wildfires across the West". Cronkite News - Arizona PBS. Retrieved 2020-05-01.
  16. ^ a b c d "Drones and Wildfire | Department of Forestry and Fire Management". dffm.az.gov. Retrieved 2020-05-01.
  17. ^ "The History Of Drones (Drone History Timeline From 1849 To 2019)". Dronethusiast. 2020-04-28. Retrieved 2020-05-01.
  18. ^ a b c d e f g Cagle, Susie (2019-09-04). "'Dragon' drones: the flame throwers fighting wildfires with fire". The Guardian. ISSN 0261-3077. Retrieved 2020-05-01.
  19. ^ "Drones: A Tool For Early Wildfire Detection". VPM.org. Retrieved 2020-05-01.
  20. ^ "Fire". www.mdpi.com. Retrieved 2020-05-01.
  21. ^ a b Kesteloo, Haye (2019-09-04). "Self-igniting eggs dropped by 'dragon' drones can help save lives". DroneDJ. Retrieved 2020-05-01.
  22. ^ a b Society, National Geographic (2020-03-16). "Drones Shoot Fireballs to Help Control Wildfires". National Geographic Society. Retrieved 2020-05-01.
  23. ^ "University of Idaho master's student first to pilot a fire-deploying drone to combat wildfire". www.uidaho.edu. Retrieved 2020-05-01.
  24. ^ a b Farmbrough, Heather. "As Australia Burns, A Danish Startup Steps Up Its Autonomous Drone Programme". Forbes. Retrieved 2020-05-01.
  25. ^ a b "Drones needed for forest-fire protection, fighting: Warawuth". The Nation Thailand. Retrieved 2020-05-01.{{cite web}}: CS1 maint: url-status (link)
  26. ^ Johnson, R. Colin (2008-07-15). "NASA drone's sensors help battle California wildfires". EE Times. Retrieved 2020-05-01.{{cite news}}: CS1 maint: url-status (link)
  27. ^ "Drones Are Now Being Used to Battle Wildfires". www.smithsonianmag.com. Retrieved 2020-05-01.
  28. ^ KTVL, Brian Schnee (2019-05-02). "Oregon used drones the most in 2018 on federal wildfires". KATU. Retrieved 2020-05-01.
  29. ^ a b "Bipartisan law pushes use of drones for fighting wildfires". www.fedscoop.com. Retrieved 2020-05-01.{{cite web}}: CS1 maint: url-status (link)
  30. ^ Knicely, John. "Wildfire firefighting technology bill headed to Trump, would expand drone mapping and GPS". KIRO. Retrieved 2020-05-01.
  31. ^ "Interior Awards First Contract for Small Unmanned Aircraft Systems Services". www.doi.gov. 2018-05-15. Retrieved 2020-05-01.
  32. ^ "B.C. Wildfire Service tests drones to help fight, map and prevent blazes". Retrieved 2020-05-01.
  33. ^ Karstens-Smith, Gemma (2015-11-03). "Drones tested to help fight blazes during B.C. wildfire season". CTVNews. Retrieved 2020-05-01.
  34. ^ Reuters, Jeremy Berke. "Firefighters are using drones to fight the raging wildfire in Alberta". Business Insider. Retrieved 2020-05-01. {{cite web}}: |last= has generic name (help)
  35. ^ "Surveying the Fury: Drones Assess Costs of 2017 BC Wildfires". UBC Faculty of Forestry. 2017-12-15. Retrieved 2020-05-01.
  36. ^ "Researchers develop drone-based wildfire early warning system". Canadian Science Publishing. Retrieved 2020-05-01.
  37. ^ "Autonomous drone gets the goods on forest fires". New Atlas. 2019-06-19. Retrieved 2020-05-01.
  38. ^ a b "Unmanned Aircraft Systems use on wildfires - InciWeb the Incident Information System". inciweb.nwcg.gov. Retrieved 2020-05-01.
  39. ^ a b "AGENCIES URGE PUBLIC NOT TO FLY DRONES OVER OR NEAR WILDFIRES TO PREVENT ACCIDENTS AND DISRUPTION OF SUPPRESSION OPERATIONS." National Interagency Fire Center. Retrieved 2020-05-01.
  40. ^ "Unauthorized Drones Interrupt Efforts to Fight California Wildfire". The Weather Channel. Retrieved 2020-05-01.
  41. ^ Meyer, Robinson (2018-06-16). "Someone Flew a Drone Too Close to a Wildfire, Again". The Atlantic. Retrieved 2020-05-01.
  42. ^ "Keep drones grounded this spring wildfire season : Apr 2, 2020 | News Release". Minnesota Department of Natural Resources. Retrieved 2020-05-01.

Further reading

  1. D. S. Thomas, D. T. Butry, S. W. Gilbert, D. H. Webb, and J. F. Fung, “The Costs and Losses of Wildfires,” National Institute of Standard and Technology (NIST), Tech. Rep., 11 2017.
  2. W. Ladrach, “The effects of fire in agriculture and forest ecosystems,” ISTF NEWS, June 2009.
  3. USDA, “Forest service wildland fire suppression costs exceed $2 billion.” https://www.usda.gov/media/press-releases/2017/09/14/forest-service-wildlandfire-suppression-costs-exceed-2-billion, 2017.
  4. R. Allison, J. Johnston, G. Craig, and S. Jennings, “Airborne optical and thermal remote sensing for wildfire detection and monitoring,” Sensors, vol. 16, no. 8, 2016.
  5. M. Erdelj, E. Natalizio, K. R. Chowdhury, and I. F. Akyildiz, “Help from the sky: Leveraging UAVs for disaster management,” IEEE Pervasive Computing, vol. 16, no. 1, pp. 24–32, Jan 2017.
  6. M. Erdelj and E. Natalizio, “UAV-assisted disaster management: Applications and open issues,” in 2016 International Conference on Computing, Networking and Communications (ICNC), Feb 2016.
  7. “No drone zone,” NIFC [National Interagency Fire Center], Available: https://www.nifc.gov/drones/, 2017.
  8. U. T. Bart Jansen, “NYC firefighters use drone to help battle blaze for first time,” https://www.usatoday.com/story/news/2017/03/08/dronefirefighters/98848038/, March 2017.
  9. C. Yuan, Y. Zhang, and Z. Liu, “A survey on technologies for automatic forest fire monitoring, detection, and fighting using unmanned aerial vehicles and remote sensing techniques,” Canadian Journal of Forest Research, vol. 47, no. 7, pp. 783–792, 2015.
  10. J. R. Mart´ınez-de Dios, L. Merino, A. Ollero, L. M. Ribeiro, and X. Viegas, Multi-UAV Experiments: Application to Forest Fires. Berlin, Heidelberg: Springer Berlin Heidelberg, 2007, pp. 207–228.
  11. H. Cruz, M. Eckert, J. Meneses, and J. Martnez, “Efficient forest fire detection index for application in unmanned aerial systems (UASs),” Sensors, vol. 16, no. 6, p. E893, 2016.
  12. L. Merino, F. Caballero, J. R. M. de Dios, and A. Ollero, “Cooperative fire detection using unmanned aerial vehicles,” in Proceedings of the 2005 IEEE International Conference on Robotics and Automation, April 2005, pp. 1884–1889.
  13. lker Bekmezci, O. K. Sahingoz, and amil Temel, “Flying ad-hoc networks (fanets): A survey,” Ad Hoc Networks, vol. 11, no. 3, pp. 1254 – 1270, 2013.
  14. S. Adams and C. Friedland, “A survey of unmanned aerial vehicle usage for imagery collection in disaster research and management,” Jan. 2011.
  15. H. Peng, A. Razi, F. Afghah, and J. Ashdown, “A unified framework for joint mobility prediction and object profiling of drones in UAV networks,” Journal of Communications and Networks, vol. 20, no. 5, pp. 434–442, Oct 2018.
  16. A. Shamsoshoara, M. Khaledi, F. Afghah, A. Razi, and J. Ashdown, “Distributed cooperative spectrum sharing in uav networks using multi-agent reinforcement learning,” in 2019 16th IEEE Annual Consumer Communications Networking Conference (CCNC), Jan 2019, pp. 1–6.
  17. M. Khaledi, A. Rovira-Sugranes, F. Afghah, and A. Razi, “On greedy routing in dynamic uav networks,” in 2018 IEEE International Conference on Sensing, Communication and Networking (SECON Workshops), June 2018, pp. 1–5.
  18. J. Chakareski, S. Naqvi, N. Mastronarde, J. Xu, F. Afghah, and A. Razi, “An energy efficient framework for UAV-assisted millimeter wave 5G heterogeneous cellular networks,” IEEE Transactions on Green Communications and Networking, Jan. 2019.
  19. S. Naqvi, J. Chakareski, N. Mastronarde, J. Xu, F. Afghah, and A. Razi, “Energy Efficiency Analysis of UAV-Assisted mmWave HetNets,” in 2018 IEEE Int’l Conf. Communications, May 2018, pp. 1–6.
  20. A. Korenda, M. Z. Amirani, and F. Afghah, “A hierarchical stackelberg-coalition formation game theoretic framework for cooperative spectrum leasing,” in 51th Annual Conference on Information Systems and Sciences (CISS’17), March 2017.
  21. A. Razi, F. Afghah, and A. Abedi, “Channel-adaptive packetization policy for minimal latency and maximal energy efficiency,” IEEE Transactions on Wireless Communications, vol. 15, no. 3, pp. 2407–2420, March 2016.
  22. J. Chakareski, “Aerial UAV-IoT sensing for ubiquitous immersive communication and virtual human teleportation,” in Proc. INFOCOM Workshop on Communication and Networking Techniques for Contemporary Video. Atlanta, GA, USA: IEEE, May 2017, pp. 718–723.
  23. “Drone networks for virtual human teleportation,” in Proc. ACM MobiSys Workshop on Micro Aerial Vehicle Networks, Systems, and Applications (DroNet), Niaga Falls, NY, USA, Jun. 2017, pp. 21–26.
  24. “VR/AR immersive communication: Caching, edge computing, and transmission trade-offs,” in Proc. ACM SIGCOMM Workshop on Virtual Reality and Augmented Reality Network, Aug. 2017.
  25. J. Chakareski, V. Velisavljevic, and V. Stankovi ´ c, “User-action-driven view and rate scalable multiview video coding,” ´ IEEE Transactions on Image Processing, vol. 22, no. 9, pp. 3473–3484, Sep. 2013.
  26. J. Chakareski, “Uplink scheduling of visual sensors: When view popularity matters,” IEEE Transaction on Communications, Feb. 2015.
  27. A. Razi, F. Afghah, and J. Chakareski, “Optimal measurement policy for predicting UAV network topology,” in 51th Asilomar Conference on Signals, Systems and Computers (Asilomar’17), November 2017. 8
  28. F. Afghah, A. Shamsoshoara, L. Njilla, and C. Kamhoua, “A reputation-based stackelberg game model to enhance secrecy rate in spectrum leasing to selfish iot devices,” in IEEE INFOCOM 2018-IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS). IEEE, 2018, pp. 312–317.
  29. E. Schneider, O. Balas, A. T. Ozgelen, E. I. Sklar, and S. Parsons, “An empirical evaluation of auction-based task allocation in multi-robot teams,” in Proc. Int’l Conf. on Autonomous Agents and Multi-agent Systems, 2014, pp. 1443–1444.
  30. G. Korsah, A. Stentz, and M. Dias, “A comprehensive taxonomy for multi-robot task allocation,” The International Journal of Robotic Research, vol. 32, no. 12, pp. 1495–1512, 2013.
  31. B. Ghazanfari, F. Afghah, and M. E. Taylor, “Autonomous extraction of a hierarchical structure of tasks in reinforcement learning, A sequential associate rule mining approach,” CoRR, vol. abs/1811.08275, 2018. [Online]. Available: http://arxiv.org/abs/1811.08275
  32. B. Ghazanfari and N. Mozayani, “Enhancing Nash Q-learning and team Q-learning mechanisms by using bottlenecks,” Journal of Intelligent & Fuzzy Systems, vol. 26, no. 6, pp. 2771–2783, 2014.
  33. A. Shamsoshoara and Y. Darmani, “Enhanced multi-route ad hoc on-demand distance vector routing,” in 2015 23rd Iranian Conference on Electrical Engineering. IEEE, 2015, pp. 578–583.
  34. A. Shamsoshoara, “Overview of blakley’s secret sharing scheme,” arXiv preprint arXiv:1901.02802, 2019.
  35. S. S. Mousavi, M. Schukat, and E. Howley, “Traffic light control using deep policy-gradient and value-function-based reinforcement learning,” IET Intelligent Transport Systems, vol. 11, no. 7, pp. 417–423, 2017.
  36. S. Mousavi, M. Schukat, E. Howley, A. Borji, and N. Mozayani, “Learning to predict where to look in interactive environments using deep recurrent q-learning,” arXiv preprint arXiv:1612.05753, 2016.
  37. B. Ghazanfari and N. Mozayani, “Extracting bottlenecks for reinforcement learning agent by holonic concept clustering and attentional functions,” Expert Systems with Applications, vol. 54, pp. 61 – 77, 2016. [Online]. Available: http://www.sciencedirect.com/science/article/pii/S0957417416000403
  38. A. Shamsoshoara, “Ring oscillator and its application as physical unclonable function (puf) for password management,” arXiv preprint arXiv:1901.06733, 2019.
  39. S. S. Mousavi, M. Schukat, and E. Howley, “Deep reinforcement learning: an overview,” in Proceedings of SAI Intelligent Systems Conference. Springer, 2016, pp. 426–440.
  40. F. Afghah, M. Zaeri-Amirani, A. Razi, J. Chakareski, and E. Bentley, “A coalition formation approach to coordinated task allocation in heterogeneous (UAV) networks,” in IEEE American Control Conference (ACC’18), June 2018.
  41. S. Mousavi, F. Afghah, J. D. Ashdown, and K. Turck, “Leader-follower based coalition formation in large-scale uav networks, a quantum evolutionary approach,” in IEEE INFOCOM 2018 - IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS), April 2018, pp. 882–887.
  42. P. Li and H. Duan, “A potential game approach to multiple uav cooperative search and surveillance,” Aerospace Science and Technology, vol. 68, pp. 403 – 415, 2017. [Online]. Available: http://www.sciencedirect.com/science/article/pii/S1270963817309422
  43. S. Mousavi, F. Afghah, J. D. Ashdown, and K. Turck, “Use of a quantum genetic algorithm for coalition formation in large-scale UAV networks,” Ad Hoc Networks, vol. 87, pp. 26 – 36, 2019. [Online]. Available: http://www.sciencedirect.com/science/article/pii/S1570870518303044
  44. L. Ruan, J. Chen, Q. Guo, H. Jiang, Y. Zhang, and D. Liu, “A coalition formation game approach for efficient cooperative multi-uav deployment,” Appl. Sci., vol. 8, no. 2427, 2018.
  45. T. Rahwan and N. Jennings, “An improved dynamic programming algorithm for coalition structure generation,” in 7th International Conference on Autonomous Agents and Multiagent Systems, 2008.
  46. F. Cruz-Menca, J. Cerquides, and A. Espinosa, “Optimizing performance for coalition structure generation problems idp algorithm,” in 2013 International Conference on Parallel and Distributed Processing Techniques and Applications, 2013.
  47. L. Sless, N. Hazon, S. Kraus, and M. Wooldridge, “Forming coalitions and facilitating relationships for completing tasks in social networks,” in 13th International Conference on Autonomous Agents and Multiagent Systems, 2014.
  48. F. Bistaffa, A. Farinelli, J. Cerquides, J. Rodriguez-Aguilar, and S. D. Ramchurn, “Anytime coalition structure generation on synergy graphs,” in 13th International Conference on Autonomous Agents and Multiagent Systems, 2014.

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