research-article

Collective intelligence and bush fire spotting

Authors:

David Howden,

Tim HendtlassAuthors Info & Claims

GECCO '08: Proceedings of the 10th annual conference on Genetic and evolutionary computation

Pages 41 - 48

https://doi.org/10.1145/1389095.1389102

Published: 12 July 2008 Publication History

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Abstract

Bush fires cause major damage each year in many areas of the world and the earlier that they can be detected the easier it is to minimize this damage. This paper describes a collective intelligence algorithm that performs localized rather than centralized control of a number of unmanned aerial vehicles (UAV) that can survey complex areas for fires, devoting attention in proportion to the user specified importance of each area. Simulation shows that not only is the algorithm able to perform this action successfully, it is also able to automatically adapt to a simulated malfunction in one of the UAVs.

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Alsammak IMahmoud MAris HAlKilabi MMahdi M(2022)The Use of Swarms of Unmanned Aerial Vehicles in Mitigating Area Coverage Challenges of Forest-Fire-Extinguishing Activities: A Systematic Literature ReviewForests10.3390/f1305081113:5(811)Online publication date: 23-May-2022
https://doi.org/10.3390/f13050811
Panahi FPanahi FOhtsuki T(2022)A Reinforcement Learning-based Fire Warning and Suppression System Using Unmanned Aerial VehiclesIEEE Transactions on Instrumentation and Measurement10.1109/TIM.2022.3227558(1-1)Online publication date: 2022
https://doi.org/10.1109/TIM.2022.3227558
Narayanan AKorium MMelgarejo DHussain HDe Sena AGoria Silva PGutierrez-Rojas DUllah MEsmaeel Nezhad ARasti MPournaras ENardelli P(2022)Collective Intelligence Using 5G: Concepts, Applications, and Challenges in Sociotechnical EnvironmentsIEEE Access10.1109/ACCESS.2022.318403510(70394-70417)Online publication date: 2022
https://doi.org/10.1109/ACCESS.2022.3184035
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Index Terms

Collective intelligence and bush fire spotting
1. Applied computing
2. Information systems
  1. Information systems applications
    1. Decision support systems
      1. Expert systems

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GECCO '08: Proceedings of the 10th annual conference on Genetic and evolutionary computation

July 2008

1814 pages

ISBN:9781605581309

DOI:10.1145/1389095

Conference Chair:
Conor Ryan
University of Limerick, Ireland
,
Editor:
Maarten Keijzer
Chordiant Software International B.V., The Netherlands

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

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Published: 12 July 2008

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GECCO08: Genetic and Evolutionary Computation Conference

July 12 - 16, 2008

GA, Atlanta, USA

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Overall Acceptance Rate 1,669 of 4,410 submissions, 38%

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Alsammak IMahmoud MAris HAlKilabi MMahdi M(2022)The Use of Swarms of Unmanned Aerial Vehicles in Mitigating Area Coverage Challenges of Forest-Fire-Extinguishing Activities: A Systematic Literature ReviewForests10.3390/f1305081113:5(811)Online publication date: 23-May-2022
https://doi.org/10.3390/f13050811
Panahi FPanahi FOhtsuki T(2022)A Reinforcement Learning-based Fire Warning and Suppression System Using Unmanned Aerial VehiclesIEEE Transactions on Instrumentation and Measurement10.1109/TIM.2022.3227558(1-1)Online publication date: 2022
https://doi.org/10.1109/TIM.2022.3227558
Narayanan AKorium MMelgarejo DHussain HDe Sena AGoria Silva PGutierrez-Rojas DUllah MEsmaeel Nezhad ARasti MPournaras ENardelli P(2022)Collective Intelligence Using 5G: Concepts, Applications, and Challenges in Sociotechnical EnvironmentsIEEE Access10.1109/ACCESS.2022.318403510(70394-70417)Online publication date: 2022
https://doi.org/10.1109/ACCESS.2022.3184035
Ahmed FMohanta JKeshari AYadav P(2022)Recent Advances in Unmanned Aerial Vehicles: A ReviewArabian Journal for Science and Engineering10.1007/s13369-022-06738-047:7(7963-7984)Online publication date: 25-Apr-2022
https://doi.org/10.1007/s13369-022-06738-0
Gayathri Devi KYasoda KRoy M(2022)Automatic Firefighting System Using Unmanned Aerial VehicleInternational Conference on Artificial Intelligence for Smart Community10.1007/978-981-16-2183-3_97(1023-1031)Online publication date: 14-Nov-2022
https://doi.org/10.1007/978-981-16-2183-3_97
Bjurling OGranlund RAlfredson JArvola MZiemke TLamas DSarapuu HŠmorgun IBerget G(2020)Drone Swarms in Forest Firefighting: A Local Development Case Study of Multi-Level Human-Swarm InteractionProceedings of the 11th Nordic Conference on Human-Computer Interaction: Shaping Experiences, Shaping Society10.1145/3419249.3421239(1-7)Online publication date: 25-Oct-2020
https://dl.acm.org/doi/10.1145/3419249.3421239
Aydin BSelvi ETao JStarek M(2019)Use of Fire-Extinguishing Balls for a Conceptual System of Drone-Assisted Wildfire FightingDrones10.3390/drones30100173:1(17)Online publication date: 12-Feb-2019
https://doi.org/10.3390/drones3010017
Vera L. J. SManchester I(2019)Priority Maps for Surveillance and Intervention of Wildfires and other Spreading Processes2019 International Conference on Robotics and Automation (ICRA)10.1109/ICRA.2019.8793874(739-745)Online publication date: May-2019
https://doi.org/10.1109/ICRA.2019.8793874
Li W(2014)Persistent surveillance for a swarm of micro aerial vehicles by flocking algorithmProceedings of the Institution of Mechanical Engineers, Part G: Journal of Aerospace Engineering10.1177/0954410014529100229:1(185-194)Online publication date: 28-Mar-2014
https://doi.org/10.1177/0954410014529100
Varela GCaamaño POrjales FDeibe ÁLópez-Peña FDuro R(2014)Autonomous UAV based search operations using Constrained Sampling Evolutionary AlgorithmsNeurocomputing10.1016/j.neucom.2013.03.060132(54-67)Online publication date: 1-May-2014
https://dl.acm.org/doi/10.1016/j.neucom.2013.03.060
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Collective Intelligence: from the Enlightenment to the Crowd Science

A Sociopsychological Perspective on Collective Intelligence in Metaheuristic Computing

Collective Attention and Collective Intelligence: The Role of Hierarchy and Team Gender Composition

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