Self-Organising Drone Swarms for Detection and Monitoring of Wildfires

Sebastian Coffeng; Hanno Hildmann; Hannu Karvonen; Fabrice Saffre

doi:10.1007/978-3-032-19008-6_7

Self-Organising Drone Swarms for Detection and Monitoring of Wildfires

Sebastian Coffeng
, Hanno Hildmann
, Hannu Karvonen^*
, Fabrice Saffre

^*Corresponding author for this work

Netherlands Organisation for Applied Scientific Research (TNO)
The Hague University of Applied Sciences

Research output: Chapter in Book/Report/Conference proceeding › Chapter or book article › Scientific › peer-review

Abstract

This chapter investigates the use of multiple unmanned platforms (a swarm) for environmental sensing. The use-case is that of wildfire detection and monitoring. The contribution of this chapter is theoretical in nature, the results are collected from simulations and numerical experiments. Specifically, the impact of varying communication ranges is explored with regard to the individual performances for the search and the monitoring-task as well as the use of communication range as a control parameter for the trade-off between exploration and exploitation.

Original language	English
Title of host publication	DroneAI for Resilient Nature
Editors	Mika-Petri Laakkonen
Publisher	Springer Nature
Pages	88-107
Number of pages	20
Volume	1
ISBN (Electronic)	9783032190086
ISBN (Print)	9783032190079
DOIs	https://doi.org/10.1007/978-3-032-19008-6_7
Publication status	Published - 2026
MoE publication type	A3 Part of a book or another research book
Event	Findrones 2024 - Oulu, Oulu, Finland Duration: 5 Nov 2024 → 6 Nov 2024

Conference

Conference	Findrones 2024
Country/Territory	Finland
City	Oulu
Period	5/11/24 → 6/11/24

Keywords

Autonomous drone swarms
Decentralization
Detection
Environmental monitoring
Local information sharing
Search algorithms
Self-organization
Swarm intelligence
Wildfire

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10.1007/978-3-032-19008-6_7

Cite this

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title = "Self-Organising Drone Swarms for Detection and Monitoring of Wildfires",

abstract = "This chapter investigates the use of multiple unmanned platforms (a swarm) for environmental sensing. The use-case is that of wildfire detection and monitoring. The contribution of this chapter is theoretical in nature, the results are collected from simulations and numerical experiments. Specifically, the impact of varying communication ranges is explored with regard to the individual performances for the search and the monitoring-task as well as the use of communication range as a control parameter for the trade-off between exploration and exploitation.",

keywords = "Autonomous drone swarms, Decentralization, Detection, Environmental monitoring, Local information sharing, Search algorithms, Self-organization, Swarm intelligence, Wildfire",

author = "Sebastian Coffeng and Hanno Hildmann and Hannu Karvonen and Fabrice Saffre",

year = "2026",

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language = "English",

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AU - Coffeng, Sebastian

AU - Hildmann, Hanno

AU - Karvonen, Hannu

AU - Saffre, Fabrice

PY - 2026

Y1 - 2026

N2 - This chapter investigates the use of multiple unmanned platforms (a swarm) for environmental sensing. The use-case is that of wildfire detection and monitoring. The contribution of this chapter is theoretical in nature, the results are collected from simulations and numerical experiments. Specifically, the impact of varying communication ranges is explored with regard to the individual performances for the search and the monitoring-task as well as the use of communication range as a control parameter for the trade-off between exploration and exploitation.

AB - This chapter investigates the use of multiple unmanned platforms (a swarm) for environmental sensing. The use-case is that of wildfire detection and monitoring. The contribution of this chapter is theoretical in nature, the results are collected from simulations and numerical experiments. Specifically, the impact of varying communication ranges is explored with regard to the individual performances for the search and the monitoring-task as well as the use of communication range as a control parameter for the trade-off between exploration and exploitation.

KW - Autonomous drone swarms

KW - Decentralization

KW - Detection

KW - Environmental monitoring

KW - Local information sharing

KW - Search algorithms

KW - Self-organization

KW - Swarm intelligence

KW - Wildfire

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DO - 10.1007/978-3-032-19008-6_7

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VL - 1

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BT - DroneAI for Resilient Nature

A2 - Laakkonen, Mika-Petri

PB - Springer Nature

T2 - Findrones 2024

Y2 - 5 November 2024 through 6 November 2024

ER -

Self-Organising Drone Swarms for Detection and Monitoring of Wildfires

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Keywords

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