Multi-agent system of systems to monitor wildfires

Wildfire monitoring and mitigation have been worldwide challenges in disaster reduction for quite a while. However as time goes, more and more acres of virgin forests continue being consumed. A problem like a wildfire can be analyzed from a System of Systems (SoS) point of view. The reason for this is because of the nature of all the involved stakeholders. In this work we discuss the benefits of developing a collaborative collection of systems. Approach that can quickly and effectively locate and track the spread of wildfires. To finish comparing it to monolithic approaches that have been vastly used until now. Agent based modelling (ABM) is used to show the different interaction of each of the different systems including different system network configuration. Our consideration in SoS problem is to find an effective configuration network communication between agents. To discover robustness with limited number of existing agents is also one of the concerns to improve.

[1]  Eric T. Matson,et al.  Using directional antennas as sensors to assist fire-fighting robots in large scale fires , 2014, 2014 IEEE Sensors Applications Symposium (SAS).

[2]  Eric Bonabeau,et al.  Agent-based modeling: Methods and techniques for simulating human systems , 2002, Proceedings of the National Academy of Sciences of the United States of America.

[3]  Aníbal Ollero,et al.  Journal of Intelligent & Robotic Systems manuscript No. (will be inserted by the editor) An Unmanned Aircraft System for Automatic Forest Fire Monitoring and Measurement , 2022 .

[4]  Robert G. Sargent,et al.  Some approaches and paradigms for verifying and validating simulation models , 2001, Proceeding of the 2001 Winter Simulation Conference (Cat. No.01CH37304).

[5]  Baisravan Homchaudhuri,et al.  Cooperative Control of Multiple Uninhabited Aerial Vehicles for Monitoring and Fighting Wildfires , 2011, J. Aerosp. Comput. Inf. Commun..

[6]  Pedro A. C. Sousa,et al.  Architecture and Message Protocol Proposal for Robot's Integration in Multi-Agent Surveillance System , 2014, RSCTC.

[7]  Eric R. Ziegel,et al.  Probability and Statistics for Engineering and the Sciences , 2004, Technometrics.

[8]  Robert L. Axtell,et al.  WHY AGENTS? ON THE VARIED MOTIVATIONS FOR AGENT COMPUTING IN THE SOCIAL SCIENCES , 2000 .

[9]  Daniel DeLaurentis,et al.  A System-of-Systems Perspective for Public Policy Decisions , 2004 .

[10]  Muharrem Mane,et al.  Taxonomy to Guide Systems-of-Systems Decision-Making in Air Transportation Problems , 2011 .