SwarmMind™ Ltd

Decentralised Intelligence | Emergent Solutions | Custom swarm solutions for every challenge | Multi-agent systems that self-organise and scale

Publications

  1. M. Tavakol Sadrabadi, & M.S. Innocente (2026). Stochastic near-surface wind field estimation from sparse aerial swarm measurements to support wildfire behaviour predictions. Applied Soft Computing, 189, 114478, Elsevier.
    DOI: 10.1016/j.asoc.2025.114478
    Temporary Open Access here.
  2. M. Tavakol Sadrabadi, J. Peiró, M.S. Innocente, & G. Rein (2025). Conceptual design of a wildfire emergency response system empowered by swarms of unmanned aerial vehicles. International Journal of Disaster Risk Reduction, 124, 105493, Elsevier.
    DOI: 10.1016/j.ijdrr.2025.105493.
  3. M. Tavakol Sadrabadi, & M.S. Innocente (2025). To cut or not to cut: Effect of vegetation height and bulk density on wildfire propagation under varying wind and slope conditions. International Journal of Disaster Risk Reduction, 121, 105372, Elsevier.
    DOI: https://doi.org/10.1016/j.ijdrr.2025.105372.
  4. I. Papagiannis, M.S. Innocente, J.D. Davies, J.L. Ryan, & E.I. Gkanas (2024). Investigating the impact of Iron Oxide Nanoparticles on the stability of Class A foam for wildfire suppression. Fire Safety Journal, 150, Part A, Elsevier.
    DOI: 10.1016/j.firesaf.2024.104282.
  5. M. Tavakol Sadrabadi, & M.S. Innocente (2024). Enhancing Wildfire Propagation Model Predictions Using Aerial Swarm-Based Real-Time Wind Measurements: A Conceptual Framework. Applied Mathematical Modelling, 130, 615–634, Elsevier.
    DOI: 10.1016/j.apm.2024.03.012.
  6. M. Tavakol Sadrabadi, & M.S. Innocente (2023). Vegetation Cover Type Classification Using Cartographic Data for Prediction of Wildfire Behaviour. Fire, 6, no. 2: 76, MDPI.
    DOI: 10.3390/fire6020076.
  7. P. Grasso, M.S. Innocente, J.J. Tai, O. Haas, & A.M. Dizqah (2022). Analysis and Accuracy Improvement of UWB-TDoA-Based Indoor Positioning System. Sensors, 22, no. 23: 9136, MDPI.
    DOI: 10.3390/s22239136.
  8. M. Tavakol Sadrabadi, M.S. Innocente, E.I. Gkanas, & I. Papagiannis (2022). Comparison of the effect of one-way and two-way fire-wind coupling on the modelling of wildland fire propagation dynamics. In: Viegas, D.X., Ribeiro, L.M. (eds.) Advances in Forest Fire Research 2022 (115–121). Imprensa da Universidade de Coimbra.
    DOI: 10.14195/978-989-26-2298-9_18.
  9. I. Papagiannis, M.S. Innocente, & E.I. Gkanas (2022). Synthesis and Characterisation of Iron Oxide Nanoparticles with Tunable Sizes by Hydrothermal Method. In Materials Science Forum, 1053, 176–181, Trans Tech Publications Ltd.
    DOI: 10.4028/p-0so8ha
  10. P. Grasso, & M.S. Innocente (2022). Stigmergy-based collision-avoidance algorithm for autonomous firefighting drone swarms. Accepted for publication in: Proceedings of fifth International Conference on Computational Vision and Bio Inspired Computing. Advances in Intelligent Systems and Computing, Springer-Nature.
    DOI: 10.1007/978-981-16-9573-5_19
  11. P. Grasso, & M.S. Innocente (2020). Physics-based model of wildfire propagation towards faster-than-real-time simulations. Computers and Mathematics with Applications, 80, 790–808, Elsevier.
    DOI: 10.1016/j.camwa.2020.05.009
  12. P. Grasso, & M.S. Innocente (2020). Debiasing of position estimations of UWB-based TDoA indoor positioning system. In Proceedings of the 2020 UK-RAS Conference: ‘Robots into the Real World’, Lincoln, UK (virtual), 2020.
    DOI: 10.31256/Ua2Vp3X
  13. P. Grasso, & M.S. Innocente (2020). Theoretical study of signal and geometrical properties of two-dimensional UWB-based indoor positioning systems using TDoA. In Proceedings of the 6th International Conference on Mechatronics and Robotics Engineering, Barcelona, Spain, 2020, IEEE.
    DOI: 10.1109/ICMRE49073.2020.9065121
  14. M.S. Innocente, & P. Grasso (2019). Self-organising swarms of firefighting drones: Harnessing the power of collective intelligence in decentralised multi-robot systems. Journal of Computational Science, 34, 80–101, Elsevier.
    DOI: 10.1016/j.jocs.2019.04.009
  15. P. Grasso, & M.S. Innocente (2018). A two-dimensional reaction-advection-diffusion model of the spread of fire in wildlands. In Advances in Forest Fire Research 2018 (pp. 334–342). Imprensa da Universidade de Coimbra.
    DOI: 10.14195/978-989-26-16-506_36
  16. M.S. Innocente, & P. Grasso (2018). Swarm of autonomous drones self-organised to fight the spread of wildfires. In Proceedings of the GEOSAFE Workshop on Robust Solutions for Fire Fighting (Vol. 2146), L’Aquila, Italy, 2018. CEUR.
  17. M.S. Innocente, & P. Grasso (2018). Proof-of-Concept Swarm of Self-Organising Drones Aimed at Fighting Wildfires. In Proceedings of the 2017 UK-RAS Conference: ‘Robots Working for and among Us’, pp. 102–105, Bristol, UK, 2017.