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A Cyber-Physical System for Wildfire Detection and Firefighting

Author

Listed:
  • Pietro Battistoni

    (Department of Computer Science, University of Salerno, 84084 Fisciano, Italy)

  • Andrea Antonio Cantone

    (Department of Computer Science, University of Salerno, 84084 Fisciano, Italy)

  • Gerardo Martino

    (Department of Computer Science, University of Salerno, 84084 Fisciano, Italy)

  • Valerio Passamano

    (Department of Computer Science, University of Salerno, 84084 Fisciano, Italy)

  • Marco Romano

    (Faculty of Political Science and Psychosocial Studies, Università degli Studi Internazionali di Roma—UNINT, 00147 Roma, Italy)

  • Monica Sebillo

    (Department of Computer Science, University of Salerno, 84084 Fisciano, Italy)

  • Giuliana Vitiello

    (Department of Computer Science, University of Salerno, 84084 Fisciano, Italy)

Abstract

The increasing frequency and severity of forest fires necessitate early detection and rapid response to mitigate their impact. This project aims to design a cyber-physical system for early detection and rapid response to forest fires using advanced technologies. The system incorporates Internet of Things sensors and autonomous unmanned aerial and ground vehicles controlled by the robot operating system. An IoT-based wildfire detection node continuously monitors environmental conditions, enabling early fire detection. Upon fire detection, a UAV autonomously surveys the area to precisely locate the fire and can deploy an extinguishing payload or provide data for decision-making. The UAV communicates the fire’s precise location to a collaborative UGV, which autonomously reaches the designated area to support ground-based firefighters. The CPS includes a ground control station with web-based dashboards for real-time monitoring of system parameters and telemetry data from UAVs and UGVs. The article demonstrates the real-time fire detection capabilities of the proposed system using simulated forest fire scenarios. The objective is to provide a practical approach using open-source technologies for early detection and extinguishing of forest fires, with potential applications in various industries, surveillance, and precision agriculture.

Suggested Citation

  • Pietro Battistoni & Andrea Antonio Cantone & Gerardo Martino & Valerio Passamano & Marco Romano & Monica Sebillo & Giuliana Vitiello, 2023. "A Cyber-Physical System for Wildfire Detection and Firefighting," Future Internet, MDPI, vol. 15(7), pages 1-28, July.
    • Handle: RePEc:gam:jftint:v:15:y:2023:i:7:p:237-:d:1188291
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    References listed on IDEAS

    as
    1. Pietro Battistoni & Marco Romano & Monica Sebillo & Giuliana Vitiello, 2023. "Monitoring Urban Happiness through Interactive Chorems," Sustainability, MDPI, vol. 15(11), pages 1-19, May.
    2. Kuldoshbay Avazov & An Eui Hyun & Alabdulwahab Abrar Sami S & Azizbek Khaitov & Akmalbek Bobomirzaevich Abdusalomov & Young Im Cho, 2023. "Forest Fire Detection and Notification Method Based on AI and IoT Approaches," Future Internet, MDPI, vol. 15(2), pages 1-13, January.
    3. Ankita Mohapatra & Timothy Trinh, 2022. "Early Wildfire Detection Technologies in Practice—A Review," Sustainability, MDPI, vol. 14(19), pages 1-21, September.
    4. Marianna Di Gregorio & Marco Romano & Monica Sebillo & Giuliana Vitiello & Angela Vozella, 2021. "Improving Human Ground Control Performance in Unmanned Aerial Systems," Future Internet, MDPI, vol. 13(8), pages 1-16, July.
    Full references (including those not matched with items on IDEAS)

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