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Where There Is Fire There Is SMOKE: A Scalable Edge Computing Framework for Early Fire Detection.

Marios Avgeris1, Dimitrios Spatharakis2, Dimitrios Dechouniotis3

  • 1School of Electrical and Computer Engineering, National Technical University of Athens-NTUA, GR 157 80 Zografou, Greece. mavgeris@netmode.ntua.gr.

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Summary

This study introduces a Cyber-Physical Social System (CPSS) for early fire detection using IoT nodes and crowd sensing. Dynamic resource scaling in the Edge Computing layer improves performance and conserves energy for critical applications.

Keywords:
IoT nodescontrol theorycyber-physical social systemedge computingfire detectionresource scalingsocial media

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Area of Science:

  • Cyber-Physical Social Systems (CPSS)
  • Internet of Things (IoT)
  • Edge Computing
  • Cloud Computing
  • Social Media Analytics

Background:

  • Early fire detection is crucial for emergency response and public safety.
  • Existing systems face challenges with data processing, energy constraints, and real-time decision-making.
  • Integrating diverse data sources, including crowd sensing and social media, can enhance situational awareness.

Purpose of the Study:

  • To present a three-level Cyber-Physical Social System (CPSS) for effective early fire detection.
  • To design a dynamic resource scaling mechanism for the Edge Computing Infrastructure to meet Quality of Service (QoS) demands.
  • To evaluate the impact of resource scaling on system performance and energy consumption.

Main Methods:

  • Developed a three-level CPSS architecture integrating IoT nodes, crowd sensing, Edge Computing, and Cloud-based decision-making.
  • Implemented a dynamic resource scaling mechanism (vertical and horizontal) for the Edge Computing layer.
  • Utilized IoT nodes for forest monitoring and end-user devices for crowd sensing environmental data.
  • Integrated social media data with sensor information for comprehensive situation assessment.

Main Results:

  • The proposed CPSS effectively assists public authorities in prompt identification and response to fire emergencies.
  • Dynamic resource scaling on the Edge Computing layer significantly improved system performance.
  • Resource scaling led to a reduction in energy consumption for the IoT nodes.
  • The integration of crowd sensing and social media data enhanced the criticality evaluation of fire situations.

Conclusions:

  • The three-level CPSS architecture provides a robust framework for time- and mission-critical applications like early fire detection.
  • Dynamic resource scaling in Edge Computing is essential for optimizing performance and energy efficiency in IoT-enabled systems.
  • Leveraging crowd sensing and social media data within a CPSS framework enhances emergency response capabilities.