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Emergency navigation without an infrastructure.

Erol Gelenbe1, Huibo Bi2

  • 1Intelligent Systems and Networks Group, Department of Electrical and Electronic Engineering, Imperial College London, London SW7 2BT, UK. e.gelenbe@imperial.ac.uk.

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Summary
This summary is machine-generated.

This study introduces a cloud-enabled framework using smartphones for indoor emergency navigation. It enhances evacuation by guiding people in clusters and improving communication reliability, boosting survival rates.

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Area of Science:

  • Computer Science
  • Electrical Engineering
  • Emergency Management

Background:

  • Traditional emergency navigation systems using wireless sensor networks (WSNs) have limited computing power and battery life.
  • Integrating WSNs with cloud computing offloads computation but retains client-side battery and reliability issues.
  • Ubiquitous smartphones offer powerful sensing capabilities for improved emergency navigation.

Purpose of the Study:

  • To present a cloud-enabled indoor emergency navigation framework leveraging smartphone sensing capabilities.
  • To enhance the reliability and resilience of communication and localization during building evacuations.
  • To guide evacuees in a coordinated manner using dynamic loose clusters.

Main Methods:

  • Utilized smartphones' sensing abilities within a cloud-enabled framework.
  • Combined social potential fields (SPF) and cognitive packet network (CPN)-based algorithms for guidance.
  • Implemented an ad hoc cognitive packet network (AHCPN) protocol for adaptive communication routing.

Main Results:

  • The proposed framework improves evacuee coordination and navigation.
  • The AHCPN protocol optimizes communication routes, conserving smartphone battery and reducing latency.
  • Simulations demonstrated increased survival rates and reduced smartphone battery drain during evacuations.

Conclusions:

  • Smartphone-based cloud-enabled navigation offers a more reliable and resilient solution for building emergencies.
  • Integrating smart human motion and network management significantly enhances evacuation efficiency.
  • This approach addresses limitations of traditional WSN-based systems and cloud-integrated WSNs.