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Geographic Information System (GIS) technology is essential for risk identification, action prioritization, and resource optimization in critical situations like flooding and earthquakes. By integrating spatial and demographic data, GIS provides a comprehensive framework for emergency response.GIS integrates data layers, like rainfall intensity, topography, elevation profiles, and river levels, to model high-risk flood zones. These layers assess areas susceptible to flooding based on their...
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A Distributed Multi-Tier Emergency Alerting System Exploiting Sensors-Based Event Detection to Support Smart City

Daniel G Costa1, Francisco Vasques2, Paulo Portugal2

  • 1Department of Technology, State University of Feira de Santana, Feira de Santana 44036-900, Brazil.

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|January 2, 2020
PubMed
Summary
This summary is machine-generated.

This study introduces a novel distributed multi-tier emergency alerting system for smart cities. It enhances real-time event detection and alarm generation using multiple sensors and GPS data, improving urban safety.

Keywords:
Internet of Thingsemergency alertingevent detectionsensors monitoringsmart cities

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Area of Science:

  • Computer Science
  • Electrical Engineering
  • Urban Planning

Background:

  • The Internet of Things (IoT) has enabled numerous sensor-based monitoring applications for environmental perception and emergency detection.
  • Existing IoT emergency systems for smart cities are limited by single-variable monitoring and high computational demands on sensor nodes.

Purpose of the Study:

  • To propose a distributed, multi-tier emergency alerting system for smart cities.
  • To address the limitations of current IoT-based emergency systems by incorporating multiple data inputs and reducing computational burden.

Main Methods:

  • Developed a distributed multi-tier system with sensor-based event detection units.
  • Integrated configurable scalar sensors and GPS data for real-time, georeferenced event information.
  • Computed emergency alarms based on detected events, area risk levels, and temporal data.
  • Implemented the system on open-source electronic platforms and created a real-time map visualization application.

Main Results:

  • The system provides modular and flexible perceptions of critical events tailored to smart city scenarios.
  • Demonstrated a feasible and useful application as a supporting service for smart cities.
  • Achieved real-time georeferenced information and dynamic display of emergency alarms on a map.

Conclusions:

  • The proposed system offers an innovative approach to enhance smart city emergency preparedness.
  • It supports the development of adaptive, IoT-based emergency-aware applications.
  • This implementation can yield valuable results for improving urban safety and response.