AEDNav: indoor navigation for locating automated external defibrillator.

Area of Science:

• Computer Science
• Biomedical Engineering
• Emergency Medicine

Background:

• Sudden cardiac arrest necessitates immediate CPR and AED use.
• Existing AED locator apps lack indoor navigation, hindering timely access.
• Current indoor navigation systems are often impractical due to hardware or data requirements.

Purpose of the Study:

• To develop a practical indoor navigation system for locating Automated External Defibrillators (AEDs).
• To enhance patient survival rates during sudden cardiac arrest by reducing AED retrieval time.

Main Methods:

• The AEDNav system utilizes smartphone-collected Wi-Fi and magnetic field data.
• Four techniques (turn detection, magnetic pattern matching, Wi-Fi fingerprinting, closest Wi-Fi) estimate user location.
• Fusion of these techniques refines location accuracy for indoor navigation.

Main Results:

• Individual methods achieved up to 80% accuracy with varying error distances.
• The combined system demonstrated robust performance with 80% accuracy and a ±2.74m error distance.
• The proposed system outperforms existing Wi-Fi and magnetic data-based navigation solutions.

Conclusions:

• AEDNav offers a novel, low-infrastructure approach to indoor navigation.
• The system achieves accuracy comparable to existing solutions without special hardware or extensive data.
• Successful implementation of AEDNav can significantly decrease AED location time, improving cardiac arrest survival outcomes.