Smartphone-Based Real-Time Indoor Location Tracking With 1-m Precision.

Area of Science:

• * Geriatric care technology
• * Indoor positioning systems
• * Sensor fusion for healthcare

Background:

• * Monitoring elderly daily living activities at home is crucial for early detection of health changes.
• * Existing indoor location tracking systems lack the necessary accuracy for reliable home monitoring.
• * Limitations in current systems hinder effective remote patient care and health surveillance.

Purpose of the Study:

• * To develop an accurate indoor localization system for real-time patient tracking in home environments.
• * To achieve a maximum estimation error of 2 meters at a 95% confidence level.
• * To create a system that is low-cost, non-intrusive, mobile, deployable, and portable.

Main Methods:

• * Implemented a sensor fusion approach combining an iPhone 5's accelerometer and compass for step detection.
• * Developed a radio-based localization subsystem utilizing Kalman filters and Received Signal Strength Indication (RSSI).
• * Focused on overcoming accuracy limitations of existing indoor tracking technologies.

Main Results:

• * The proof-of-concept system demonstrated promising results in experimental settings.
• * Achieved a highly accurate average estimation error of 0.47 meters.
• * Indicated significant potential for improving indoor localization accuracy.

Conclusions:

• * The proposed sensor fusion localization system offers a viable solution for elderly home monitoring.
• * The design considerations enhance mobility, portability, and reduce intrusiveness.
• * Future work aims to adapt the system for robust localization in realistic home environments.