A comprehensive algorithm for vertical positioning in multi-building environments as an advancement in indoor...

Area of Science:

• Indoor localization and positioning systems
• Ubiquitous computing and mobile sensing
• Wireless sensor networks and robotics

Background:

• Smartphone proliferation drives demand for indoor localization services across various sectors.
• Existing indoor localization techniques often rely on extensive infrastructure or have limitations in vertical positioning.
• Accurate real-time location tracking is crucial for security, navigation, and emergency response.

Purpose of the Study:

• To propose an innovative, infrastructure-independent indoor location system.
• To enhance indoor tracking accuracy by integrating GPS and barometer readings.
• To enable continuous real-time location updates, including vertical positioning and elevator travel detection.

Main Methods:

• Amalgamation of Global Positioning System (GPS) for entry detection and barometer readings for floor-level tracking.
• Development of an algorithm that leverages smartphone sensors without external infrastructure.
• Utilizing Wi-Fi Access Point (AP) or LTE signals for detecting elevator travel.

Main Results:

• Building entry detection accuracy exceeds 93%.
• Elevator recognition achieves 75% sensitivity and 97% specificity.
• Floor change detection demonstrates over 95% sensitivity and nearly 98% specificity, resulting in approximately 97% overall accuracy.

Conclusions:

• The proposed system offers a highly accurate and versatile solution for indoor localization.
• Precise vertical positioning is achieved using readily available smartphone sensors.
• This advancement improves security, navigation, and emergency response within urban structures.