Indoor Localization within Multi-Story Buildings Using MAC and RSSI Fingerprint Vectors

Area of Science:

• Wireless communication
• Indoor positioning systems
• Signal processing

Background:

• Fingerprint localization using Received Signal Strength Indicator (RSSI) is common for indoor positioning.
• Existing methods often overlook Media Access Control (MAC) addresses, focusing primarily on RSSI for Received Signal Strength Indicator (RSSI) value improvements.
• There is a need for enhanced indoor localization techniques, especially within multi-story buildings.

Purpose of the Study:

• To develop a novel indoor positioning approach for multi-story buildings.
• To integrate both Received Signal Strength Indicator (RSSI) and Media Access Control (MAC) addresses for improved localization.
• To enhance the efficiency and accuracy of indoor positioning through MAC address-based clustering.

Main Methods:

• A two-step approach: first, floor identification using distinct MAC addresses across floors.
• Second, precise localization within the identified floor.
• Incorporation of clustering using MAC addresses during the online positioning phase.

Main Results:

• Achieved precise horizontal localization accuracy of 1.8 meters.
• Successfully identified the correct floor within multi-story buildings.
• Demonstrated improved efficiency and accuracy through MAC address-based clustering.

Conclusions:

• The proposed method effectively integrates MAC addresses and RSSI for accurate indoor positioning in multi-story buildings.
• The floor identification step using MAC addresses is a key innovation.
• MAC address clustering enhances the performance of online positioning algorithms.