Publications and Research
Document Type
Poster
Publication Date
5-9-2024
Abstract
Real-time indoor location tracking is indispensable for numerous applications spanning healthcare equipment management, security, navigation, and smart building operations. However, accurately determining the relationship between location and signal strength can be challenging due to indoor multipath phenomena. In this study, we propose an approach to address this challenge by developing a robot car using the GoPiGo3 Raspberry Pi kit. The robot car will navigate indoor environments autonomously, continuously transmitting timestamped coordinate data to a software platform. Leveraging advanced data analysis techniques, we aim to uncover hidden patterns within the collected data, elucidating the intricate relationship between location and signal strength in indoor settings. By clarifying these relationships, our study seeks to enhance the efficacy of real-time indoor location tracking systems, thereby improving their utility across a wide array of applications.
Comments
This poster was presented at the 40th Semi-Annual Dr. Janet Liou-Mark Honors & Undergraduate Research Poster Presentation, May 9, 2024. Mentor: Prof. Li Geng (Electrical & Telecommunications Engineering Technology).