부산대학교 도서관

Location‐based services have attracted significant attention since the concept of Industry 4.0 was proposed and the ‘Internet +’ era began owing to its social and commercial value. Many scholars have attempted to introduce machine learning in indoor fingerprint positioning to improve indoor positioning accuracy, enhance system robustness, reduce costs, and improve the performance of indoor positioning methods. A comprehensive overview of indoor positioning technology, its methods, and classifications is provided. Furthermore, a detailed review of the application of WiFi fingerprinting and machine learning methods in indoor positioning is presented, and the advantages and disadvantages of these methods when applied to indoor positioning are analyzed. This study summarizes the difficulties and challenges encountered by indoor positioning and suggests development directions.
INTRODUCTION The accuracy of satellite‐based positioning has been demonstrated in the outdoor environment. This creates significant convenience in our daily lives, work, and other scenarios such as navigating cars and [...]