Ebaid, Emad and Navaie, Keivan (2022) Efficient Design of Scalable Indoor Positioning System Based on Wi-Fi Fingerprinting. In: CPS Summer School PhD Workshop 2022. CEUR Workshop Proceedings . CEUR Workshop Proceedings.
Full text not available from this repository.Abstract
Cyber-Physical Systems (CPS) are evolving and gradually building an ecosystem of smart homes, smart cities and automated systems. Indoor Positioning Systems (IPSs) play an essential part in providing location-based services to many demanded applications such as robots, UAVs, shopping malls, health care and more. Indoor positioning based on Wi-Fi is widely used to limit the complexity and cost of the Indoor Positioning System (IPS). This study aims to find an efficient design that makes IPS based on Wi-Fi fingerprinting more simple and scalable to enhance indoor positioning performance. Investigating the IPS system design in indoor settings tries to improve the positioning accuracy of Wi-Fi RSSI-based systems and reduce database-fingerprinting complexity by using cloud-computing architecture for efficient resource management and system scalability.