<> "The repository administrator has not yet configured an RDF license."^^ . <> . . . "Bluetooth Low Energy based Indoor Positioning on iOS platform"^^ . "In this age of IoT (Internet of Things), Indoor\r\nPositioning (IPS) is considered as one of the most popular topicsand has been researched widely all around the world, as the result of various applications it can provide. However, IPS is also a challenging topic that has a number of stringent requirements,such as cost, energy efficiency, availability and accuracy. The\r\ndevelopment of Bluetooth Low Energy (BLE) iBeacon has opened great opportunities for researchers to solve those challenges. In this paper, we present our iBeacon based positioning system, which we built as an application running on iOS platform. We also present Fingerprinting − the main positioning technique used in our system, in which we configure its fingerprints to improve accuracy. With that, a machine learning algorithm called\r\nk-Nearest Neighbor (kNN) is applied to extract the most probable user location. In addition, we also use Kalman Filter in order to enhance the stability of iBeacon’s signal. Our system results in a 60% − 71.4% accuracy rate and an error of up to 1.6 m, which is acceptable in IPS."^^ . "2018-09-12" . . . . . . . . . . . . . . "Thi Thai Mai"^^ . "Dinh"^^ . "Thi Thai Mai Dinh"^^ . . "Vu Tuan Anh"^^ . "Trinh"^^ . "Vu Tuan Anh Trinh"^^ . . "Ngoc Son"^^ . "Duong"^^ . "Ngoc Son Duong"^^ . . . . "IEEE 12th International Symposium on Embedded Multicore/Many-core Systems-on-Chip (MCSoC-2018)"^^ . . . . . "Hanoi city, Vietnam"^^ . . . . . . "Bluetooth Low Energy based Indoor Positioning on iOS platform (PDF)"^^ . . . "19072018 BLE based IPS_editted (2).pdf"^^ . . "HTML Summary of #3185 \n\nBluetooth Low Energy based Indoor Positioning on iOS platform\n\n" . "text/html" . . . "Communications"@en . . . "Electronics and Communications"@en . . . "Electronics and Computer Engineering"@en . .