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• W2989666268 abstract "Increasing the location accuracy of the Indoor Positioning System (IPS) is an important research area in localization. Utilizing mobile beacons in IPS environment has made localization more accurate and cost-effective. This paper proposes an Filtered RSSI and Beacon Weight Approach (FRBW) based on improved Received Signal Strength Indicator (RSSI) values using a Kalman filter. This algorithm takes both the distance and improved RSSI measurements between beacon nodes into consideration. Kalman filter applied on the RSSI measurements that eliminate noise of the signal and then applied on FRBW positioning algorithm. The proposed algorithm was applied using eight beacons. The results show that this FRBW approach has better positioning accuracy and minimum location error, and can be applied in IoT applications in smart city." @default.
• W2989666268 created "2019-12-05" @default.
• W2989666268 creator A5045172155 @default.
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• W2989666268 date "2019-09-01" @default.
• W2989666268 modified "2023-09-23" @default.
• W2989666268 title "Improve Indoor Positioning Accuracy Using Filtered RSSI and Beacon Weight Approach in iBeacon Network" @default.
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• W2989666268 doi "https://doi.org/10.1109/iscit.2019.8905189" @default.
• W2989666268 hasPublicationYear "2019" @default.
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