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Abstract
The prevalence of smartphones has increased the demand for and application of location-based services. However, the Global Positioning System, currently the most widely used positioning technology, cannot provide accurate positioning services when obstructed by obstacles. Consequently, this system can only provide outdoor application services such as outdoor navigation and tracking. In 2013, Apple Inc. released iBeacon, a positioning technology based on Bluetooth low energy (BLE). This device transmits Bluetooth signals within a specific range, in which the signals are received by other smartphones to calculate distances for providing indoor positioning-related services. In this study, the iBeacon transmission power level is adjusted to significantly increase Bluetooth signal differences in indoor environments. Therefore, it can reduce received signal strength indicators (RSSI) similarity for some reference points by adjusting the power level. Subsequently, radio frequency signals are filtered using a modified moving average filter to reduce signal variations after reception. Next, pattern matching and the K-Nearest Neighbors (KNNs) algorithm are integrated to facilitate positioning. The integration of the modified moving average filter with the KNNs algorithm increases the positioning accuracy by 23.08% during the online phase. This finding can thus improve location-based services.