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Location-Based Services (LBSs) have long been studied by many researchers and they nowadays provide very useful information to us, making our daily lives convenient. Vehicle navigation systems are an example of an LBS. As people frequently visit huge unfamiliar buildings, the demand for Indoor LBSs (ILBSs) has rapidly increased. Since indoor positioning is a key technique needed to implement an ILBS system, it has been studied by many researchers. However, a universal solution for indoor positioning has not been found yet. Smartphones are one of the best devices with which interactions between humans and ILBS systems occur because they are equipped with screens, sensors, processors and telecommunications gadgets. Therefore, many research results from smartphone-based indoor positioning studies have been published. One of the most popular methods of indoor positioning is the fingerprint method. The smartphonebased fingerprint method cannot be accurate if the smartphone sensor values collected at one spot are not different from smartphone sensor values collected at other spots. This paper outlines experiments done to show which smartphone sensors can be used in fingerprint indoor positioning.

Keywords

Indoor Positioning, Location-Based Service, Neural Network, Smartphone Sensors
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