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Location estimation is significant in mobile and ubiquitous computing systems. The complexity and smaller scale of the indoor environment impose a great impact on location estimation. The key of location estimation lies in the representation and fusion of uncertain information from multiple sources. The improvement of location estimation is a complicated(More)
The recognition of locomotion activities (e.g., walking, running, still) is important for a wide range of applications like indoor positioning, navigation, location-based services, and health monitoring. Recently, there has been a growing interest in activity recognition using accelerometer data. However, when utilizing only acceleration-based features, it(More)
The utility and adoption of indoor localization applications have been limited due to the complex nature of the physical environment combined with an increasing requirement for more robust localization performance. Existing solutions to this problem are either too expensive or too dependent on infrastructure such as Wi-Fi access points. To address this(More)
In this research, a new Map/INS/Wi-Fi integrated system for indoor location-based service (LBS) applications based on a cascaded Particle/Kalman filter framework structure is proposed. Two-dimension indoor map information, together with measurements from an inertial measurement unit (IMU) and Received Signal Strength Indicator (RSSI) value, are integrated(More)
Location-aware applications based on local wireless networks, like Wi-Fi, RFID, are becoming more realistic and attractive for many research and commercial organizations in recent years. In this paper, we provide comprehensive analysis on key characteristics of museum mobile guide system with location-aware features, including related location technologies,(More)
Many location-based services require location awareness, but it is often too expensive to include a GPS receiver in every network node. Hence, localization schemes using radio signal strength is more attractive when high precision isn't in demand. Fingerprinting is an effective method, but it is inaccurate when accidental gross error is included in the(More)
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