LearnLoc: a framework for smart indoor localization with embedded mobile devices

摘要: There has been growing interest in location-based services and indoor localization recent years. While several smartphone based techniques have proposed, these many shortcomings related to accuracy consistency. These prior efforts also ignore energy consumption analysis which is a crucial quality metric resource-constrained smartphones. In this work, we propose novel on machine learning algorithms smart sensor management for real-time using We implement our proposed as well state-of-the-art real smartphones evaluate their tracking effectiveness overheads across diverse real-world environments. Our best technique improves upon achieving between 1--3 meters.