Indoor Localization Data Analytics: Integrating Wi-Fi and Inertial Sensor Data from Smartwatches and Smartphones
Keywords:
Keywords: Indoor Localization, Wi-Fi Signal Strength, Support Vector Classifier, Random Forest Classifier, Smartphone and Smartwatch Sensors.Abstract
Indoor localization is a rapidly evolving field, with studies indicating that Wi-Fi-based positioningachieves an average accuracy of 2-5 meters, while inertial sensor fusion can further enhance precisionby up to 30% in dynamic environments. However, traditional manual localization methods relying onphysical infrastructure or RFID-based tracking remain inefficient, requiring significant setup time andmaintenance, which is impractical for large-scale deployment. To address these limitations, this researchpresents a comprehensive approach to indoor localization by integrating Wi-Fi signal strengths withinertial sensor data from smartwatches and smartphones
References
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