About cookies on this site Our websites require some cookies to function properly (required). In addition, other cookies may be used with your consent to analyze site usage, improve the user experience and for advertising. For more information, please review your options. By visiting our website, you agree to our processing of information as described in IBM’sprivacy statement. To provide a smooth navigation, your cookie preferences will be shared across the IBM web domains listed here.
Conference paper
An iBeacon Training App for Indoor Fingerprinting
Abstract
Indoor positioning systems have become widely available due to the increased number of wireless technologies available today. A type of wireless device that has become very popular in the past years has been the Bluetooth Low Energy (BLE) beacon. This compact, battery-powered device can enable location-based and proximity services across in-door spaces. Several indoor positioning techniques have been explored to achieve indoor localization using these wireless devices. One of these techniques is the fingerprinting technique, which requires careful collection of training data at known locations. We developed an app to facilitate and expedite the process of collecting training data with iOS devices. The training data is collected by our app and saved in the cloud for future retrieval. We collected training data from different floor maps, performed initial analysis on this data, and tested a fingerprinting algorithm in order to provide indoor localization. We developed several tools to evaluate and visualize the training data and tested our indoor localization algorithm in a real-time scenario.
Related
Conference paper
Formal verification of smart contracts using interface automata
Conference paper