Abstract: A user device may provide, to a network associated with a base station, user device location data identifying a latitude, a longitude, and a heading of the user device, and may receive base station location data identifying a latitude, a longitude, and signal coverage of the base station. The user device may display a first user interface that includes a user device indication, a base station indication, and a selection option, and may receive a selection of the selection option. The user device may retrieve camera view data and sensor data associated with the user device and may display, based on the camera view data and the sensor data, a second user interface that includes the first user interface overlaid on a camera view of the user device, an augmented reality-based signal strength directional indicator, and an augmented reality-based base station location representation associated with the base station.

Abstract: A user device may provide, to a network associated with a base station, user device location data identifying a latitude, a longitude, and a heading of the user device, and may receive base station location data identifying a latitude, a longitude, and signal coverage of the base station. The user device may display a first user interface that includes a user device indication, a base station indication, and a selection option, and may receive a selection of the selection option. The user device may retrieve camera view data and sensor data associated with the user device and may display, based on the camera view data and the sensor data, a second user interface that includes the first user interface overlaid on a camera view of the user device, an augmented reality-based signal strength directional indicator, and an augmented reality-based base station location representation associated with the base station.

Abstract: Embodiments of the disclosure are directed to providing a single source for adverse event data by taking a layered approach to standardizing, harmonizing and detecting duplicates across multiple data sources at different scales. In one embodiment, a method is provided. The method includes parsing datasets stored in a data store. These datasets are enriched using standardization and normalization. In the candidate duplicates and feature engineering step, the method may join send the data to hashing algorithm to generate candidate duplicates. Features are extracted from each duplicate candidate pair using the term-pair set adjustment technique. These candidates and associate features are sampled using a sampling technique and are labeled as duplicates or non-duplicates. Upon a conflict in labels, a conflict resolution strategy is applied to create a master list of duplicate pairs. A classifier is trained on the master list to classify the rest of the candidate pairs as duplicates/non-duplicates.