Field experience using AI-based data augmentation & data interpretation in fiber network operation скачать в хорошем качестве

Field experience using AI-based data augmentation & data interpretation in fiber network operation

To efficiently manage a network, decisions based on accurate insights are imperative, which heavily rely on data quality. However, availability of high-pacing traffic data is either not practical, might be intrusive and asks for extended processing resources. At Nokia Bell Labs, we have developed an alternative to the creation/externalization of high volume of network traffic data, leveraging our AI-based data augmentation & interpretation models. Now deployed as prototype at POST Technologies, they facilitate the management and troubleshooting of the PON network thanks to a gain in bandwidth-demand visibility and a better understanding of traffic patterns, moreover solely from the data counters natively available in PON equipment. Presenters Olivier Ferveur, Senior Network Architect, Post Lux Philippe Dierickx, Senior Data Scientist, Nokia Beall Labs