As telecommunications companies embrace 5G and the new technology is rolled out across networks globally, organizations will be seeking to automate processes to make their services faster and more efficient. To do this, telcos must implement artificial intelligence and machine learning solutions – as these are the only way that automation can reach the levels required for the realization of 5G’s full potential while keeping costs down and bringing innovative new products and services to the market.
ABGAD monitors key performance indicators, quality performance and customer satisfaction indices for violations. Clustering violations into anomalies, root-cause analysis of these anomalies and long-term forecasting optimizes the work of telco experts.
Using previous technologies meant analyzing multiple sources and monitoring hundreds of thousands of parameters.
Using machine learning (ML) technology, seen as a subset of artificial intelligence, is the proposed scenario here. Anomaly detection based on machine learning can identify performance indicators that do not conform to an expected pattern in a data set, and improve the breadth of detection by uncovering new patterns consisting of many baseline violations. Then, once an anomaly is detected, it can be prioritized, and cases with highest priority can be analyzed first, speeding up the entire process significantly.
Automating this type of activity increases the number of variables and makes them more flexible and dynamic. Additionally, the ability to create links between many different variables and to determine the symptoms facilitates the identification and neutralization of disruptions before they influence customer experience.