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Telecom Industry

In telecommunications, AI is used to optimize features in networks and predict failures in telecom sites. And, as with any technological innovation, the more we rely on technology the more vulnerable we become.

A misbehaving network may drop your call or cancel your Instagram upload, and ofcourse, this becomes annoying if it is an important call or upload. But in the future, networks will be an integral part of any mission-critical use case relying on connectivity, be it remote control of heavy machinery, autonomous drones or self-organizing logistics.

The role of Artificial Intelligence and Data Science to Improve Network Performance, Reliability, and Security

In our opinion, the following uses of AI in Telecom proves that the technology is already mature enough to become a real game-changer.

Combatting Overload

With AI in place, your network will be able to respond automatically to any significant overload that may arise. It will become possible for the network to detect an overload, create automatically the number of virtual machines, required to handle the incoming amount of traffic, and funnel the excessive traffic by using these virtual machines, promptly and without human involvement.

Optimizing Service Quality by Predicting Future Network Usage

AI technology can help to optimize your service quality. You can use Machine Learning algorithms to predict how the usage of your network will vary across the different geographies it covers during a specific time period.

Performing Predictive Maintenance

Machine Learning is now turning the tables on you by giving you the ability to detect various alarming network signals (for example, those, emitted by cell towers or powerlines), that may be a precursor of a forthcoming network failure.

In essence, Artificial Intelligence can help you to take the robustness and reliability of your network to an entirely new level.

Averting Malicious Actions

Machine Learning can reliably secure your network against malicious actions, such as for example, DDoS attacks.

With Machine Learning, your network can be trained to identify a large number of similar requests, inundating it simultaneously, and make a decision on whether to deny these requests flat-out or shunt them to another, less busy Data Center to be dealt with manually by your employees

Thesis
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