How mobile operators can use machine learning to detect and optimise the network for roaming IoT devices

On-demand version

While almost half of roaming revenues will come from machine-to-machine communications (IoT devices), providing permanent M2M/IoT roaming is cited as a key challenge by more than 50% of mobile operators.

By gaining a complete view of IoT devices roaming on their networks, mobile operators can optimise their networks for M2M traffic, offer optimal Quality of Service, and ultimately monetise IoT better.

The information needed to unlock this potential is already present within an operator’s network traffic, it just needs to be mined and interpreted. BICS SMART Webvision is an advanced end-to-end traffic monitoring, reporting and business intelligence tool that uses advanced analytics and machine learning techniques to provide the insights needed to optimise and improve the network for M2M roaming traffic.

Join Damion Rose, mobile signaling and roaming expert from BICS, as he discusses how mobile operators can use machine learning to automatically detect and optimize for roaming M2M devices.

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