When natural disasters strike, such as a powerful hurricane, our top priority is ensuring that customers, their families, and first responders stay connected. Preparing for the potential impact on our network infrastructure often involves a degree of uncertainty. To address this, our Network Disaster Recovery (NDR) program’s more than 400-person team works tirelessly to deploy a fleet of dedicated assets and innovative solutions to support critical communications before and after major weather events. Yet, despite these efforts, the true extent of the challenge is only revealed when the storm arrives. But what if AI could revolutionize our response? Imagine utilizing AI to adapt to unexpected changes in our network infrastructure, remotely resolving coverage gaps or other challenges in near real-time.
This is now a reality and being delivered by the AT&T Geo Modeler, a Generative AI system that uses synthetic data and a Network Foundation Model (NFM) to simulate and predict network coverage under dynamically changing network and environmental conditions. Using ray tracing, the Geo Modeler simulates radio transmissions in complex geospatial environments and integrates with multiple internal systems to help automate network decisions and change how the network is configured to improve overall performance and help manage connectivity nationwide, even during extreme events or as the seasons change.
If a cell tower were to go down during a storm or other unforeseen circumstances, the Geo Modeler analyzes the situation within seconds to determine how nearby towers can be optimized to compensate for coverage gaps. It can also recommend everyday changes to enhance network performance and get the best out of our resources, especially when needing to adapt to changes in the environment or when planning network coverage to support a major public event. These adjustments are fully automated and can be as simple as changing antenna angles. The network feedback data is also closely monitored by employees to ensure the AI provides accurate recommendations.
“Mobile network operators have immense challenges in ensuring optimal coverage, high availability, and corresponding application responsiveness for subscribers. Consequently, the ability to predict these parameters in near real-time delivers significant value in the form of dramatically improved service assurance. This is especially important in natural disaster scenarios”, said Will Townsend, vice president and principal analyst at Moor, Insights & Strategy.
“With its Geo-Modeler, AT&T is utilizing AI and machine learning to improve network insights and efficiency for consumers and enterprises,” added Townsend. “I have seen the solution in a live environment, and I am impressed with both its visibility and capability to dynamically facilitate the uptime demanded by consumers, enterprises, and first responders.”
The Geo Modeler is also a key enabler for emerging technologies, such as drones. When first responders utilize drones to assess and manage situations on the ground, maintaining connectivity is vital. With the Geo Modeler, we can determine the most efficient flight path and elevation, while also optimizing our network to ensure the best possible signal quality and connectivity.
Currently, the Geo Modeler is live nationwide. This advancement helps maintain service during extreme network events, enhances public safety, and helps us fulfil our promise to provide our customers with connectivity they can depend on, backed by the AT&T Guarantee. It’s a step towards network autonomy, enabling quick and efficient auto-healing of the network, while making it possible, in near real-time, to allocate network capacity where our customers need it most. Additionally, it opens possibilities for AI-powered APIs in connected cars.
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