Keysight Technologies helps accelerate AI-powered assessment of real-world user interactions with core applications.

With the growing use of mobile apps, Keysight has developed a new method for device app testing that leverages AI, machine learning (ML), and automation, using data captured from native mobile apps rather than simulated data traffic.

Keysight said this will allow it to more accurately assess end-user interactions with the same mobile app.

Wireless service providers can quickly optimize 5G network performance and deliver superior quality of experience (QoE) for the world's most popular OTT services and applications through a new automated application testing method.

“Service providers and mobile app developers need a reliable way to verify the real end-user experience associated with accessing over-the-top (OTT) applications on smartphones connected to cellular networks,” said Metti Passoja, director of Keysight’s NEMO wireless solutions. “Keysight combines a unique suite of software and hardware technology platforms to enable real-world applications to be used to validate the most complex and reliable end-user experiences.” “We have developed an automated app testing method that provides more accurate insights into network performance even in dynamic situations,” he added.

The new automated app testing method is one of a complementary suite of test methods offered by Keysight's Nemo device application test suite.

Depending on the type of mobile application and key performance indicators (KPIs), specific testing methods are used in conjunction with the Nemo field testing solution. Users of the Nemo test suite can flexibly verify 5G network performance and assess end-user QoE.

Meanwhile, Keysight's Nemo test tools capture real-world measurement data in the field for real-time or post-event analysis. These test tools include the Nemo Outdoor 5G NR Drive Test Solution, the Nemo Backpack Pro 5G In-Building Benchmarking Solution, and the Nemo Network Benchmarking Solution.