Artificial Inteligence used in postprocessing of drive test logfiles

[punto]

Hi,

does anyone know the status of current trends of development of tools like Actix, Nemo Outdoor/Analyze , TEMS Investigation/Discovery, XCAL/XCAP ... if they will
for the postprocessing tools, in near future, start using Artificial Intelligence/machine learning to suggest , for example failed events (HO/call drops, blocks ...) root cause or other irregular RF behavior ?
There is a tool with analogue idea, that on other hand tries to simplify 4G/5G network troubleshooting and analysis , but for Wireshark PCAP logfiles ... see hxxps://www.b-yond.com/ , x=t

Thanks for any answer.
P

[ranengpro]

Here is what A.I says about this


AI is revolutionizing network engineering tools, with a focus on augmentation rather than replacement of human network engineers. Here are some key trends:

• Proactive anomaly detection and root cause analysis: AI can continuously analyze network data to identify unusual patterns and pinpoint the root cause of issues. This helps prevent outages and reduces troubleshooting time.
• Predictive maintenance: AI can predict potential problems before they occur, allowing for proactive maintenance and preventing network disruptions.
• Intent-based networking: AI helps translate high-level network goals into specific configurations, automating mundane tasks and freeing engineers for strategic work.
• Self-healing networks: Advanced AI could one day enable networks to automatically identify and fix problems without human intervention.

AI is revolutionizing network engineering tools, with a focus on augmentation rather than replacement of human network engineers. Here are some key trends:

• Proactive anomaly detection and root cause analysis: AI can continuously analyze network data to identify unusual patterns and pinpoint the root cause of issues. This helps prevent outages and reduces troubleshooting time.
• Predictive maintenance: AI can predict potential problems before they occur, allowing for proactive maintenance and preventing network disruptions.
• Intent-based networking: AI helps translate high-level network goals into specific configurations, automating mundane tasks and freeing engineers for strategic work.
• Self-healing networks: Advanced AI could one day enable networks to automatically identify and fix problems without human intervention.