There’s no question that Wi-Fi networks continue to grow in importance for most companies. Workers rely on it to do their jobs, students are being educated on mobile tablets, doctors are pulling up records at a patients’ bedside, and millions of Internet of Things (IoT) devices are now being connected to Wi-Fi. 

Wireless is no longer the connection of convenience — it’s mission critical, and a poor-performing wireless network means a key process is likely to fail. 

Wi-Fi troubleshooting a continued source of pain for network engineers  

If the wireless network is so critical, why aren’t there better Wi-Fi troubleshooting tools? A recent ZK Research survey about Wi-Fi troubleshooting uncovered how difficult this. Some interesting data points from the survey:

  • Just under 60 percent of respondents spend at least a quarter of their time doing nothing but troubleshooting Wi-Fi issues. In a 40-hour work week, that’s 10 hours of time dedicated to finding and fixing Wi-Fi problems.
  • Forty-seven percent of respondents said it takes 30 minutes or longer to diagnose a problem and 41 percent claim it takes another 30 minutes or more to solve the issue. That means for about half the companies, Wi-Fi issues take an hour or more to correct.
  • Over 60 percent of respondents still use packet capture as their primary troubleshooting tool. Packet capture is akin to a data dump, and then someone needs to sift through and analyze the data, which explains why the troubleshooting time is so lengthy.

What if there were a better way? What if Wi-Fi problems could be found before users report problems? Science fiction you say? I understand the skepticism, but machine learning and artificial intelligence (AI) is used widely in many industries to do things such as drive cars, automate supply chain, feed crickets, and more. If it can do those things, can’t it help find Wi-Fi problems?

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