INSUBCONTINENT EXCLUSIVE:
see a huge number of mobile devices
Each person might have multiple devices in their possession or direct use
functional Wi-Fi networks in a device-centric era
Many wireless problems are ephemeral, disappearing shortly after they arise based on changing user and environmental conditions
Sending techs onsite to reproduce the problem can be expensive, and often yields lacklustre results as the data needed to reproduce and
other things, such as an issue with DNS, DHCP or authentication servers.The benefits of machine learningThanks to machine learning and other
AI technologies, it is finally possible to address these issues in a seamless and scalable manner
experience for mobile users.There are four key components to building an AI engine for a WLAN: data, structure and classify, data science
states from every wireless device
The information, or metadata, from these access points is sent to the cloud, where the AI engine can then structure and classify this
data.Once your data is in place, at this point the AI engine is able to structure and classify the received metadata through a set of AI
By programming the AI engine with relevant wireless network domain knowledge, this metadata can be classified and analysed effectively by
the data science toolbox, in order to deliver insights of value straight into the network.Apply the data science wizardryCollected, measured
So, whether you want to deploy supervised and unsupervised machine learning, data mining, deep learning or mutual information, there are
This is baselined, and used for anomaly detection
Streamlining these techniques with one another helps network administrators reduce to mean-time-to-repair, enhancing end-user
Completing the AI engine is the virtual assistant that delivers insights to the IT administrator, as well as feeds that insight back into
the network itself to automate the correction of issues.A top priority here is the use of a natural language processor
This will make life easier for the administrators who would otherwise have to hunt through dashboards or common language interpreter
commands in order to extract the insights from the AI engine
The upshot of using natural language is that it increases the productivity of IT teams while delivering a better user experience for
employees and customers.Look forwards with data scienceBy incorporating AI and data science with wireless expertise, it puts an end to
When a user is experiencing a network anomaly, the WLAN system can automatically detect it and start capturing packets, a concept known as
This process is akin to going into a time machine because it enables you to see what was going on in the Wi-Fi network and the mobile device
when the anomaly was detected
intelligence and insights into the wireless network, however, takes this a step further
Changes can be automated, and made in real-time, empowering Wi-Fi networks to dynamically and autonomously self-optimise for each connection
and varied devices, operating systems, and applications, troubleshooting issues can prove challenging
