AI Case Study

Guilford College improves Wi-Fi and Bluetooth wireless services using machine learning

Guilford College uses Mist Systems' Learning WLAN to monitor its wireless network and services to proactively detect anomalies and bottlenecks. The platform utilises machine learning to map the network and monitor it to detect any variations and helps identify root causes immediately in case of issues.

Industry

Public And Social Sector

Education And Academia

Project Overview

"Service levels were set up to measure key metrics — like coverage and capacity — ensuring that the Guilford campus community has the best service possible. The new technology also allows IT&S to rapidly isolate issues and address other non-wireless problems efficiently.

Mist’s AI engine, Marvis™, simplifies Wi-Fi operations and delivers personalized indoor location services.

The Mist platform has a unique Proactive Analytics and Correlation Engine (PACE), which provides the foundation for AI data collection and analysis in the Wi-Fi / BLE domain. PACE collects over 100 pre- and post- connection user and location states in near real-time from every wireless device. This state information is sent to the Mist cloud, where AI algorithms are used for real-time analysis. "

Reported Results

The solution is claimed to offer:

* Centralised monitoring
* Anomaly detection
* Automation
* Root cause identification

Technology

Function

Information Technology

Network Operations

Background

Guilford College is a liberal arts school located in Greensboro, North Carolina.

Benefits

Data