Intelligent monitoring systems and methods for Wi-Fi metric-based alarms for cloud based Wi-Fi networks

A system comprising:

• a processor configured to:
• receive, by an application, data related to an access point device for a Wi-Fi network at a location, the data comprising Wi-Fi related performance metrics at the location for a time;
• analyze, by the application, the received data for the access point, the analysis comprising executing a machine learning model trained to identify network performance anomalies, wherein the analyzing comprises pattern matching based on the received data for the location;
• determine, by the application, based on the analysis, information related to a network topology for the Wi-Fi network at the location, the network topology comprising a configuration of network connectivity for at least one device in relation to the access point device, the network topology comprises information related to identification of backhaul links between access point devices and client links to Wi-Fi client devices, wherein channel assignments for the backhaul links and the client links are determined via the determined information;
• and
• provide, by the application, an output related to the network topology and operation of the Wi-Fi network, the output comprising a graphical representation of the information related to the network topology showing the access point devices and connectivity therebetween, including the information related to the identification of the backhaul links between the access point devices and the client links to the Wi-Fi client devices and the channel assignments, wherein the output includes a network health score that is a weighted combination of factors including received signal strength indicator (RSSI), interference, and bandwidth.

A non-transitory computer-readable storage medium tangibly encoded with computer-executable instructions, that when executed by a processor, perform a method comprising:

• receiving, by an application, data related to an access point device for a Wi-Fi network at a location, the data comprising Wi-Fi related performance metrics at the location for a time;
• analyzing, by the application, the received data for the access point, the analysis comprising executing a machine learning model trained to identify network performance anomalies, wherein the analyzing comprises pattern matching based on the received data for the location;
• determining, by the application, based on the analysis, information related to a network topology for the Wi-Fi network at the location, the network topology comprising a configuration of network connectivity for at least one device in relation to the access point device, the network topology comprises information related to identification of backhaul links between access point devices and client links to Wi-Fi client devices, wherein channel assignments for the backhaul links and the client links are determined via the determined information;
• and
• providing, by the application, an output related to the network topology and operation of the Wi-Fi network, the output comprising a graphical representation of the information related to the network topology showing the access point devices and connectivity therebetween, including the information related to the identification of the backhaul links between the access point devices and the client links to the Wi-Fi client devices and the channel assignments, wherein the output includes a network health score that is a weighted combination of factors including received signal strength indicator (RSSI), interference, and bandwidth.