obtaining data, over the Internet, associated with a plurality of Wi-Fi networks, the obtained data for each Wi-Fi network corresponding to a condition of each Wi-Fi network, the condition indicating current instability in a respective Wi-Fi network within the plurality of Wi-Fi networks, each Wi-Fi network having one or more access points and each Wi-Fi network being associated with a customer;

aggregating and filtering the data;

analyzing the aggregated and filtered data, the analysis comprising correlating a state, a customer type and a severity of each condition of each Wi-Fi network via a machine learning model, the customer type for each respective condition of each Wi-Fi network being associated with a type of frequency for which the respective condition has been identified;

determining, based on the analysis via the machine learning model-based correlation of the state, the customer type and the severity of each condition of each Wi-Fi network, an alarm for a Wi-Fi network within the plurality of Wi-Fi networks; and

determining, based on the determination of the alarm, one or more resolutions for the condition of the Wi-Fi network within the plurality of Wi-Fi networks, the one or more resolutions include causing repositioning nodes of the Wi-Fi network, wherein a recommendation for repositioning the nodes of the Wi-Fi network relates to their physical location and topology, the recommendation is based on at least one of a signal strength between the nodes, a number of the nodes, a number of devices connecting to the nodes, network speed tests, alarms triggered by the Wi-Fi network, and a Quality of Experience of users of the Wi-Fi network.