Addition of devices in a mobile cluster

A method for addressing anomalies in an Internet of things (IOT) device, the IOT device being a part of a mobile cluster, the method comprising:

• determining whether the IOT device produces an anomaly based at least on a first machine learning model;
• determining adjustments for recommending in functioning of the IOT device based at least on a second machine learning model in response to a determination that the IOT device produces the anomaly;
• sending the recommended adjustments to one or more user devices that are a part of the mobile cluster for loading the recommended adjustments on to the mobile cluster;
• and
• receiving a selection of one or more of the recommended adjustments from the one or more user devices for facilitating addressal of the anomaly in the IOT device.

A system for addressing anomalies in a mobile cluster, the system comprising:

• one or more user devices that are a part of the mobile cluster;
• and
• an Internet of things (IOT) device, the IOT device being a part of a mobile cluster, the IOT being configured to:
• determine whether the IOT device produces an anomaly based at least on a first machine learning model;
• determine adjustments to recommend in functioning of the IOT device based at least on a second machine learning model in response to a determination that the IOT device produces the anomaly;
• send the recommended adjustments to one or more user devices that are a part of the mobile cluster to load the recommended adjustments on to the mobile cluster;
• and
• receive a selection of one or more of the recommended adjustments from the one or more user devices to facilitate addressal of the anomaly in the IOT device.