Purging IoT devices in a cellular network

A system for removing non-functioning Internet-of-Things (IoT) devices from a cellular network, the system comprising:

• one or more processors;
• and
• a memory storing computer instructions that when executed cause the one or more processors to perform acts comprising:
• receiving, as training data, first data from first one or more IoT devices, the training data being collected over a time interval, including, after receiving a first portion of the training data:
• determining, during the time interval, characteristics of the first portion of the training data collected over the time interval;
• and
• determining, during the time interval, a length of the time interval over which the training data is collected based at least in part on the characteristics of the first portion of the training data, wherein at least a second portion of the training data is received during a remainder of the time interval after the determining of the length of the time interval based at least in part on the characteristics of the first portion of the training data;
• generating, based at least in part on the training data, a model representing an expected data profile to be transmitted to the cellular network by second one or more IoT devices;
• receiving, as received data, second data from an IoT device;
• comparing the received data from the IoT device to the model representing the expected data profile to be transmitted to identify the IoT device as a non-functioning IoT device;
• and
• removing, based at least in part on comparing the received data to the model representing the expected data profile to be transmitted, the non-functioning IoT device from the cellular network.

A non-transitory computer-readable media for removing non-functioning Internet-of-Things (loT) devices from a cellular network, the non-transitory computer-readable media including instructions that when executed by a processor, cause a node in the cellular network to perform acts comprising:

• receiving, as training data, first data from first one or more IoT devices, the training data being collected over a time interval, including, after receiving a first portion of the training data:
• determining, during the time interval, characteristics of the first portion of the training data collected over the time interval;
• and
• determining, during the time interval, a length of the time interval over which the training data is collected based at least in part on the characteristics of the first portion of the training data, wherein at least a second portion of the training data is received during a remainder of the time interval after the determining of the length of the time interval based at least in part on the characteristics of the first portion of the training data;
• generating, based at least in part on the training data, a model representing an expected data profile to be transmitted to the cellular network by second one or more IoT devices;
• receiving, as received data, second data from an IoT device;
• comparing the received data from the IoT device to the model representing the expected data profile to be transmitted to identify the IoT device as a non-functioning IoT device;
• and
• removing, based at least in part on comparing the received data to the model representing the expected data profile to be transmitted, the non-functioning IoT device from the cellular network.