Abstract: Methods, systems, and apparatuses for identifying network leaks are described herein. Data associated with network leaks may be collected and analyzed to determine a network leak type(s) associated with each network leak. Each network leak type may be associated with a particular radio frequency (RF) radiation pattern. RF radiation patterns as well as corresponding features associated with a number of network leak types may be stored in a database and/or library. A classification model may use the database and/or library to classify an unknown RF radiation pattern as being associated with a leak type(s) of the number of network leak types.

Abstract: Methods, systems, and apparatuses are provided for detecting events in proximity to one or more transmission lines or cables of a data, power, communications, and/or content data transmission system. Data indicating an event may be received. The data may indicate movement or deflection of a portion of the transmission line or cable. A location of the portion of the transmission line or cable may be determine. The location may be determined based on the received data. A classification of the event may be determined. For example, the classification of the event may be based on the data on the received data and the determined location. For example, the classification of the event may be determined by a machine-learning model. A response may be caused. The response may be associated with the portion of the cable. The response may be based on the classification of the event.

Abstract: Methods, systems, and apparatuses for identifying network leaks are described herein. Data associated with network leaks may be collected and analyzed to determine a network leak type(s) associated with each network leak. Each network leak type may be associated with a particular radio frequency (RF) radiation pattern. RF radiation patterns as well as corresponding features associated with a number of network leak types may be stored in a database and/or library. A classification model may use the database and/or library to classify an unknown RF radiation pattern as being associated with a leak type(s) of the number of network leak types.