This article presents a monitoring system for industrial electrical equipment in a production line, aiming at real-time monitoring of its operational state, allowing machine management and early detection of deviations and failures. The system measures the effective current draw of the monitored equipment using sensors connected to a data concentrator module, which stores the data collected by these sensors and performs preliminary processing before transmission to an Internet of Things platform. Preliminary data processing focuses on analyzing the time series of the electric current values in order to detect the operating state of the monitored machine. This information is then sent over the Internet to an IoT platform for long-term storage, post-processing and real-time visualization of data by end users. When a behavior deviation is detected in current consumption related to some type of potential failure, the system issues alerts and sends additional information to the production line supervisor, for example to proceed with equipment maintenance intervention without impact on production. The availability of full-time data series, as well as the history of all occurrences recorded by the monitoring system, also allow for correlations with data from other sources and their interpretation in contexts other than machine operation or maintenance. The proposed monitoring system provides minimal automation on older machines and opens up the possibility of independent, parallel and non-intrusive monitoring on machines that already have supervisory systems.