The demand for electric energy has escalated in households and industries with the use of different electric and electronic loads day in and out. This has uplifted a concern to be addressed to many developed and developing nations with the demand for an immediate increase of electric energy especially in traditional factories alongside its monitoring parameters and control systems. Thus, there is a call to enhance the reduction of energy consumption and graduate traditional factories to smart factories by imploring real-time energy consumption monitoring
techniques and control systems.

An electric energy monitoring system has been used for ultimate purposes such as process scheduling and billing in the traditional industries. The increasing demand especially in intensive industrial energy sectors dictates the development of smarter energy management systems which involves the embedded systems. Industrial end-users need to understand their energy consumption to reduce energy costs, improve company ecological profile, and suggestive feedback scheduling of their production lines. Factory machines to be more efficient and the need to reduce energy costs by the optimization of industrial processes can be satisfied by the use of embedded systems for energy monitoring and control systems.

For traditional factories smart electric energy monitoring has been neglected due to limited knowledge and also lack of expertise in real-time energy monitoring systems to acquire and process both energy and power quality data in real-time through the use of embedded computing. The advent of disruptive technologies such as the IoT, Machine learning, and Big Data has made real-time data acquisition and analysis very practical, reliable, and viable. The design of the system is based on a low-cost Arduino microcontroller, non-invasive split-core current transformer, relay module, and voltage transformer. The sensor data of the developed system indicated that the prototype can successfully record RMS voltage and current, real and apparent power, power factor, and energy with great accuracy.

Through the proposed monitoring system, traditional factories can have an overview of how much energy they are consuming at a particular time which may reduce energy costs, reduce carbon emissions and environmental damage and increase the profit margin of the factory