Fog computing uses Radial Basis Function for Power Production Classification Solar Panel Electricity

Energy is a very important problem for life, especially electrical energy in areas that are still lagging behind and far from development activities. These problems encourage the creation of an innovation that can be used to help people get the availability of electricity easily. Solar panels is effective energy producers, but many things are disrupt to productivity. Therefore, a system is needed to support the sustainability of the energy sources produced. Monitoring requires an online computing system that requires the availability of large broadband on the internet network. This is a serious obstacle if you want an online realtime system productivity monitoring system. In this study we propose fog computing technology using the support vector machines method for computational processes. Data on temperature, humidity, intensity and power were obtained from physical parameter sensors of solar panels. And then, The data is computed using the support vector machines method with the kernel radial base function in the fog network. This research produces an information system is capable to provide an early warning to the user to display the results of electric power production that is available in the field online and real time. Root mean square error showed very good results which reached 0.066.