JMU // ISEG

Project Outline

Together with a manufacturer of industrial machinery, we developed a web application to optimize customer appointments for a showroom based on energy data. The aim is to reduce the amount of energy that has to be purchased externally via the power grid. The app uses machine learning, to predict energy consumption, energy already generated by solar and stored in accumulators, and energy production at the time. Based on the consumption of the machinery in the showroom, needed power up and cool down phases, and the predicted available energy, customer appointments are then optimally scheduled.

Links:

• Code : github repository