Cost Saving Model For Lighting in Smart Cities

With the increase in technology and utilities in urban areas and cities, the energy consumption increases drastically. New ways and methods became necessary to reduce the expenditure and lower the cost on the governing entities of those cities. The purpose of IoT is to empower smart power saving and leverage the use of other technologies which in turn reduces cost. Many countries around the world are implementing IoT in their infrastructure and have become an integrated part of the workings of society. The study will focus on implementing a solution that uses AIoT, data gathered from IoT devices and machine learning in producing a solution that can accurately predict and suggest a suitable lighting technique. Random Forest Regressor outperformed well in predicting accurately, described the vehicular count and suggested a proper lighting technique, and ultimately reduced the cost by certain margin.