Smart Street Light For Energy Saving Based On Vehicular Traffic Volume

The energy crisis is one of Pakistan's biggest problems, as electricity is necessary, and its accessibility to every Pakistani at a cheap rate is essential. Although Pakistan has overcome the energy crises by implementing a new green energy power plant, the energy resources have not been utilized effectively due to line losses and inefficient electrical devices. So, instead of just emphasizing increasing power generation, we should resort to energy curtailment and move toward a solution that could make our devices smart enough to save energy and reduce the burden on our resources. Streetlights are one of the significant sources of electricity consumption, and an enormous amount of energy could be saved by converting conventional streetlights into smart streetlights. This paper has discussed a novel idea of developing smart streetlights by utilizing the preinstalled surveillance cameras. Cameras are installed at entry exit points of each street, to vary light intensity based on pedestrian and vehicular traffic volume using CNN-based Artificial Neural Network Algorithm YOLOv5. The system is further integrated with a control module which could vary the light intensity between 50 to 100 percent on receiving a signal from the processing unit (Jetson Nano). The system can save around 25 percent of the total cost consumed by the conventional LED streetlight.