Smart Street Lighting with Reduced Sensors for Sustainable and Efficient Smart Cities

Abstract

Street Lights are absolutely important and without them, people would be risking their life every minute they spend on the roads. The main problem involved in street light hardware system is excessive consumption of power. This amount of power consumption can be minimized by designing smart street lighting systems in order to have smart cities. To enable the growth of smart cities and help them shape into self-sustaining, energy harvesting, green hubs, the energy must be conserved. To solve this problem there are many smart street lighting methods which discussed efficient ways to conserve power. To support the financial needs of some of the proposed methods, a struggling economy like India would not be able to afford the costs. However, to make it truly smart and affordable, the number of sensors involved in the street lighting system can be reduced strategically to account for driver’s visibility range as well as power consumed by the lights. The algorithm discussed in this paper, takes advantage of Cellular Automata [CA], to simulate the traffic similar to real-time traffic and utilized Bernoulli’s probability distribution to analyze the randomized the traffic present on the roads. This helped to visualize the situation as aptly as possible. According to the statistics street lights use up nearly 38% of the electricity produced. If this energy is saved using an energy saving scheme such as the one discussed in this paper, that energy can be utilized elsewhere – where there is an absolute and immediate need, for instance smart cities. According to the results obtained through the utilization of the method discussed in this paper, nearly 50 percent of the energy consumed by the existing smart street lighting systems can be saved. If the energy thus saved is transferred to the development of the smart cities, more than 100 of them can achieve full transition from an urban city into a smart city.