Stochastic Modeling for Performance and Availability Evaluation of Street Lighting Systems

The need for better management and cost reduction for maintaining street lighting systems has motivated the development of new techniques and architectures based on Internet of Things (IoT). Remote and autonomous control are prominent features of IoT-based systems that may considerably improve street lighting operation. However, mechanisms for assessing the availability and performance of smart street lighting systems are not usually taken into account, which would assist in evaluating distinct architectures and configurations before implementing the real system. This paper presents an approach based on generalized stochastic Petri nets (GSPN) and reliability block diagrams (RBD) for assessing availability and performance of smart street lighting systems. Experimental results demonstrate the practical feasibility of the proposed approach, in which a sensitivity analysis is also taken into account to indicate the components with most impact on system operation.