Stochastic modeling of smart street lighting systems: maintenance models assessment

Smart Street Lighting System (SSLS) is an intelligent outdoor lighting system with automated controls that enhances energy savings, safety, and city design, reducing operational costs and environmental impact. The need for better management and cost reduction for maintaining SSLS has motivated the development of new techniques and architectures based on the 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 evaluating the availability of smart street lighting systems are not taken into account for the corrective and preventive maintenance of the entire system. This paper presents an approach based on stochastic Petri nets (SPN) to assess availability from maintenance models of street lighting systems. This approach highlights the importance of systematic maintenance strategies to ensure the continuous and efficient operation of these systems before their implementation. Experimental results demonstrate the practical feasibility of the proposed approach, including a sensitivity analysis to identify the components with the greatest impact on system operation.