Designing a Low-Cost System to Monitor the Structural Behavior of Street Lighting Poles in Smart Cities

The structural collapse of a street lighting pole represents an aspect that is often underestimated and unpredictable, but of relevant importance for the safety of people and things. These events are complex to evaluate since several sources of damage are involved. In addition, traditional inspection methods are ineffective, do not correctly quantify the residual life of poles, and are inefficient, requiring enormous costs associated with the vastness of elements to be investigated. An advantageous alternative is to adopt a distributed type of Structural Health Monitoring (SHM) technique based on the Internet of Things (IoT). This paper proposes the design of a low-cost system, which is also easy to integrate in current infrastructures, for monitoring the structural behavior of street lighting poles in Smart Cities. At the same time, this device collects previous structural information and offers some secondary functionalities related to its application, such as meteorological information. Furthermore, this paper intends to lay the foundations for the development of a method that is able to avoid the collapse of the poles. Specifically, the implementation phase is described in the aspects concerning low-cost devices and sensors for data acquisition and transmission and the strategies of information technologies (ITs), such as Cloud/Edge approaches, for storing, processing and presenting the achieved measurements. Finally, an experimental evaluation of the metrological performance of the sensing features of this system is reported. The main results highlight that the employment of low-cost equipment and open-source software has a double implication. On one hand, they entail advantages such as limited costs and flexibility to accommodate the specific necessities of the interested user. On the other hand, the used sensors require an indispensable metrological evaluation of their performance due to encountered issues relating to calibration, reliability and uncertainty.