The resource-constrained sensors that compose these networks collect information about the environment that surrounds them and are interconnected with the rest of the nodes of the network, making this technology a fundamental part of the Internet of Things (IoT). Nowadays wireless sensor networks have become a key technology used in diverse applications such as environmental and disaster area monitoring, security, inventory management, healthcare monitoring, etc. It ranges from less than 10 ms to more than 300 ms depending on the fuzzification level, which demonstrates the importance of evaluating localization algorithms in real nodes to prevent the introduction of large overheads that may not be affordable by resource-constrained nodes. In addition, the execution time of the algorithm running in the nodes has been evaluated. While the overall behaviour is similar in simulations and in real tests, important differences can be observed attending to quantitative accuracy results. Multiple tests have been carried out to obtain the localization accuracy data in three different scenarios, showing the difference between simulation and real results. We have implemented the fuzzy ring-overlapping range-free (FRORF) algorithm with some modifications to make its operation feasible on resource-constrained devices. Therefore, in this work we present an experimental evaluation of a received signal strength indicator (RSSI)-based localization algorithm implemented on IoT end-devices, comparing its results with those obtained from simulations. For this reason, many localization algorithms for WSNs have been developed in the last years, although in most cases the results provided are obtained from simulations that do not consider the resource constraints of the end-devices. WSNs nodes constitute part of the end-devices present in the IoT, and in many cases location data of these devices is expected by IoT applications. In recent years, wireless sensor networks (WSNs) have experienced a significant growth as a fundamental part of the Internet of Things (IoT).
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