802.11g Signal Strength Evaluation in an Industrial Environment The advances in wireless network technologies and Industrial Internet of Things (IIoT) devices are easing the establishment of what is called Industry 4.0. For the industrial environments, the wireless networks are more suitable mainly due to their great flexibility, low deployment cost and for being less invasive. Although new wireless protocols are emerging or being updated, changes in existing industries generally can lead to large expenditures. As the well known and accepted IEEE 802.11g standard, mostly used in residential and commercial applications, has a low deployment and maintenance cost, many industries also decide to adopt it. In this scenario, there is a need to evaluate the signal quality to better design the network infrastructure in order to obtain good communication coverage. In this work, we present a practical study about the 802.11g signal strength in a thermoelectric power plant. We collected signal strength values in different points along the engine room and compared our measured values with the estimated ones through the LogDistance Path Loss model. We concluded that it is possible to use this model in an industrial environment to estimate signal strength with a low error by choosing the right propagation (path loss) exponent.

Evaluation of a Link Quality Estimator in an Outdoor WSN Using a Dedicated Node Industrial Wireless Sensor Networks (IWSN) demand deterministic and reliable communication. Adaptive mechanisms, such as channel adaptation and channel hopping, can be applied to deal with the temporal and spatial variations in link quality that can appear in an IWSN. The first step to effectively use such mechanisms is to estimate the quality of the links in the network, which can provide useful information for the adaptive mechanisms, in order to improve important metrics, such as the packet reception rate, and energy consumption. In this context, this paper evaluates experimentally a link quality estimator, which uses dedicated nodes to estimate the link quality in realtime, without imposing a high overhead. A longterm experiment was performed in a fuel loading plant and the results showed that the estimator is accurate and reactive for the scenario considered in the paper. From the results obtained in the experiment, it was also possible to observe the quality of the 16 channels defined by the IEEE 802.15.4 standard in the 2.4 GHz band, for different nodes, and discuss how the adaptive mechanisms could be used to increase the network quality of service, by picking the appropriate channels for each link during the network operation.