In this paper, we propose a flexible Fog Computing architecture in which the main features are that it allows us to select among two different communication links (WiFi and LoRa) on the fly and offers a low-power solution, thanks to the applied power management strategies at hardware and firmware level. The proposed Fog Computing architecture is formed by sensor nodes and an Internet of Things (IoT) gateway. In the case of LoRa, we have the choice of implementing the LoRaWAN and Application servers on the cloud or on the IoT gateway, avoiding, in this case, to send data to the Cloud. Additionally, we have presented an specific setup and methodology with the aim of measuring the sensor node’s power consumption and making sure there is a fair comparison between the different alternatives among the two selected wireless communication links by varying the duty cycle, the size of the payload, and the Spreading Factor (SF). This research work is in the scope of the STARPORTS Interconnecta Project, where we have deployed two sensor nodes in the offshore platform of PLOCAN, which communicate with the IoT gateway located in the PLOCAN premises. In this case, we have used LoRa communications due to the required large distance between the IoT gateway and the nodes in the offshore platform (in the range of kilometers). This deployment demonstrates that the proposed solution operates in a real environment and that it is a low-power and robust approach since it is sending data to the IoT gateway during more than one year and it continues working.

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Structural health monitoring is a critical part of the maintenance procedures of an aircraft. Most of the problems that arise from structural elements are detected by trained personnel using visual inspection. Moreover, the places at which these structural elements are located are frequently very difficult to access. This makes inspections time consuming and potentially very costly. In this paper we are presenting the design principles that must be taken into account in order to successfully deploy a wireless sensor network in an aircraft. We will discuss the relations between sampling duration, power consumption, energy harvesting and storage, wireless communication and network architecture in order to successfully deploy the system. In order to consider the trade-offs between different design issues we have designed a sensor node equipped with an accelerometer, a temperature and humidity sensor and a strain gauge sensor. The sensor node has an energy harvester from a thermo-electrical generator and a battery storage element. Wireless communications are based on Zigbee protocol and the sensor node is controlled from a low power microcontroller.