This paper presents a scalable IoT architecture based on the edge–fog–cloud paradigm for monitoring the Indoor Environmental Quality (IEQ) parameters in public buildings. Nowadays, IEQ monitoring systems are becoming important for several reasons: (1) to ensure that temperature and humidity conditions are adequate, improving the comfort and productivity of the occupants; (2) to introduce actions to reduce energy consumption, contributing to achieving the Sustainable Development Goals (SDG); and (3) to guarantee the quality of the air—a key concern due to the COVID-19 worldwide pandemic. Two kinds of nodes compose the proposed architecture; these are the so-called: (1) smart IEQ sensor nodes, responsible for acquiring indoor environmental measures locally, and (2) the IEQ concentrators, responsible for collecting the data from smart sensor nodes distributed along the facilities. The IEQ concentrators are also responsible for configuring the acquisition system locally, logging the acquired local data, analyzing the information, and connecting to cloud applications. The presented architecture has been designed using low-cost open-source hardware and software—specifically, single board computers and microcontrollers such as Raspberry Pis and Arduino boards. WiFi and TCP/IP communication technologies were selected, since they are typically available in corporative buildings, benefiting from already available communication infrastructures. The application layer was implemented with MQTT. A prototype was built and deployed at the Faculty of Engineering of Vitoria-Gasteiz, University of the Basque Country (UPV/EHU), using the existing network infrastructure. This prototype allowed for collecting data within different academic scenarios. Finally, a smart sensor node was designed including low-cost sensors to measure temperature, humidity, eCO₂, and VOC.

Safety and performance of the turbo-engine in an aircraft is directly affected by the health of its blades. In recent years, several improvements to the sensors have taken place to monitor the blades in a non-intrusive way. The parameters that are usually measured are the distance between the blade tip and the casing, and the passing time at a given point. Simultaneously, several techniques have been developed that allow for the inference—from those parameters and under certain conditions—of the amplitude and frequency of the blade vibration. These measurements are carried out on engines set on a rig, before being installed in an airplane. In order to incorporate these methods during the regular operation of the engine, signal processing that allows for the monitoring of those parameters at all times should be developed. This article introduces an architecture, based on a trifurcated optic sensor and a hardware processor, that fulfills this need. The proposed architecture is scalable and allows several sensors to be simultaneously monitored at different points around a bladed disk. Furthermore, the results obtained by the electronic system will be compared with the results obtained by the validation of the optic sensor.

Typical Internet of Things (IoT) applications involve collecting information automatically from diverse geographically-distributed smart sensors and concentrating the information into more powerful computers. The Raspberry Pi platform has become a very interesting choice for IoT applications for several reasons: (1) good computing power/cost ratio; (2) high availability; it has become a de facto hardware standard; and (3) ease of use; it is based on operating systems with a big community of users. In IoT applications, data are frequently carried by means of wireless sensor networks in which energy consumption is a key issue. Energy consumption is especially relevant for smart sensors that are scattered over wide geographical areas and may need to work unattended on batteries for long intervals of time. In this scenario, it is convenient to ease the construction of IoT applications while keeping energy consumption to a minimum at the sensors. This work proposes a possible gateway implementation with specific technologies. It solves the following research question: how to build gateways for IoT applications with Raspberry Pi and low power IQRF communication modules. The following contributions are presented: (1) one architecture for IoT gateways that integrates data from sensor nodes into a higher level application based on low-cost/low-energy technologies; (2) bindings in Java and C that ease the construction of IoT applications; (3) an empirical model that describes the consumption of the communications at the nodes (smart sensors) and allows scaling their batteries; and (4) validation of the proposed energy model at the battery-operated nodes.

The nature of wireless propagation may reduce the QoS of the applications, such that some packages can be delayed or lost. For this reason, the design of wireless control applications must be faced in a holistic way to avoid degrading the performance of the control algorithms. This paper is aimed at improving the reliability of wireless control applications in the event of communication degradation or temporary loss at the wireless links. Two controller levels are used: sophisticated algorithms providing better performance are executed in a central node, whereas local independent controllers, implemented as back-up controllers, are executed next to the process in case of QoS degradation. This work presents a reliable strategy for switching between central and local controllers avoiding that plants may become uncontrolled. For validation purposes, the presented approach was used to control a planar robot. A Fuzzy Logic control algorithm was implemented as a main controller at a high performance computing platform. A back-up controller was implemented on an edge device. This approach avoids the robot becoming uncontrolled in case of communication failure. Although a planar robot was chosen in this work, the presented approach may be extended to other processes. XBee 900 MHz communication technology was selected for control tasks, leaving the 2.4 GHz band for integration with cloud services. Several experiments are presented to analyze the behavior of the control application under different circumstances. The results proved that our approach allows the use of wireless communications, even in critical control applications.

The performance of airplane engines is influenced by the performance of their bladed disks. The loads those engines are under, both internal and external, are the origin of vibrations than can jeopardize their integrity. Traditionally, monitoring of those vibrations has been circumscribed to prototyping and quality tests of manufactured disks. However, the development of nonintrusive sensors and techniques to evaluate the vibration based on those sensors opens the monitoring of full engines, even onboard, to new possibilities. In order to assess the vibrations with these techniques, several sensors should be employed. The distance from the blade tip to the casing (tip clearance) and the time of arrival of a blade in front of the sensor are two parameters that are used as a starting point to characterize the vibrations. A flexible architecture to extract these parameters from the blades of a gas turbine has been developed. The generalization of this architecture is introduced which is able to deal with several sensors simultaneously. An implementation of this architecture has been carried out employing a trifurcated optic sensor, whose working principle is explained. A study of the resources required to implement this architecture on measurements of several optic sensors simultaneously and in parallel is presented. The architecture and measurement method have been validated using signals recorded during the test of the compressor stage with 146 blades on a turbine rig.

The sustainable development goals (SDGs) reflect the relevance that sustainability is gaining in our societies. Including sustainability-related topics in university curricula requires the revision of the contents, teaching/learning strategies and assessment techniques. Although engineering degrees are starting to introduce them, it may become complex to design significant educational experiences. This partly comes from the fact that sustainability is a highly multidisciplinary issue but, currently, the knowledge is compartmentalised into subjects. In this challenging scenario, concrete activities are required for students to better internalise sustainability issues. This work aims to present a methodology that guides academic staff to materialise the design of sustainability-related multidisciplinary activities. Since the designers of new activities may benefit from knowledge of similar experiences, this article describes one implementation throughout eight subjects within the Bachelor’s degree on Industrial Electronics and Automation Engineering at UPV/EHU. The analysis and optimisation of the thermal comfort and energy consumption in the Faculty building became the common thread to design an educational itinerary that covers several subjects along all academic years of the degree, making use of active methodologies. The problem is analysed for every subject from different perspectives. Two questionnaires, carried out before and after the activities, were used for analysing the perception of the students after the activities. Results proved that the multidisciplinary project raised awareness about the SDGs and allowed students to visualise how to apply the acquired skills in problems close to their experience. As a result, more students considered sustainability as a possible future professional activity.