ALBERT

Description: Sensors, Vol. 18, Pages 3211: A Secure Multi-Tier Mobile Edge Computing Model for Data Processing Offloading Based on Degree of Trust Sensors doi: 10.3390/s18103211 Authors: Francisco José Mora-Gimeno Higinio Mora-Mora Diego Marcos-Jorquera Bruno Volckaert Current mobile devices need to run applications with high computational demands and critical response times. The mobile edge computing (MEC) paradigm was developed to improve the performance of these devices. This new computation architecture allows for the mobile devices to execute applications on fog nodes at the network edge; this process is called data processing offloading. This article presents a security model for the externalization of application execution in multi-tier MEC environments. The principal novelty of this study is that the model is able to modify the required security level in each tier of the distributed architecture as a function of the degree of trust associated with that tier. The basic idea is that a higher degree of trust requires a lower level of security, and vice versa. A formal framework is introduced that represents the general environment of application execution in distributed MEC architectures. An architecture is proposed that allows for deployment of the model in production environments and is implemented for evaluation purposes. The results show that the security model can be applied in multi-tier MEC architectures and that the model produces a minimal overhead, especially for computationally intensive applications.

Description: The Internet of Things (IoT) has made it possible for devices around the world to acquire information and store it, in order to be able to use it at a later stage. However, this potential opportunity is often not exploited because of the excessively big interval between the data collection and the capability to process and analyse it. In this paper, we review the current IoT technologies, approaches and models in order to discover what challenges need to be met to make more sense of data. The main goal of this paper is to review the surveys related to IoT in order to provide well integrated and context aware intelligent services for IoT. Moreover, we present a state-of-the-art of IoT from the context aware perspective that allows the integration of IoT and social networks in the emerging Social Internet of Things (SIoT) term.

Description: The application of Information Technologies into Precision Agriculture methods has clear benefits. Precision Agriculture optimises production efficiency, increases quality, minimises environmental impact and reduces the use of resources (energy, water); however, there are different barriers that have delayed its wide development. Some of these main barriers are expensive equipment, the difficulty to operate and maintain and the standard for sensor networks are still under development. Nowadays, new technological development in embedded devices (hardware and communication protocols), the evolution of Internet technologies (Internet of Things) and ubiquitous computing (Ubiquitous Sensor Networks) allow developing less expensive systems, easier to control, install and maintain, using standard protocols with low-power consumption. This work develops and test a low-cost sensor/actuator network platform, based in Internet of Things, integrating machine-to-machine and human-machine-interface protocols. Edge computing uses this multi-protocol approach to develop control processes on Precision Agriculture scenarios. A greenhouse with hydroponic crop production was developed and tested using Ubiquitous Sensor Network monitoring and edge control on Internet of Things paradigm. The experimental results showed that the Internet technologies and Smart Object Communication Patterns can be combined to encourage development of Precision Agriculture. They demonstrated added benefits (cost, energy, smart developing, acceptance by agricultural specialists) when a project is launched.

Description: Information Technology and Communications (ICT) is presented as the main element in order to achieve more efficient and sustainable city resource management, while making sure that the needs of the citizens to improve their quality of life are satisfied. A key element will be the creation of new systems that allow the acquisition of context information, automatically and transparently, in order to provide it to decision support systems. In this paper, we present a novel distributed system for obtaining, representing and providing the flow and movement of people in densely populated geographical areas. In order to accomplish these tasks, we propose the design of a smart sensor network based on RFID communication technologies, reliability patterns and integration techniques. Contrary to other proposals, this system represents a comprehensive solution that permits the acquisition of user information in a transparent and reliable way in a non-controlled and heterogeneous environment. This knowledge will be useful in moving towards the design of smart cities in which decision support on transport strategies, business evaluation or initiatives in the tourism sector will be supported by real relevant information. As a final result, a case study will be presented which will allow the validation of the proposal.

Description: The use of visual information is a very well known input from different kinds of sensors. However, most of the perception problems are individually modeled and tackled. It is necessary to provide a general imaging model that allows us to parametrize different input systems as well as their problems and possible solutions. In this paper, we present an active vision model considering the imaging system as a whole (including camera, lighting system, object to be perceived) in order to propose solutions to automated visual systems that present problems that we perceive. As a concrete case study, we instantiate the model in a real application and still challenging problem: automated visual inspection. It is one of the most used quality control systems to detect defects on manufactured objects. However, it presents problems for specular products. We model these perception problems taking into account environmental conditions and camera parameters that allow a system to properly perceive the specific object characteristics to determine defects on surfaces. The validation of the model has been carried out using simulations providing an efficient way to perform a large set of tests (different environment conditions and camera parameters) as a previous step of experimentation in real manufacturing environments, which more complex in terms of instrumentation and more expensive. Results prove the success of the model application adjusting scale, viewpoint and lighting conditions to detect structural and color defects on specular surfaces.

Description: Sustainability, Vol. 10, Pages 1102: A Low-Cost Immersive Virtual Reality System for Teaching Robotic Manipulators Programming Sustainability doi: 10.3390/su10041102 Authors: Vicente Román-Ibáñez Francisco Pujol-López Higinio Mora-Mora Maria Pertegal-Felices Antonio Jimeno-Morenilla Laboratory tasks are a powerful pedagogical strategy for developing competences in science and engineering degrees, making students understand in a practical way the theoretical topics explained in the classroom. However, performing experiments in real conditions is usually expensive in terms of time, money and energy, as it requires expensive infrastructures that are generally difficult to maintain in good conditions. To overcome this problem, virtual reality has proven to be a powerful tool to achieve sustainability, making it easy to update laboratories without the need to acquire new equipment. Moreover, the ability to introduce practical knowledge into classrooms without leaving them, makes virtual laboratories capable of simulating typical operating environments as well as extreme situations in the operation of different devices. A typical subject in which students can benefit from the use of virtual laboratories is robotics. In this work we will develop an immersive virtual reality (VR) pedagogical simulator of industrial robotic arms for engineering students. With the proposed system, students will know the effects of their own designed trajectories on several different robotic arms and cell environments without having to buy all of them and being safe of damaging the cell components. The simulation will be checking for collisions of the elements in the scene and alert the student when they happen. This can be achieved with a robotic simulator, but the integration with immersive VR is intended to help students better understand robotics. Moreover, even having a real robotic arm available for students, with this proposed VR method, all the students have the opportunity to manage and learn his own version of the robotic cell, without waiting times generated by having less robotic arms than students in classroom.

Description: Sustainability, Vol. 10, Pages 1074: Virtual Reality Learning Activities for Multimedia Students to Enhance Spatial Ability Sustainability doi: 10.3390/su10041074 Authors: Rafael Molina-Carmona María Luisa Pertegal-Felices Antonio Jimeno-Morenilla Higinio Mora-Mora Virtual Reality is an incipient technology that is proving very useful for training different skills. Our hypothesis is that it is possible to design virtual reality learning activities that can help students to develop their spatial ability. To prove the hypothesis, we have conducted an experiment consisting of training the students using an on-purpose learning activity based on a virtual reality application and assessing the possible improvement of the students’ spatial ability through a widely accepted spatial visualization test. The learning activity consists of a virtual environment where some simple polyhedral shapes are shown and manipulated by moving, rotating and scaling them. The students participating in the experiment are divided into a control and an experimental group, carrying out the same learning activity with the only difference of the device used for the interaction: a traditional computer with screen, keyboard and mouse for the control group, and virtual reality goggles with a smartphone for the experimental group. To assess the experience, all the students have completed a spatial visualization test twice: just before performing the activities and four weeks later, once all the activities were performed. Specifically, we have used the well-known and widely used Purdue Spatial Visualization Test—Rotation (PSVT-R), designed to test rotational visualization ability. The results of the test show that there is an improvement in the test results for both groups, but the improvement is significantly higher in the case of the experimental group. The conclusion is that the virtual reality learning activities have shown to improve the spatial ability of the experimental group.

Description: Biodiesel from used cooking oil (UCO) is one of the most sustainable solutions to replace conventional fossil fuels in the transport sector. It can achieve greenhouse gas savings up to 88% and at the same time reducing the disposal of a polluting waste. In addition, it does not provoke potential negative impacts that conventional biofuels may eventually cause linked to the use of arable land. For this reason, most policy frameworks favor its consumption. This is the case of the EU policy that double-counters the use of residue and waste use to achieve the renewable energy target in the transport sector. According to different sources, biodiesel produced from UCO could replace around 1.5%–1.8% of the EU-27 diesel consumption. This paper presents an in-depth thermoeconomic analysis of the UCO biodiesel life cycle to understand its cost formation process. It calculates the ExROI value (exergy return on investment) and renewability factor, and it demonstrates that thermoeconomics is a useful tool to assess life cycles of renewable energy systems. It also shows that UCO life cycle biodiesel production is more sustainable than biodiesel produced from vegetable oils.

Description: A short bipolar pressure pulse with “pancake” directivity is produced and propagated when an Ultra-High Energy (UHE) neutrino interacts with a nucleus in water. Nowadays, acoustic sensor networks are being deployed in deep seas to detect this phenomenon as a first step toward building a neutrino telescope. In order to study the feasibility of the method, it is critical to have a calibrator that is able to mimic the neutrino signature. In previous works the possibility of using the acoustic parametric technique for this aim was proven. In this study, the array is operated at a high frequency and, by means of the parametric effect, the emission of the low-frequency acoustic bipolar pulse is generated mimicking the UHE neutrino acoustic pulse. To this end, the development of the transducer to be used in the parametric array is described in all its phases. The transducer design process, the characterization tests for the bare piezoelectric ceramic, and the addition of backing and matching layers are presented. The efficiencies and directivity patterns obtained for both primary and parametric beams confirm that the design of the proposed calibrator meets all the requirements for the emitter.

Description: Wireless Sensor Networks (WSNs) are a technology that is becoming very popular for many applications, and environmental monitoring is one of its most important application areas. This technology solves the lack of flexibility of wired sensor installations and, at the same time, reduces the deployment costs. To demonstrate the advantages of WSN technology, for the last five years we have been deploying some prototypes in the Doñana Biological Reserve, which is an important protected area in Southern Spain. These prototypes not only evaluate the technology, but also solve some of the monitoring problems that have been raised by biologists working in Doñana. This paper presents a review of the work that has been developed during these five years. Here, we demonstrate the enormous potential of using machine learning in wireless sensor networks for environmental and animal monitoring because this approach increases the amount of useful information and reduces the effort that is required by biologists in an environmental monitoring task.