Examinando por Autor "Casado Mansilla, Diego"
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Ítem A cascading model for nudging employees towards energy-efficient behaviour in tertiary buildings(Public Library of Science, 2024-05) Kalamaras, Ilias; Sánchez Corcuera, Rubén; Casado Mansilla, Diego; Tsolakis, Apostolos C.; Gómez Carmona, Oihane; Krinidis, Stelios; Borges Hernández, Cruz E.; Tzovaras, Dimitrios; López de Ipiña González de Artaza, DiegoEnergy-related occupant behaviour in the built environment is considered crucial when aiming towards Energy Efficiency (EE), especially given the notion that people are most often unaware and disengaged regarding the impacts of energy-consuming habits. In order to affect such energy-related behaviour, various approaches have been employed, being the most common the provision of recommendations towards more energy-efficient actions. In this work, the authors extend prior research findings in an effort to automatically identify the optimal Persuasion Strategy (PS), out of ten pre-selected by experts, tailored to a user (i.e., the context to trigger a message, allocate a task or providing cues to enact an action). This process aims to successfully influence the employees' decisions about EE in tertiary buildings. The framework presented in this study utilizes cultural traits and socio-economic information. It is based on one of the largest survey datasets on this subject, comprising responses from 743 users collected through an online survey in four countries across Europe (Spain, Greece, Austria and the UK). The resulting framework was designed as a cascade of sequential data-driven prediction models. The first step employs a particular case of matrix factorisation to rank the ten PP in terms of preference for each user, followed by a random forest regression model that uses these rankings as a filtering step to compute scores for each PP and conclude with the best selection for each user. An ex-post assessment of the individual steps and the combined ensemble revealed increased accuracy over baseline non-personalised methods. Furthermore, the analysis also sheds light on important user characteristics to take into account for future interventions related to EE and the most effective persuasion strategies to adopt based on user data. Discussion and implications of the reported results are provided in the text regarding the flourishing field of personalisation to motivate pro-environmental behaviour change in tertiary buildings.Ítem Climate change from B to Z: a cross-generational perception study in Spain(Frontiers Media SA, 2025) Divasson Jaureguibarria, Asier; Aguayo Mendoza, Armando; Quesada Granja, Carlos; Casado Mansilla, Diego; Borges Hernández, Cruz E.In the context of increasing climate concerns, this study explores generational perceptions and responses to potential climate-induced crises through a workshop and survey methodology. The aim of this study is to understand how different age groups view and react to extreme climate scenarios and evaluate their proposed actions and attitudes toward climate change mitigation. This study investigates generational perceptions and responses to climate change through a dual-format workshop and survey, conducted both in person and online. The methodological approach involved presenting respondents with a range of apocalyptic scenarios resulting from climate change, including electricity shortages, reduced food production, fuel scarcity, inadequate home heating, drought, and raw material shortages. These scenarios aimed to assess respondents’ awareness, concern, and proposed actions in response to potential future crises. The survey, administered via the Prolific platform, and workshops, held at the “Zientzia Azoka” science fair and online, gathered data from 153 participants across four generational cohorts, namely, Baby Boomers, Generation X (Gen X), Millennials, and Generation Z (Gen Z). The analysis revealed distinct generational differences in attitudes toward societal responsibility and action. Baby Boomers emphasized community responsibility over formal regulations, showing a preference for moral and ethical accountability rather than legislative action. Generation X displayed balanced responses, with tendencies toward valuing education and long-term stability. Millennials were more likely to emphasize the role of authorities and formal governance in addressing societal issues, reflecting their reliance on structured systems. In contrast, Generation Z showed a strong inclination to hold companies accountable, often associating responsibility with corporate entities, and were more vocal about behavioral changes and restrictions to drive progress. The study underscores significant generational differences in climate change perceptions and actions, highlighting a trend toward increasing demand for climate action and growing distrust in institutions. These insights suggest the need for inclusive, generationally tailored climate policies with a focus on education and systemic change. Future research should explore the relationship between sustainable consumption and economic vulnerability, addressing how financial constraints impact individuals’ ability to adopt sustainable practicesÍtem Engagement and accessibility tools for pro-environmental action on air quality: the SOCIO-BEE paradigm(Springer Science and Business Media Deutschland GmbH, 2024-01) Atutxa Ordeñana, Ekhi; García Torres, Sofía; Kyfonidis, Charalampos; Karanassos, Dimitrios; Kopsacheilis, Evangelos; Tsita, Christina; Casado Mansilla, Diego; Emvoliadis, Alexandros; Angelis, Georgios; López de Ipiña González de Artaza, Diego; Puerta Beldarrain, Maite; Drosou, Anastasios; Tzovaras, DimitriosThe involvement of citizens and all stakeholders is crucial in tackling environmental and social matters. This, addressing equity and diversity issues, although challenging, is a necessary condition for achieving positive outcomes and ensuring that no one is left behind. To help ease this challenge, this work presents a systematic approach to ensure inclusive participation and leverage non-technical and technical elements to maximise stakeholder engagement in scientific activities to successfully address sustainability concerns. For that, it builds on the interim results of the H2020 SOCIO-BEE project, a Citizen science (CS) proposal to reduce air pollution through inclusive community engagement and social innovation. As part of an interdisciplinary CS project, an abductive systematic combining methodology was employed, which allowed for dialogue and collaboration between theory and practice throughout the whole process, during which separate groups of experts and potential end-users were involved. The article presents (i) the stakeholder engagement strategy codified in the SOCIO-BEE toolkit as a robust, actionable and inclusive foundation of engagement to CS activities; and (ii) the digital platform UX that allows setting up campaigns for measurements and assignment to citizens, incorporating the requirements for flexibility, accessibility, limited digital literacy, inclusion and legal and ethical considerations. Their combination and mutual interaction aim to leverage the pros of CS and technology whilst reducing their cons to ensure the four pillars of applicability, scalability, actionability, and inclusion. This is supported by the presented hybrid model which combines physical and virtual spaces and individual and collective action.Ítem Exploring the computational cost of machine learning at the edge for human-centric Internet of Things(Elsevier B.V., 2020-11) Gómez Carmona, Oihane; Casado Mansilla, Diego; Kraemer, Frank Alexander; López de Ipiña González de Artaza, Diego; García-Zubía, JavierIn response to users’ demand for privacy, trust and control over their data, executing machine learning tasks at the edge of the system has the potential to make the Internet of Things (IoT) applications and services more human-centric. This implies moving complex computation to a local stage, where edge devices must balance the computational cost of the machine learning techniques to meet the available resources. Thus, in this paper, we analyze all the factors affecting the classification process and empirically evaluate their impact in terms of performance and cost. We put the focus on Human Activity Recognition (HAR) systems, which represent a standard type of classification problems in human-centered IoT applications. We present a holistic optimization approach through input data reduction and feature engineering that aims to enhance all the stages of the classification pipeline and integrate both inference and training at the edge. The results of the conducted evaluation show that there is a highly non-linear trade-off to make between the computational cost, in terms of processing time, and the achieved classification accuracy. In the presented case of study, the computational effort can be reduced by 80% assuming a decline of the classification accuracy of only 3%. The potential impact of the optimization strategy highlights the importance of understanding the initial data and studying the most relevant characteristics of the signal to meet the cost–accuracy requirements. This would contribute to bringing embedded machine learning to the edge and, hence, creating spaces where human and machine intelligence could collaborate.Ítem Human-in-the-loop machine learning: reconceptualizing the role of the user in interactive approaches(Elsevier B.V., 2024-04) Gómez Carmona, Oihane; Casado Mansilla, Diego; López de Ipiña González de Artaza, Diego; García-Zubía, JavierThe rise of intelligent systems and smart spaces has opened up new opportunities for human–machine collaborations. Interactive Machine Learning (IML) contribute to fostering such collaborations. Nonetheless, IML solutions tend to overlook critical factors such as the timing, frequency and workload that drive this interaction and are vital to adapting these systems to users’ goals and engagement. To address this gap, this work explores users’ expectations towards IML solutions in the context of an interactive hydration monitoring system for the workplace, which represents a challenging environment to implement intelligent solutions that can collaborate with individuals. The proposed system involves users in the learning process by providing feedback on the success of detecting their drinking gestures and enabling them to contribute with additional examples of their data. A qualitative study was conducted to evaluate this use case, where participants completed specific tasks with varying levels of involvement. This study provides promising insights into the potential of placing the Human-in-the-Loop (HitL) to adapt and reconceptualize the users’ role in interactive solutions, highlighting the importance of considering human factors in designing more effective and flexible collaborative systems between humans and machines.Ítem An image-based sensor system for low-cost airborne particle detection in citizen science air quality monitoring(Multidisciplinary Digital Publishing Institute (MDPI), 2024-10) Shah, Syed Mohsin Ali; Casado Mansilla, Diego; López de Ipiña González de Artaza, DiegoAir pollution poses significant public health risks, necessitating accurate and efficient monitoring of particulate matter (PM). These organic compounds may be released from natural sources like trees and vegetation, as well as from anthropogenic, or human-made sources including industrial activities and motor vehicle emissions. Therefore, measuring PM concentrations is paramount to understanding people’s exposure levels to pollutants. This paper introduces a novel image processing technique utilizing photographs/pictures of Do-it-Yourself (DiY) sensors for the detection and quantification of (Formula presented.) particles, enhancing community involvement and data collection accuracy in Citizen Science (CS) projects. A synthetic data generation algorithm was developed to overcome the challenge of data scarcity commonly associated with citizen-based data collection to validate the image processing technique. This algorithm generates images by precisely defining parameters such as image resolution, image dimension, and PM airborne particle density. To ensure these synthetic images mimic real-world conditions, variations like Gaussian noise, focus blur, and white balance adjustments and combinations were introduced, simulating the environmental and technical factors affecting image quality in typical smartphone digital cameras. The detection algorithm for (Formula presented.) particles demonstrates robust performance across varying levels of noise, maintaining effectiveness in realistic mobile imaging conditions. Therefore, the methodology retains sufficient accuracy, suggesting its practical applicability for environmental monitoring in diverse real-world conditions using mobile devices.Ítem Mind the gap: the AURORAL ecosystem for the digital transformation of smart communities and rural areas(Elsevier Ltd, 2023-08) Gómez Carmona, Oihane; Buján Carballal, David; Casado Mansilla, Diego; López de Ipiña González de Artaza, Diego; Cano de Benito, Juan; Cimmino, Andrea; Poveda Villalón, María; García Castro, Raúl; Almela Miralles, Jorge; Apostolidis, Dimitris; Drosou, Anastasios; Tzovaras, Dimitrios; Wagner, Martin; Guadalupe Rodríguez, María; Salinas, Diego; Esteller, David; Riera Rovira, Martí; González, Arnau; Clavijo Ágreda, Jaime; Díez Frias, Alberto; Bocanegra Yáñez, María del Carmen; Pedro Henriques, Rui; Ferreira Nunes, Elsa; Lux, Marian; Bujalkova, NikolRural areas play a crucial role in addressing challenges related to climate change, food provision, biomass, and energy. At the same time, digital solutions have proven essential in improving safety, quality of life, and resilience in daily life. However, the lower population density and the lack of digital infrastructure in such rural areas make it difficult to develop technology-driven private businesses and public services. This can negatively impact socio-economic indicators and hinder the development of new services to cover peoples’ needs. For this reason, in this document, we seek to provide a stronger focus on rural regions in digitalization efforts and create new opportunities for rural communities. For that, we analyze the barriers and needs of the rural environment and present AURORAL, a digital service platform designed to meet the needs and contexts of rural areas. This ecosystem, comprising sustainable and multi-interoperable apps and services, can help communities succeed in innovation and smart transformation, providing the necessary infrastructure to facilitate long-lasting social, environmental, and economic benefits by prioritizing openness, interoperability, and decentralization. On the principle that the full potential of these technologies can only be realized when they are integrated into societal and economic activity and organization, AURORAL aims to promote economic growth and digitalization in the rural domain and contribute to bridging the digital divide between rural and urban areas.Ítem Opportunities and challenges of technology-Based interventions to increase health-wareness in the workplace(IOS Press, 2019) Gómez Carmona, Oihane; Casado Mansilla, Diego; García-Zubía, JavierWell-being at work is gaining an increasing importance on the overall health promotion as the workplace is considered an adequate setting to support health-related interventions reaching large audiences. In fact, an increasing number of initiatives are being carried out to influence employees towards healthier lifestyles in later years. However, despite demonstrating moderate efficacy, the body of literature shows that the lack of adherence of the target audience to the interventions is an important factor to overcome in order to attain higher success. To increase employees' motivation and prevent early drop-out, disengagement or high attrition rates, this work presents an intervention methodology based on the Internet of Things (IoT) paradigm. Specifically, it presents a novel concept of a participatory workercentric IoT solution for enhancing individuals' well-being in office environments. This approach seeks to stress the significance of empowering workers providing to them fine-grained control of their own well-being and self-care which correlates to higher rates of participation in health promotion initiatives. Along this chapter the main challenges associated with the design and development of technology-based interventions are reviewed. Moreover, the value of increasing the acceptance and adoption of the presented IoT approach from the employee's perspective is analyzed in a comprehensive manner.Ítem Optimizing computational resources for edge intelligence through model cascade strategies(Institute of Electrical and Electronics Engineers Inc., 2022-05-15) Gómez Carmona, Oihane; Casado Mansilla, Diego; López de Ipiña González de Artaza, Diego; García-Zubía, JavierAs the number of interconnected devices increases and more artificial intelligence (AI) applications upon the Internet of Things (IoT) start to flourish, so does the environmental cost of the computational resources needed to send and process all the generated data. Therefore, promoting the optimization of AI applications is a key factor for the sustainable development of IoT solutions. Paradigms such as Edge Computing are progressively proposed as a solution in the IoT field, becoming an alternative to delegate all the computation to the Cloud. However, bringing the computation to the local stage is limited by the resources' availability of the devices hosted at the Edge of the network. For this reason, this work presents an approach that simplifies the complexity of supervised learning algorithms at the Edge. Specifically, it separates complex models into multiple simpler classifiers forming a cascade of discriminative models. The suitability of this proposal in a human activity recognition (HAR) context is assessed by comparing the performance of three different variations of this strategy. Furthermore, its computational cost is analyzed in several resource-constrained Edge devices in terms of processing time. The experimental results show the viability of this approach to outperform other ensemble methods, i.e., the Stacking technique. Moreover, it substantially reduces the computational cost of the classification tasks by more than 60% without a significant accuracy loss (around 3.5%). This highlights the potential of this strategy to reduce resource and energy requirements in IoT architectures and promote more efficient and sustainable classification solutions.Ítem Promoting long term energy-efficient behaviour in work environments through persuasive technologies(Universidad de Deusto, 2016-09-12) Casado Mansilla, Diego; López de Ipiña González de Artaza, Diego; Garaizar, Pablo; Facultad de Ingeniería; Ingeniería Informática y TelecomunicaciónThere are several actions that can be taken to adopt a sustainable lifestyle: recycling, reducing resources or the use of disposable items, avoiding heat or cold leakages depending on the season, switching off electrical equipment or lights when they are not in use, etc. The environment can ease or hinder these actions. Sustainability in a private setting, where every element is known, and occupants have complete control of each electrical device, seems to be easier than sustainability in common or shared spaces, such as workplaces. In these latter environments, although the motivation or intentions are high, there are barriers to pro-environmental behavior: 1) workers do not pay the electrical invoices and are unaware of energy use and cost; 2) the diffusion of responsibility phenomenon and the shared use of many electrical devices (e.g. photocopiers, thermostats, coffee-makers, kettles, etc.) keep the devices unnecessarily switched on because no one takes the responsibility to switch them off; and 3) there is an overall uncertainty about the most energy-efficient way to operate shared equipment and people doubt if the action they are taking will reduce the ecological footprint (e.g. whether to switch off an electrical device or the room lights if someone immediately after us will use them). The thesis hypothesis to overcome sustainability barriers in common or shared spaces requires the design of strategies that ease the adoption of long-term energy-efficient behaviors. To this aim, three empirical studies were conducted, one of them longitudinal. The leading actor of each of these studies is the persuasive technology, defined as technology designed to change the attitudes or behaviors of the users through persuasion, built into the shared electrical devices prone to energy-inefficient utilization. Augmenting these devices with persuasive technology was embraced favorably by the participants of the study. Even more insightful was finding that people tend to treat the augmented devices as if they were real people, attributing social characters to them or affiliating with them to create a team relationship towards coping with energy inefficiency in the workplace. To validate the hypothesis, this thesis contributed to the Sustainable Human-Computer Interaction community (S)HCI in the following ways: 1) combining predictive soft computing techniques with persuasive interaction to cope with energy inefficiency, increasing workers' energy awareness through eco-feedback provided immediately upon performing the energy inefficient action; 2) illustrating that persuasive technologies are propitious, forming pro-environmental behaviour in the mid and long term; and 3) demonstrating that automating electronic devices (i.e. preventing subjects from controlling these devices), in favor of comfort, is associated with a reduction of the participant's confidence in technology as a means to solve all current environmental problems.Ítem PyFF: a fog-based flexible architecture for enabling privacy-by-esign IoT-based communal smart environments(NLM (Medline), 2021-06) Benhamida, Fatima Zohra; Navarro, Joan; Gómez Carmona, Oihane; Casado Mansilla, Diego; López de Ipiña González de Artaza, Diego; Zaballos, AgustínThe advent of the Internet of Things (IoT) and the massive growth of devices connected to the Internet are reshaping modern societies. However, human lifestyles are not evolving at the same pace as technology, which often derives into users' reluctance and aversion. Although it is essential to consider user involvement/privacy while deploying IoT devices in a human-centric environment, current IoT architecture standards tend to neglect the degree of trust that humans require to adopt these technologies on a daily basis. In this regard, this paper proposes an architecture to enable privacy-by-design with human-in-the-loop IoT environments. In this regard, it first distills two IoT use-cases with high human interaction to analyze the interactions between human beings and IoT devices in an environment which had not previously been subject to the Internet of People principles.. Leveraging the lessons learned in these use-cases, the Privacy-enabling Fog-based and Flexible (PyFF) human-centric and human-aware architecture is proposed which brings together distributed and intelligent systems are brought together. PyFF aims to maintain end-users' privacy by involving them in the whole data lifecycle, allowing them to decide which information can be monitored, where it can be computed and the appropriate feedback channels in accordance with human-in-the-loop principles.Ítem A spatial crowdsourcing engine for harmonizing volunteers’ needs and tasks’ completion goals(Multidisciplinary Digital Publishing Institute (MDPI), 2024-12) Puerta Beldarrain, Maite; Gómez Carmona, Oihane; Chen, Liming; López de Ipiña González de Artaza, Diego; Casado Mansilla, Diego; Vergara, Felipe EduardoThis work addresses the task allocation problem in spatial crowdsensing with altruistic participation, tackling challenges like declining engagement and user fatigue from task overload. Unlike typical models relying on financial incentives, this context requires alternative strategies to sustain participation. This paper presents a new solution, the Volunteer Task Allocation Engine (VTAE), to address these challenges. This solution is not based on economic incentives, and it has two primary goals. The first one is to improve user experience by limiting the workload and creating a user-centric task allocation solution. The second goal is to create an equal distribution of tasks over the spatial locations to make the solution robust against the possible decrease in participation. Two approaches are used to test the performance of this solution against different conditions: computer simulations and a real-world experiment with real users, which include a qualitative evaluation. The simulations tested system performance in controlled environments, while the real-world experiment assessed the effectiveness and usability of the VTAE with real users. This research highlights the importance of user-centered design in citizen science applications with altruistic participation. The findings demonstrate that the VTAE algorithm ensures equitable task distribution across geographical areas while actively involving users in the decision-making process.Ítem Tecnoetica: inclusion and assessment of the ethical competence in engineering final degree projects(Education Society of IEEE (Spanish Chapter), 2022-02-07) Romero Yesa, Susana; Ukar Arrien, Olatz; Bilbao Alberdi, Galo; Sasia Santos, Pedro Manuel; Casado Mansilla, Diego; Eguíluz, AndoniEthics is taking a relevant role in this 21st century, in most cases going hand in hand with scientific-technological advances and the social and cultural implications. However, to date, the evidence on which a university in the European Higher Education Area (EHEA) can rely to incorporate the ethical perspective in the educational curriculum successfully is still scarce. To increase the body of knowledge in engineering ethics, this article presents and evaluates the initiative called 'Tecnoetica' implemented at the University of Deusto, Spain. This initiative proposes to include training in ethical principles, dilemmas, and issues from a holistic and participatory standpoint in which lecturers and students are involved. Because of the initiative, an evaluation rubric is presented as the main contribution from which other centers, universities and/or faculties can benefitÍtem Towards smart, digitalised rural regions and communities: policies, best practices and case studies(Elsevier Ltd, 2025-06) Leviäkangas, Pekka; Sønvisen, Signe; Casado Mansilla, Diego; Mikalsen, Marius; Cimmino, Andrea; Drosou, Anastasios; Hussain, ShahidRural communities and regions face specific challenges in terms of thin markets, low population density, and long distances. Also, the demographics of these communities are often skewed towards the elderly, and the socioeconomics is characterized by higher share of low-income populations. While the concept of urban smart communities is quite well established, such as Smart Cities, the concept of smart rural region communities is only beginning to gain scholarly attention. Smart rural communities can be understood as rural areas and communities that build on their existing strengths and assets as well as on developing new opportunities based on the aforementioned. Traditional and new networks and services can be improved by utilizing digital telecommunication technologies, innovations, and better use of data and knowledge to benefit the communities. Investing in both physical and digital connectivity, and building digital environments for innovative services, economic sustainability, jobs, and social capital can be enhanced, thus contributing to active and live rural communities. Consequently, the development of smart rural communities and regions begins to emerge in research. What is becoming evident is that achieving the ambitions of smart rural communities requires not only digital technologies but also innovation of commercial and social services, as well as better digital capabilities and skills to bridge the existing – and in places the widening - divide between rural and urban communities.Ítem Understanding the factors that affect households' investment decisions required by the energy transition(Public Library of Science, 2024-03) Aguayo Mendoza, Armando; Irizar Arrieta, Ane; Casado Mansilla, Diego; Borges Hernández, Cruz E.In energy systems' economic models, people's behaviour is often underestimated, and they are generally unaware of how habits impact energy efficiency. Improving efficiency is challenging, and recommendations alone may not be sufficient. Changing behaviour requires understanding the direct impact of needs and habits on energy efficiency. This research introduces a methodology that retrieves human expert knowledge from four key aspects of the current energy transition: everyday appliances, buildings, mobility, flexibility, and energy efficiency. The aim is to examine the causal relationship between energy consumption and human behaviour, gaining a deeper understanding of the links among the factors that drive final energy consumers to change habits through the adoption of energy-saving measures. Working in collaboration with expert panels, this study provides a methodology for extracting expert human knowledge based on a set of future energy transition scenarios aligned with the achievement of the Paris Agreement, a taxonomy of 32 factors that have a strong influence on households' investment decisions, and the results of a survey that characterises the European population through the 32-factor taxonomy and some socioeconomic conditions. In addition, the survey included a sample of the Latin American population to analyse how socioeconomic conditions (region, education, gender, etc.) influence the prioritisation of these factors. We discuss the high priority given to competence and autonomy over financial factors by inhabitants of the European Union residential sector. We provide an analysis of the factors through which other similar projects are focused and on which we converge. In addition, we contribute by presenting the hierarchy of priorities assigned by people. This highlights the importance for policymakers to take these aspects seriously when implementing energy policy interventions that go beyond purely financial measures and fiscal incentives