[u' @inproceedings{diaz-de-arcaya_akats_2023, title = {Akats: {A} {System} for {Resilient} {Deployments} on {Edge} {Computing} {Environments} {Using} {Federated} {Machine} {Learning} {Techniques}}, shorttitle = {Akats}, doi = {10.23919/SpliTech58164.2023.10193302}, abstract = {Edge computing is a game changer for IoT, as it allows IoT devices to independently process and analyze data instead of just sending it to the cloud. But managing this considerable number of devices and deploying workloads on them in a coordinated and intelligent manner remains a challenge nowadays. In this paper, we focus on introducing the resilience dimension into these deployments, and we provide two main contributions: the use of federated machine learning techniques to develop a collaborative tool between the different devices aimed at detecting the possibility of a device failure, and subsequently, the utilization of the inferred information to optimize deployment plans ensuring the resilience in the devices. These two advances are implemented in an intelligent system, Akats, whose architecture is described in detail in this article. Finally, an application scenario is presented, based on Industry 4.0 - Machine predictive maintenance, to exemplify the benefits of the proposed intelligent system.}, booktitle = {2023 8th {International} {Conference} on {Smart} and {Sustainable} {Technologies} ({SpliTech})}, author = {Diaz-de-Arcaya, Josu and Torre-Bastida, Ana I. and Bonilla, Lander and L\xf3pez-de-Armentia, Juan and Mi\xf1\xf3n, Ra\xfal and Zarate, Gorka and Almeida, Aitor}, month = jun, year = {2023}, keywords = {AIOps, Collaborative tools, Computer architecture, Edge Computing, FML, Federated Machine Learning, Fourth Industrial Revolution, Games, Intelligent systems, Internet of Things, Machine learning, Optimization}, pages = {1--4}, } ']
[u" @article{casado-mansilla_embedding_2015, title = {Embedding {Intelligent} {Eco}-aware {Systems} within {Everyday} {Things} to {Increase} {People}\u2019s {Energy} {Awareness}}, volume = {20}, issn = {1432-7643}, doi = {10.1007/s00500-015-1751-0}, abstract = {There is a lack of energy consumption awareness in working spaces. People in their workplaces do not receive energy consumption feedback nor do they pay a monthly invoice to electricity providers. In order to enhance workers' energy awareness, we have transformed everyday shared electrical appliances which are placed in common spaces (e.g. beamer projectors, coffee-makers, printers, screens, portable fans, kettles, and so on.) into persuasive eco-aware everyday things. The proposed approach lets these appliances report their usage patterns to a Cloud-server where the data is transformed into time-series and then processed to obtain the appliances' next-week usage forecast. Autoregressive Integrated Moving Average (ARIMA) model has been selected as the potentially most accurate method for processing such usage predictions when compared with the performance exhibited by three different configurations of Artificial Neural Networks (ANNs). Our major contribution is the application of soft computing techniques to the field of sustainable persuasive technologies. Thus, consumption predictions are used to trigger timely persuasive interactions to help devices users to operate the appliances as efficiently, energy-wise, as possible. Qualitative and quantitative results were gathered in a between-three-groups study related with the use of shared electrical coffee-makers at workplace. The goal of these studies was to assess the effectiveness of the proposed eco-aware design in a workplace environment in terms of energy saving and the degree of affiliation between people and the smart appliances to create a green-team relationship.}, language = {English}, number = {5}, journal = {Soft Computing Journal. Springer Berlin Heidelberg}, author = {Casado-Mansilla, Diego and {L\xf3pez-de-Armentia, Juan} and {Ventura, Daniela} and {Garaizar, Pablo} and {L\xf3pez-de-Ipi\xf1a, Diego}}, month = jun, year = {2015}, keywords = {ANN, ARIMA Models, Eco-aware Everyday Things, Persuasive Technology, Q2, Soft Computing, eco-awareness, eco-feedback, energy efficiency, hci, jcr1.630, linked-data-social-coffee-maker}, pages = {1695--1711} }"]
[u' @inproceedings{casado-mansilla_switch_2014, address = {Toronto, ON, Canada}, title = {To switch off the coffee-maker or not: that is the question to be energy-efficient at work}, copyright = {Copyright is held by the author/owner(s).}, isbn = {978-1-4503-2474-8}, shorttitle = {To switch off the coffee-maker or not}, url = {http://dl.acm.org/citation.cfm?doid=2559206.2581152}, doi = {10.1145/2559206.2581152}, abstract = {There are some barriers to reduce energy consumption in shared spaces where many people use common electronic devices (e.g. dilution of responsibility, the trade-off between comfort and necessity, absentmindedness, or the lack of support to foster energy-efficiency). The workplace is a challenging scenario since the economic incentives are not present to increase energy awareness. To tackle some of these issues we have augmented a shared coffee-maker with eco-feedback to turn it into a green ally of the workers. Its design rationale is twofold: Firstly, to make the coffee-maker able to learn its own usage pattern. Secondly, to communicate persuasively and in real-time to users whether it is more efficient to leave the appliance on or off during certain periods of time along the workday. The goal is to explore a human-machine team towards energy efficiency and awareness, i.e. whether giving the initiative to users to decide how to operate the common appliances, but being assisted by them, is a better choice than automation or mere informative eco-feedback.}, language = {en}, urldate = {2014-05-08TZ}, booktitle = {Extended {Abstracts} on {Human} {Factors} in {Computing} {Systems} ({CHI} 2014)}, publisher = {ACM New York, NY, USA \xa92014}, author = {Casado-Mansilla, Diego and Lopez-de-Armentia, Juan and Garaizar, Pablo and L\xf3pez-de-Ipi\xf1a, Diego}, year = {2014}, keywords = {Eco-aware Everyday Things, Energy-efficiency, Persuasive Technology, Sustainability, eco-feedback, linked-data-social-coffee-maker}, pages = {2425--2430} }']
[u' @incollection{hervas_ariima:_2014, address = {Cham}, title = {{ARIIMA}: {A} {Real} {IoT} {Implementation} of a {Machine}-{Learning} {Architecture} for {Reducing} {Energy} {Consumption}}, volume = {8867}, isbn = {978-3-319-13101-6 978-3-319-13102-3}, shorttitle = {{ARIIMA}}, url = {http://link.springer.com/10.1007/978-3-319-13102-3_72}, abstract = {As the inclusion of more devices and appliances within the IoT ecosystem increases, methodologies for lowering their energy consumption impact are appearing. On this field, we contribute with the implementation of a RESTful infrastructure that gives support to Internet-connected appliances to reduce their energy waste in an intelligent fashion. Our work is focused on coffee machines located in common spaces where people usually do not care on saving energy, e.g. the workplace. The proposed approach lets these kind of appliances report their usage patterns and to process their data in the Cloud through ARIMA predictive models. The aim such prediction is that the appliances get back their next-week usage forecast in order to operate autonomously as efficient as possible. The underlying distributed architecture design and implementation rationale is discussed in this paper, together with the strategy followed to get an accurate prediction matching with the real data retrieved by four coffee machines.}, urldate = {2015-04-23TZ}, booktitle = {Ubiquitous {Computing} and {Ambient} {Intelligence}. {Personalisation} and {User} {Adapted} {Services}}, publisher = {Springer International Publishing}, author = {Ventura, Daniela and Casado-Mansilla, Diego and L\xf3pez-de-Armentia, Juan and Garaizar, Pablo and L\xf3pez-de-Ipi\xf1a, Diego and Catania, Vincenzo}, editor = {Herv\xe1s, Ram\xf3n and Lee, Sungyoung and Nugent, Chris and Bravo, Jos\xe9}, year = {2014}, note = {00000}, keywords = {ARIMA Models, Eco-aware Everyday Things, Forecasting, Internet of Things, energy efficiency, linked-data-social-coffee-maker}, pages = {444--451} }']
[u' @article{lopez-de-armentia_reducing_2014, title = {Reducing energy waste through eco-aware everyday things}, volume = {10}, issn = {1574-017x}, url = {http://www.hindawi.com/journals/misy/2014/956135/abs/}, doi = {10.3233/MIS-130172}, abstract = {Society wastes much more energy than it should. This produces tons of unnecessary CO\\_2 emissions. This is partly due to the inadequate use of electrical devices given the intangible and invisible nature of energy. This misuse of devices and energy unawareness is particularly relevant in public spaces (offices, schools, hospitals and so on), where people use electrical appliances, but they do not directly pay the invoice to energy providers. Embedding intelligence within public, shared appliances, transforming them into Eco-aware things, is valuable to reduce a proportion of the unnecessarily consumed energy. To this end, we present a twofold approach for better energy efficiency in public spaces: 1) informing persuasively to concerned users about the misuse of electronic appliances; 2) Customizing the operating mode of this everyday electrical appliances as a function of their real usage pattern. To back this approach, a capsule-based coffee machine placed in a research laboratory has been augmented. This device is able to continuously collect its usage pattern to offer feedback to coffee consumers about the energy wasting and also, to intelligently adapt its operation to reduce wasted energy. To this aim, several machine learning approaches are compared and evaluated to forecast the next-day device usage.}, number = {1}, journal = {Mobile Information Systems. IOS Press}, author = {L\xf3pez-de-Armentia, Juan and Casado-Mansilla, Diego and L\xf3pez-P\xe9rez, Sergio and L\xf3pez-De-Ipi\xf1a, Diego}, month = jan, year = {2014}, keywords = {Coffee Machines, Eco-aware Everyday Things, Energy-efficiency, JCR1.789, Predictive Models, Q1, Smart Everyday Objects, Sustainability, eco-awareness, linked-data-social-coffee-maker, social devices}, pages = {79--103} }']
[u' @article{lopez-de-armentia_making_2014, title = {Making social networks a means to save energy}, issn = {1084-8045}, shorttitle = {{JNCA}}, url = {http://www.sciencedirect.com/science/article/pii/S1084804514002276}, doi = {10.1016/j.jnca.2014.09.020}, abstract = {Energy consumption in the world has increased significantly in the last few decades, becoming an important issue nowadays. The eco-aware everyday things were devised to prevent the waste of energy resources in common areas where people often elude their responsibility about the energy consumption when using appliances of collective use, like printers, coffee makers, beamers and so on. These eco-appliances are able to improve their energy efficiency dynamically adapting their operation according to their usage patterns. This work proposes a further step, also aligned with devices\u05f3 automation, where everyday consumer devices are transformed into collaborative eco-aware everyday things. Taking advantage of the evolution of the Internet towards the Internet of Things and the Web as a universal communication mechanism both among humans-to-things and things-to-things, it is proposed to use Twitter as a communication channel for eco-aware appliances to share their usage patterns. Thus, other newly deployed similar devices in comparable environments can alleviate the cold-start problem, which is common in scenarios where usage learning is needed. To assess the effectiveness of this approach, a collaboration between three of these eco-aware devices has been simulated, giving place, encouragingly, to a higher energy reduction efficiency when compared with non-collaborative objects.}, urldate = {2015-01-07TZ}, journal = {Journal of Network and Computer Applications}, author = {L\xf3pez-de-Armentia, Juan and Casado-Mansilla, Diego and L\xf3pez-de-Ipi\xf1a, Diego}, month = oct, year = {2014}, note = {00000}, keywords = {Coffee machines, Collaborative eco-aware everyday things, Eco-aware everyday things, JCR1.772, Predictive models, Q1, Smart Everyday Objects, energy-efficiency, linked-data-social-coffee-maker, social devices} }']
[u' @inproceedings{casado-mansilla_team_2014, address = {Birmingham, UK}, title = {Team up with {Eco}-aware {Everyday} {Things} to {Green} your {Workplace}!}, isbn = {978-1-4799-4331-9}, doi = {10.1109/IMIS.2014.55}, abstract = {The lack of energy consumption awareness in public spaces is a fact. There, people do not receive energy consumption feedback nor do they pay a monthly invoice to electricity providers. Thus, there is practically a non-existent perception of energy waste; and hence, there is low motivation to reduce it. To tackle this problem we transform everyday shared electrical appliances which are placed in common spaces into collaborative eco-aware everyday things. These eco-appliances make people aware that they are not alone to save energy, but the everyday things can team up with them to achieve this task. Qualitative and quantitative results were gathered in three case studies performed with shared coffee machines at workplace. The objective was to assess the effectiveness of the proposed eco-aware design in terms of energy saving and the degree of affiliation between workers and the smart appliance to create a green-team relationship.}, booktitle = {Eighth {International} {Conference} on {Innovative} {Mobile} and {Internet} {Services} in {Ubiquitous} {Computing}}, publisher = {IEEE Xplore}, author = {Casado-Mansilla, Diego and {L\xf3pez-de-Armentia, Juan} and {Pablo Garaizar} and {L\xf3pez-de-Ipi\xf1a, Diego}}, year = {2014}, keywords = {Eco-aware Everyday Things, Energy-efficiency, Persuasive Technology, Sustainability, eco-awareness, eco-feedback, hci, linked-data-social-coffee-maker, social devices}, pages = {409--414} }']
[u' @inproceedings{lopez-de-armentia_saving_2013, address = {Taichung, Taiwan}, title = {Saving {Energy} through {Collaborative} {Eco}-aware {Everyday} {Things}}, isbn = {978-0-7695-4974-3}, url = {http://ieee.164288.com/xpl/articleDetails.jsp?reload=true&arnumber=6603721}, doi = {10.1109/IMIS.2013.88}, abstract = {The reduction of energy waste in any of its forms and everywhere is a major challenge of our society. An important proportion of such waste is due to the misuse of consumer appliances of shared use in public areas (computers, printers, coffee makers,...}, language = {English}, urldate = {2013-09-20TZ}, booktitle = {The {Seventh} {International} {Conference} on {Innovative} {Mobile} and {Internet} {Services} in {Ubiquitous} {Computing}}, publisher = {IEEE Xplore}, author = {L\xf3pez-de-Armentia, Juan and Casado-Mansilla, Diego and L\xf3pez-de-Ipi\xf1a, Diego}, month = jul, year = {2013}, keywords = {Coffee Machines, Eco-aware Everyday Things, Energy-efficiency, Predictive Models, Smart Everyday Objects, eco-awareness, linked-data-social-coffee-maker, smart, social devices}, pages = {489 -- 493} }']
[u" @inproceedings{juan_lopez-de-armentia_social_2013, address = {Zurich}, title = {Social {Collaboration} of {Intelligent} {Electrical} {Devices} to {Enhance} {Energy} {Consumption}}, isbn = {978-1-4503-2215-7}, booktitle = {{UbiComp} '13 {Adjunct}}, author = {{Juan L\xf3pez-de-Armentia}}, month = aug, year = {2013}, keywords = {Coffee Machines, Eco-aware Everyday Things, Energy-efficiency, Predictive Models, Smart Everyday Objects, eco-awareness, linked-data-social-coffee-maker, social devices} }"]
[u" @inproceedings{casado-mansilla_will_2012, address = {Berlin, Heidelberg}, series = {{UCAmI}'12}, title = {Will eco-aware objects help to save the world?}, isbn = {978-3-642-35376-5}, url = {http://dx.doi.org/10.1007/978-3-642-35377-2_3}, doi = {10.1007/978-3-642-35377-2_3}, abstract = {Our society waste more energy than they should. This is mostly due to the inadequate use that human beings perform on electrical devices. The presented paper aims to justify that embedding intelligence within everyday objects is valuable to reduce the portion of unnecessary consumed energy which is due to human misusing. To such extend, we have augmented a capsule-based coffee machine which is placed in a work office to back our assumptions. Using this device we have devised an energy saving model that takes into consideration features like how and when workers use the appliance along the day. Additionally, we have simulated the model to demonstrate, through error metric comparison (measured in {\\textless}Literal{\\textgreater}KWh{\\textless}/Literal{\\textgreater} ), that a big amount of energy would be reduced if such intelligent systems were applied when compared with a baseline approach. Therefore, this paper contributes with a set of early, but promising, findings regarding how smart eco-aware objects can help to save energy in areas where people inhabit (cities, buildings or homes).}, urldate = {2013-09-23TZ}, booktitle = {Proceedings of the 6th international conference on {Ubiquitous} {Computing} and {Ambient} {Intelligence}}, publisher = {Springer-Verlag}, author = {Casado-Mansilla, Diego and L\xf3pez-de-Armentia, Juan and L\xf3pez-de-Ipi\xf1a, Diego}, year = {2012}, note = {00001}, keywords = {eco-awareness, energy-efficiency, linked-data-social-coffee-maker, smart everyday objects}, pages = {17--24} }"]
[u" @inproceedings{lopez-de-armentia_fighting_2012, address = {Palermo, Italy}, title = {Fighting against {Vampire} {Appliances} through {Eco}-{Aware} {Things}}, isbn = {978-1-4673-1328-5}, url = {http://www.computer.org/csdl/proceedings/imis/2012/4684/00/4684a868-abs.html}, doi = {10.1109/IMIS.2012.112}, abstract = {This paper provides an overview of how Internet connected objects can lead to a social change towards energy efficiency in areas where people inhabit (cities, buildings or homes). For this aim it is proposed the use of social networks, like Twitter, as an interaction and communication channel between smart objects and human beings. The presented work demonstrates, by means of an experiment, how an augmented everyday object, i.e. a capsule-based coffee machine, may help to reduce the unnecessary consumed energy in electric appliances. The paper opens the discussion of the promising potential of combining people and future smart everyday objects teaming up to promote a more sustainable behaviour on the planet's behalf.}, booktitle = {The {Sixth} {International} {Conference} on {Innovative} {Mobile} and {Internet} {Services} in {Ubiquitous} {Computing}}, publisher = {IEEE Computer Society}, author = {L\xf3pez-de-Armentia, Juan and Casado-Mansilla, Diego and L\xf3pez-de-Ipi\xf1a, Diego}, year = {2012}, keywords = {arduino, eco-awareness, energy-efficiency, linked-data-social-coffee-maker, persuasive technology, smart everyday objects, social coffee, social devices, twitter}, pages = {868--873} }"]
Dr.
Juan López de Armentia
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