Maite Puerta-Beldarrain

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[u' @inproceedings{vergara_enhancing_2024, title = {Enhancing {Citizen} {Science} {Engagement} {Through} {Gamification}: {A} {Case} {Study} of the {SOCIO}-{BEE} {Project}}, shorttitle = {Enhancing {Citizen} {Science} {Engagement} {Through} {Gamification}}, url = {https://ieeexplore.ieee.org/abstract/document/10612319}, doi = {10.23919/SpliTech61897.2024.10612319}, abstract = {The SOCIO-BEE project is a new way to improve Citizen Science (CS) by highlighting urban pollution and increasing public engagement in environmental science. CS lets everyone do scientific research, making collecting data and teaching people about important issues easier. However, it is hard to keep people interested and show them how important their work is. Adding game-like parts such as points, coins, and leaderboards can make it more exciting for people to stay involved, help each other out, and improve the quality of the data they collect. This study discusses creating and using GAME (Goals And Motivation Engine), a system that can be changed to fit different CS projects like SOCIO-BEE. It helps overcome the problems of keeping people interested and motivated. By looking at how SOCIO-BEE worked to improve air quality in cities across Europe through people working together, we show that adding game elements can increase how many people take part, improve how they collect data, and encourage them to care more about the environment. The big hopes for adding these game parts include making people more knowledgeable about science, including more people, and helping everyone understand environmental issues better.}, urldate = {2025-03-11}, booktitle = {2024 9th {International} {Conference} on {Smart} and {Sustainable} {Technologies} ({SpliTech})}, author = {Vergara, Felipe and Olivares-Rodr\xedguez, Cristian and Guenaga, Mariluz and L\xf3pez-De-Ipi\xf1a, Diego and Puerta-Beldarrain, Maite and S\xe1nchez-Corcuera, Rub\xe9n}, month = jun, year = {2024}, keywords = {Air quality, Citizen Science Engagement, Education, Environmental Conservation, Environmental science, Europe, Games, Gamification Strategies, Urban areas, Urban pollution}, pages = {1--7}, } ']

[u" @inproceedings{hernandez-jayo_socio-bee_2023, title = {{SOCIO}-{BEE}: {Example} of a {Citizen} {Science} {Community} for the {Co}-{Creation} of {Measures} to {Reduce} the {Impact} of {Environmental} {Pollution} in the {Framework} of {Smart} {Cities}}, shorttitle = {{SOCIO}-{BEE}}, url = {https://ieeexplore.ieee.org/document/10545919}, doi = {10.1109/exp.at2358782.2023.10545919}, abstract = {Despite the fact that nowadays there are many environmental monitoring stations in cities as well as different initiatives that provide open data on their measurements, there are gaps in terms of the availability and accuracy of these data. In many cases this information only gathers georeferenced data at static positions and in a number not significant enough to describe the diverse and dynamic environmental situations that can be found in an urban environment. The SOCIO-BEE initiative described in this article is not only a technological solution to obtain dynamic data from a larger geographical area, but its main objective is to involve citizens in this data collection, its exploitation and the taking of measures to help mitigate the environmental impact, all in a context of co-creation and citizen participation.}, urldate = {2025-01-07}, booktitle = {2023 6th {Experiment}@ {International} {Conference} (exp.at'23)}, author = {Hernandez-Jayo, Unai and Garcia-Zubia, Javier and L\xf3pez-De-Ipi\xf1a, Diego and Casado-Mansilla, Diego and Puerta-Beldarrain, Maite and Martelo, Alexandre Barco}, month = jun, year = {2023}, note = {ISSN: 2376-6328}, keywords = {Air quality, Atmospheric measurements, Citizen Science, Data collection, Environment Monitoring, Particle measurements, Phase measurement, Pollution, Smart City, Smart cities}, pages = {101--105}, } "]

[u' @inproceedings{puerta-beldarrain_human-ai_2023, address = {Cham}, title = {Human-{AI} {Collaboration} to {Promote} {Trust}, {Engagement} and {Adaptation} in the {Process} of {Pro}-environmental and {Health} {Behaviour} {Change}}, volume = {594}, isbn = {978-3-031-21332-8 978-3-031-21333-5}, url = {https://link.springer.com/10.1007/978-3-031-21333-5_38}, abstract = {A necessary step in the digitalization of our environments is to include the users in the decision loop, following a more human-centric paradigm. Such an aproach will make their interactions with surrounding technology closer to them. Therefore, there is a recurrent need in contemporary technological solutions to create proposals to assist users in a way that is not exclusive to them and makes them feel integrated into the intelligent system. In fact, this is particularly relevant when the proposed technology or system aims to nudge users to form, shape, or change their daily behaviours. In essence, solutions designed for assisting users in that matter need to consider the inclusion of humans in the learning/decision loop and still the literature in the field is scarce. In this work, we identify and address three crucial human requirements that this technology has to integrate to promote a comfortable and long-term use of technology for the effective assistance of behaviour change: trust, engagement, and adaptation. Besides, we propose a collaborative workflow based on hybrid intelligent systems to cover the lack of human requirements and needs of traditional approaches. In essence, this work aims to shed light on how to promote closer collaboration between humans and intelligent agents for behaviour change under the principle that people should not be treated as mere users of technologies and services, but their behaviour should become one of the critical levers for designing and using technologies. That is, creating a closer interaction between these technologies and people.}, language = {en}, urldate = {2022-11-28}, booktitle = {Proceedings of the {International} {Conference} on {Ubiquitous} {Computing} \\& {Ambient} {Intelligence} ({UCAmI} 2022)}, publisher = {Springer International Publishing}, author = {Puerta-Beldarrain, Maite and G\xf3mez-Carmona, Oihane and Casado-Mansilla, Diego and L\xf3pez-de-Ipi\xf1a, Diego}, year = {2023}, doi = {10.1007/978-3-031-21333-5_38}, note = {Series Title: Lecture Notes in Networks and Systems}, pages = {381--392}, } ']

[u" @inproceedings{puerta-beldarrain_micro-volunteering_2023, title = {A {Micro}-volunteering {Engine} to drive crowd-measuring of {Air} {Quality} in {Citizen} {Science}}, url = {https://ieeexplore.ieee.org/document/10192983}, doi = {10.23919/SpliTech58164.2023.10192983}, abstract = {Citizen Science (CS) is a great instrument to drive societal challenges. In a glimpse, CS enables the collection and analysis of data relating to the natural world by members of the general public, typically as part of a collaborative project with professional scientists. Sometimes, researchers need to frame their data collection in concentrated or sparse areas. However, there not exist a digital tool that allow to specify and area and provide geopositionded recommendations to citizen scientists to get evidence from specific points. The Micro-Volunteering Engine (MVE) that is presented in this article is responsible to provide the best fitting spatial cells that need to be measured given a user's location. MVE is used in EU project SOCIO-BEE, a project where members with different profiles organize, manage, and execute CS campaigns. Through CS campaign simulations, it is demonstrated how this engine may be usable to mobilize and drive citizens to carry out crowd-sourcing campaigns which help understanding better the effects of air pollution and, hence, aid decision-making, i.e., co-design of pro-environmental mitigation actions. The MVE is evaluated through a series of dimulations in which its performance is measured to prove its effectiveness for real uses cases of any nature.}, urldate = {2024-12-20}, booktitle = {2023 8th {International} {Conference} on {Smart} and {Sustainable} {Technologies} ({SpliTech})}, author = {Puerta-Beldarrain, Maite and G\xf3mez-Carmona, Oihane and L\xf3pez-de-Ipi\xf1a, Diego and Casado-Mansilla, Diego and Barco, Alexandre and Jayo, Unai Hern\xe1ndez and Garc\xeda-Zubia, Javier}, month = jun, year = {2023}, keywords = {Atmospheric measurements, Atmospheric modeling, Citizen Science, Collaboration, Data collection, Decision making, Fitting, Instruments, crowdsourcing, geo-position, recommendations}, pages = {1--6}, } "]