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Dr. Sergio Trilles Oliver
Universitat Jaume I

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0 Real Time System Design
0 Smart Cities
0 sensor integration
0 geoscience
0 Internet of Things - IoT

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Internet of Things - IoT
Smart Cities

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Conference paper
Published: 18 May 2021 in Communications in Computer and Information Science
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Data from automated fare collection systems have become almost essential in the study of the mobility of people using public transport. Among other advantages, the data collected enable longitudinal studies to be carried out with a detail that other sources cannot approximate. However, despite the great potential of these data, the data collecting systems are usually intended for purely accounting purposes and not for carrying out mobility studies. Largely for this reason, these data are not always used to their full potential, and so it is necessary to propose strategies that allow the preparation and exploitation of these data, especially in those cases where the usefulness and value of the data have not yet been proven. This study proposes a workflow that seeks to prevent duplication of efforts when querying this type of data. The implementation of a generic database model and a protocol for sharing meaningful queries and results greatly facilitates an initial analysis of these data. This strategy has been applied within a specific project, but it could be the basis for sharing methods between different studies.

ACS Style

Benito Zaragozí; Aaron Gutierrez; Sergio Trilles. Analysis of Public Transport Mobility Data: A System for Sharing and Reusing GIS Database Queries. Communications in Computer and Information Science 2021, 102 -118.

AMA Style

Benito Zaragozí, Aaron Gutierrez, Sergio Trilles. Analysis of Public Transport Mobility Data: A System for Sharing and Reusing GIS Database Queries. Communications in Computer and Information Science. 2021; ():102-118.

Chicago/Turabian Style

Benito Zaragozí; Aaron Gutierrez; Sergio Trilles. 2021. "Analysis of Public Transport Mobility Data: A System for Sharing and Reusing GIS Database Queries." Communications in Computer and Information Science , no. : 102-118.

Conference paper
Published: 18 May 2021 in Communications in Computer and Information Science
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Land use and land cover (LULC) information is essential in territorial planning for the study of natural risks and landscape science. Given the importance of LULC data, increasing efforts are being focused on producing quality and easily accessible databases. In Spain, the Land Use and Cover Information System (SIOSE) is a clear example of these efforts. The SIOSE database was one of the first to be built following an object-oriented data model and a set of specifications that facilitates the integration of data from different sources. However, the SIOSE information alone is so accurate and complete that there is a usability gap that means that this data is not used to its full potential in some contexts, nor is the possibility of integrating other data sources considered. In this work, we examine the circumstances of this usability gap, its causes and consequences, and we introduce an extension of the SIOSE object-oriented data model that will enable enriching the LULC data including new useful data for different types of studies. Finally, an example of implementation of this extended model serves to encourage the user community to propose and disseminate new extended LULC datasets that facilitate various types of landscape studies.

ACS Style

Benito Zaragozí; Jesús Javier Rodríguez-Sala; Sergio Trilles; Alfredo Ramón-Morte. Integration of New Data Layers to Support the Land Cover and Use Information System of Spain (SIOSE): An Approach from Object-Oriented Modelling. Communications in Computer and Information Science 2021, 85 -101.

AMA Style

Benito Zaragozí, Jesús Javier Rodríguez-Sala, Sergio Trilles, Alfredo Ramón-Morte. Integration of New Data Layers to Support the Land Cover and Use Information System of Spain (SIOSE): An Approach from Object-Oriented Modelling. Communications in Computer and Information Science. 2021; ():85-101.

Chicago/Turabian Style

Benito Zaragozí; Jesús Javier Rodríguez-Sala; Sergio Trilles; Alfredo Ramón-Morte. 2021. "Integration of New Data Layers to Support the Land Cover and Use Information System of Spain (SIOSE): An Approach from Object-Oriented Modelling." Communications in Computer and Information Science , no. : 85-101.

Review
Published: 28 February 2021 in Atmosphere
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Air pollution and its consequences are negatively impacting on the world population and the environment, which converts the monitoring and forecasting air quality techniques as essential tools to combat this problem. To predict air quality with maximum accuracy, along with the implemented models and the quantity of the data, it is crucial also to consider the dataset types. This study selected a set of research works in the field of air quality prediction and is concentrated on the exploration of the datasets utilised in them. The most significant findings of this research work are: (1) meteorological datasets were used in 94.6% of the papers leaving behind the rest of the datasets with a big difference, which is complemented with others, such as temporal data, spatial data, and so on; (2) the usage of various datasets combinations has been commenced since 2009; and (3) the utilisation of open data have been started since 2012, 32.3% of the studies used open data, and 63.4% of the studies did not provide the data.

ACS Style

Ditsuhi Iskandaryan; Francisco Ramos; Sergio Trilles. Features Exploration from Datasets Vision in Air Quality Prediction Domain. Atmosphere 2021, 12, 312 .

AMA Style

Ditsuhi Iskandaryan, Francisco Ramos, Sergio Trilles. Features Exploration from Datasets Vision in Air Quality Prediction Domain. Atmosphere. 2021; 12 (3):312.

Chicago/Turabian Style

Ditsuhi Iskandaryan; Francisco Ramos; Sergio Trilles. 2021. "Features Exploration from Datasets Vision in Air Quality Prediction Domain." Atmosphere 12, no. 3: 312.

Journal article
Published: 22 February 2021 in ISPRS International Journal of Geo-Information
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The article uses passive mobile data to analyse the complex mobilities that occur in a coastal region characterised by seasonal patterns of tourism activity. A large volume of data generated by mobile phone users has been selected and processed to subsequently display the information in the form of visualisations that are useful for transport and tourism research, policy, and practice. More specifically, the analysis consisted of four steps: (1) a dataset containing records for four days—two on summer days and two in winter—was selected, (2) these were aggregated spatially, temporally, and differentiating trips by local residents, national tourists, and international tourists, (3) origin-destination matrices were built, and (4) graph-based visualisations were created to provide evidence on the nature of the mobilities affecting the study area. The results of our work provide new evidence of how the analysis of passive mobile data can be useful to study the effects of tourism seasonality in local mobility patterns.

ACS Style

Benito Zaragozí; Sergio Trilles; Aaron Gutiérrez. Passive Mobile Data for Studying Seasonal Tourism Mobilities: an Application in a Mediterranean Coastal Destination. ISPRS International Journal of Geo-Information 2021, 10, 98 .

AMA Style

Benito Zaragozí, Sergio Trilles, Aaron Gutiérrez. Passive Mobile Data for Studying Seasonal Tourism Mobilities: an Application in a Mediterranean Coastal Destination. ISPRS International Journal of Geo-Information. 2021; 10 (2):98.

Chicago/Turabian Style

Benito Zaragozí; Sergio Trilles; Aaron Gutiérrez. 2021. "Passive Mobile Data for Studying Seasonal Tourism Mobilities: an Application in a Mediterranean Coastal Destination." ISPRS International Journal of Geo-Information 10, no. 2: 98.

Journal article
Published: 18 November 2020 in Sensors
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Temperature, humidity and precipitation have a strong influence on the generation of diseases in different crops, especially in vine. In recent years, advances in different disciplines have enabled the deployment of sensor nodes on agricultural plots. These sensors are characterised by a low cost and so the reliability of the data obtained from them can be compromised, as they are built from low-confidence components. In this research, two studies were carried out to determine the reliability of the data obtained by different SEnviro nodes installed in vineyards. Two networks of meteorological stations were used to carry out these studies, one official and the other professional. The first study was based on calculating the homogenisation of the data, which was performed using the Climatol tool. The second study proposed a similarity analysis using cross-correlation. The results showed that the low-cost node can be used to monitor climatic conditions in an agricultural area in the central zone of the province of Castelló (Spain) and to obtain reliable observations for use in previously published fungal disease models.

ACS Style

Sergio Trilles; Pablo Juan; Carlos Díaz-Avalos; Sara Ribeiro; Marco Painho. Reliability Evaluation of the Data Acquisition Potential of a Low-Cost Climatic Network for Applications in Agriculture. Sensors 2020, 20, 6597 .

AMA Style

Sergio Trilles, Pablo Juan, Carlos Díaz-Avalos, Sara Ribeiro, Marco Painho. Reliability Evaluation of the Data Acquisition Potential of a Low-Cost Climatic Network for Applications in Agriculture. Sensors. 2020; 20 (22):6597.

Chicago/Turabian Style

Sergio Trilles; Pablo Juan; Carlos Díaz-Avalos; Sara Ribeiro; Marco Painho. 2020. "Reliability Evaluation of the Data Acquisition Potential of a Low-Cost Climatic Network for Applications in Agriculture." Sensors 20, no. 22: 6597.

Data article
Published: 18 November 2020 in Data in Brief
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Inadequate weather conditions are one of the main threats to the correct development of sensitive crops, where a bad situation can lead to greater stress on plants and their weakness against various diseases. This statement is especially decisive in the cultivation of the vineyard. Meteorological monitoring of vineyard parcels is vital to detect and prevent possible fungal diseases. The development of new Information and Communication Technologies, linked to the Smart Farming movement, together with the reduced cost of electronic components, have favoured a greater availability of meteorological monitoring stations to get to know first-class hand the state of the vineyard smallholdings. This work provides a set of over 750,000 environmental raw data records collected by low-cost Internet of Things nodes, primarily located within vineyard smallholdings. The published observations were collected between 2018-04-01 and 2018-10-31 and were validated in previous research to determine the data's reliability.

ACS Style

Sergio Trilles; Alberto González-Pérez; Benito Zaragozí; Joaquín Huerta. Data on records of environmental phenomena using low-cost sensors in vineyard smallholdings. Data in Brief 2020, 33, 106524 .

AMA Style

Sergio Trilles, Alberto González-Pérez, Benito Zaragozí, Joaquín Huerta. Data on records of environmental phenomena using low-cost sensors in vineyard smallholdings. Data in Brief. 2020; 33 ():106524.

Chicago/Turabian Style

Sergio Trilles; Alberto González-Pérez; Benito Zaragozí; Joaquín Huerta. 2020. "Data on records of environmental phenomena using low-cost sensors in vineyard smallholdings." Data in Brief 33, no. : 106524.

Journal article
Published: 26 September 2020 in Applied Sciences
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The growing popularity of soccer has led to the prediction of match results becoming of interest to the research community. The aim of this research is to detect the effects of weather on the result of matches by implementing Random Forest, Support Vector Machine, K-Nearest Neighbors Algorithm, and Extremely Randomized Trees Classifier. The analysis was executed using the Spanish La Liga and Segunda division from the seasons 2013–2014 to 2017–2018 in combination with weather data. Two tasks were proposed as part of this study: the first was to find out whether the game will end in a draw, a win by the hosts or a victory by the guests, and the second was to determine whether the match will end in a draw or if one of the teams will win. The results show that, for the first task, Extremely Randomized Trees Classifier is a better method, with an accuracy of 65.9%, and, for the second task, Support Vector Machine yielded better results with an accuracy of 79.3%. Moreover, it is possible to predict whether the game will end in a draw or not with 0.85 AUC-ROC. Additionally, for comparative purposes, the analysis was also performed without weather data.

ACS Style

Ditsuhi Iskandaryan; Francisco Ramos; Denny Asarias Palinggi; Sergio Trilles. The Effect of Weather in Soccer Results: An Approach Using Machine Learning Techniques. Applied Sciences 2020, 10, 6750 .

AMA Style

Ditsuhi Iskandaryan, Francisco Ramos, Denny Asarias Palinggi, Sergio Trilles. The Effect of Weather in Soccer Results: An Approach Using Machine Learning Techniques. Applied Sciences. 2020; 10 (19):6750.

Chicago/Turabian Style

Ditsuhi Iskandaryan; Francisco Ramos; Denny Asarias Palinggi; Sergio Trilles. 2020. "The Effect of Weather in Soccer Results: An Approach Using Machine Learning Techniques." Applied Sciences 10, no. 19: 6750.

Erratum
Published: 08 September 2020 in ISPRS International Journal of Geo-Information
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The authors wish to make the following corrections to their paper

ACS Style

Pravesh Yagol; Francisco Ramos; Sergio Trilles; Joaquín Torres-Sospedra; Francisco J. Perales. Erratum: Ramos, F.; Trilles, S.; Torres-Sospedra, J.; Perales, F.J. New Trends in Using Augmented Reality Apps for Smart City Contexts. ISPRS Int. J. Geo-Inf. 2018, 7, 478. ISPRS International Journal of Geo-Information 2020, 9, 537 .

AMA Style

Pravesh Yagol, Francisco Ramos, Sergio Trilles, Joaquín Torres-Sospedra, Francisco J. Perales. Erratum: Ramos, F.; Trilles, S.; Torres-Sospedra, J.; Perales, F.J. New Trends in Using Augmented Reality Apps for Smart City Contexts. ISPRS Int. J. Geo-Inf. 2018, 7, 478. ISPRS International Journal of Geo-Information. 2020; 9 (9):537.

Chicago/Turabian Style

Pravesh Yagol; Francisco Ramos; Sergio Trilles; Joaquín Torres-Sospedra; Francisco J. Perales. 2020. "Erratum: Ramos, F.; Trilles, S.; Torres-Sospedra, J.; Perales, F.J. New Trends in Using Augmented Reality Apps for Smart City Contexts. ISPRS Int. J. Geo-Inf. 2018, 7, 478." ISPRS International Journal of Geo-Information 9, no. 9: 537.

Journal article
Published: 17 August 2020 in IEEE Transactions on Mobile Computing
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Wi-Fi fingerprinting is a well-known technique used for indoor positioning. It relies on a pattern recognition method that compares the captured operational fingerprint with a set of previously collected reference samples (radio map) using a similarity function. The matching algorithms suffer from a scalability problem in large deployments with a huge density of fingerprints, where the number of reference samples in the training dataset is prohibitively large. This paper presents a comprehensive comparative study of existing methods to reduce the complexity and size of the radio map used at the operational stage. Our empirical results show that most of the methods reduce the computational burden at the expense of failing to provide a competitive accuracy. Among the studied methods, only k-means, affinity propagation, and the rules based on the strongest Access Point properly balance the positioning accuracy and computational time. In addition to the comparative results, this paper also introduces a new evaluation framework with multiple datasets, aiming at getting more general results and contributing to a better reproducibility of new proposed solutions in the future.

ACS Style

Joaquin Torres-Sospedra; Philipp Richter; Adriano Moreira; German M. Mendoza-Silva; Elena-Simona Lohan; Sergio Trilles; Miguel Matey-Sanz; Joaquin Huerta. A Comprehensive and Reproducible Comparison of Clustering and Optimization Rules in Wi-Fi Fingerprinting. IEEE Transactions on Mobile Computing 2020, PP, 1 -1.

AMA Style

Joaquin Torres-Sospedra, Philipp Richter, Adriano Moreira, German M. Mendoza-Silva, Elena-Simona Lohan, Sergio Trilles, Miguel Matey-Sanz, Joaquin Huerta. A Comprehensive and Reproducible Comparison of Clustering and Optimization Rules in Wi-Fi Fingerprinting. IEEE Transactions on Mobile Computing. 2020; PP (99):1-1.

Chicago/Turabian Style

Joaquin Torres-Sospedra; Philipp Richter; Adriano Moreira; German M. Mendoza-Silva; Elena-Simona Lohan; Sergio Trilles; Miguel Matey-Sanz; Joaquin Huerta. 2020. "A Comprehensive and Reproducible Comparison of Clustering and Optimization Rules in Wi-Fi Fingerprinting." IEEE Transactions on Mobile Computing PP, no. 99: 1-1.

Research article
Published: 17 August 2020 in Computer Applications in Engineering Education
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University students enroling in Science, Technology, Engineering and Mathematics (STEM)‐related studies such as computer science continue to decline, even though worldwide educational policy reports warn about the need for this type of professionals in the immediate future. Promoting computer science studies among preuniversity students seems the most direct solution to reverse this issue. In this context, we present the Sucre4Kids project whose main objectives are to engage young people into computational thinking and programming concepts using tangible elements and social interaction. We apply the Sucre4Kids approach to introductory courses of computational thinking and programming concepts to high‐school students. The main results of the 3‐year intervention in the classroom with 256 high‐school students reached suggest that tangible elements and social interaction in groups are determining factors in increasing students' motivation to learn to code and to raise their interest in STEM disciplines.

ACS Style

Sergio Trilles; Carlos Granell. Advancing preuniversity students' computational thinking skills through an educational project based on tangible elements and virtual block‐based programming. Computer Applications in Engineering Education 2020, 28, 1490 -1502.

AMA Style

Sergio Trilles, Carlos Granell. Advancing preuniversity students' computational thinking skills through an educational project based on tangible elements and virtual block‐based programming. Computer Applications in Engineering Education. 2020; 28 (6):1490-1502.

Chicago/Turabian Style

Sergio Trilles; Carlos Granell. 2020. "Advancing preuniversity students' computational thinking skills through an educational project based on tangible elements and virtual block‐based programming." Computer Applications in Engineering Education 28, no. 6: 1490-1502.

Journal article
Published: 24 April 2020 in Sensors
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Nowadays, the concept of “Everything is connected to Everything” has spread to reach increasingly diverse scenarios, due to the benefits of constantly being able to know, in real-time, the status of your factory, your city, your health or your smallholding. This wide variety of scenarios creates different challenges such as the heterogeneity of IoT devices, support for large numbers of connected devices, reliable and safe systems, energy efficiency and the possibility of using this system by third-parties in other scenarios. A transversal middleware in all IoT solutions is called an IoT platform. the IoT platform is a piece of software that works like a kind of “glue” to combine platforms and orchestrate capabilities that connect devices, users and applications/services in a “cyber-physical” world. In this way, the IoT platform can help solve the challenges listed above. This paper proposes an IoT agnostic architecture, highlighting the role of the IoT platform, within a broader ecosystem of interconnected tools, aiming at increasing scalability, stability, interoperability and reusability. For that purpose, different paradigms of computing will be used, such as microservices architecture and serverless computing. Additionally, a technological proposal of the architecture, called SEnviro Connect, is presented. This proposal is validated in the IoT scenario of smart farming, where five IoT devices (SEnviro nodes) have been deployed to improve wine production. A comprehensive performance evaluation is carried out to guarantee a scalable and stable platform.

ACS Style

Sergio Trilles; Alberto González-Pérez; Joaquín Huerta. An IoT Platform Based on Microservices and Serverless Paradigms for Smart Farming Purposes. Sensors 2020, 20, 2418 .

AMA Style

Sergio Trilles, Alberto González-Pérez, Joaquín Huerta. An IoT Platform Based on Microservices and Serverless Paradigms for Smart Farming Purposes. Sensors. 2020; 20 (8):2418.

Chicago/Turabian Style

Sergio Trilles; Alberto González-Pérez; Joaquín Huerta. 2020. "An IoT Platform Based on Microservices and Serverless Paradigms for Smart Farming Purposes." Sensors 20, no. 8: 2418.

Review
Published: 01 April 2020 in Applied Sciences
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The influence of machine learning technologies is rapidly increasing and penetrating almost in every field, and air pollution prediction is not being excluded from those fields. This paper covers the revision of the studies related to air pollution prediction using machine learning algorithms based on sensor data in the context of smart cities. Using the most popular databases and executing the corresponding filtration, the most relevant papers were selected. After thorough reviewing those papers, the main features were extracted, which served as a base to link and compare them to each other. As a result, we can conclude that: (1) instead of using simple machine learning techniques, currently, the authors apply advanced and sophisticated techniques, (2) China was the leading country in terms of a case study, (3) Particulate matter with diameter equal to 2.5 micrometers was the main prediction target, (4) in 41% of the publications the authors carried out the prediction for the next day, (5) 66% of the studies used data had an hourly rate, (6) 49% of the papers used open data and since 2016 it had a tendency to increase, and (7) for efficient air quality prediction it is important to consider the external factors such as weather conditions, spatial characteristics, and temporal features.

ACS Style

Ditsuhi Iskandaryan; Francisco Ramos; Sergio Trilles. Air Quality Prediction in Smart Cities Using Machine Learning Technologies based on Sensor Data: A Review. Applied Sciences 2020, 10, 2401 .

AMA Style

Ditsuhi Iskandaryan, Francisco Ramos, Sergio Trilles. Air Quality Prediction in Smart Cities Using Machine Learning Technologies based on Sensor Data: A Review. Applied Sciences. 2020; 10 (7):2401.

Chicago/Turabian Style

Ditsuhi Iskandaryan; Francisco Ramos; Sergio Trilles. 2020. "Air Quality Prediction in Smart Cities Using Machine Learning Technologies based on Sensor Data: A Review." Applied Sciences 10, no. 7: 2401.

Journal article
Published: 25 February 2020 in ISPRS International Journal of Geo-Information
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Scientific reproducibility is essential for the advancement of science. It allows the results of previous studies to be reproduced, validates their conclusions and develops new contributions based on previous research. Nowadays, more and more authors consider that the ultimate product of academic research is the scientific manuscript, together with all the necessary elements (i.e., code and data) so that others can reproduce the results. However, there are numerous difficulties for some studies to be reproduced easily (i.e., biased results, the pressure to publish, and proprietary data). In this context, we explain our experience in an attempt to improve the reproducibility of a GIScience project. According to our project needs, we evaluated a list of practices, standards and tools that may facilitate open and reproducible research in the geospatial domain, contextualising them on Peng’s reproducibility spectrum. Among these resources, we focused on containerisation technologies and performed a shallow review to reflect on the level of adoption of these technologies in combination with OSGeo software. Finally, containerisation technologies proved to enhance the reproducibility and we used UML diagrams to describe representative work-flows deployed in our GIScience project.

ACS Style

Benito M. Zaragozí; Sergio Trilles; José T. Navarro-Carrión. Leveraging Container Technologies in a GIScience Project: A Perspective from Open Reproducible Research. ISPRS International Journal of Geo-Information 2020, 9, 138 .

AMA Style

Benito M. Zaragozí, Sergio Trilles, José T. Navarro-Carrión. Leveraging Container Technologies in a GIScience Project: A Perspective from Open Reproducible Research. ISPRS International Journal of Geo-Information. 2020; 9 (3):138.

Chicago/Turabian Style

Benito M. Zaragozí; Sergio Trilles; José T. Navarro-Carrión. 2020. "Leveraging Container Technologies in a GIScience Project: A Perspective from Open Reproducible Research." ISPRS International Journal of Geo-Information 9, no. 3: 138.

Research article
Published: 31 January 2020 in PLOS ONE
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Scientific research results are traditionally published as articles in peer-reviewed conference proceedings or journals. These articles often use technical jargon, which precludes the general public from consuming the results achieved. New ways to communicate scientific results are thus necessary to transfer scientific insights to non-experts, and this work proposes the concept of interactive guidelines to fill this gap. A web tool, called Interactive Guidelines Tool, was developed as a proof-of-concept for the idea. It was used in the context of the GEO-C project to communicate research outputs in smart cities scenarios to the public. A comparative analysis between the Interactive Guidelines Tool and related tools helps to highlight the progress it enables beyond the current state of the art. Interactive Guidelines Tool is available as an open-source tool and can be customised/extended by any interested researcher, in the process of making scientific knowledge and insights more accessible and understandable to a broader public.

ACS Style

Sergio Trilles; Carlos Granell; Auriol Degbelo; Devanjan Bhattacharya. Interactive guidelines: Public communication of data-based research in cities. PLOS ONE 2020, 15, e0228008 .

AMA Style

Sergio Trilles, Carlos Granell, Auriol Degbelo, Devanjan Bhattacharya. Interactive guidelines: Public communication of data-based research in cities. PLOS ONE. 2020; 15 (1):e0228008.

Chicago/Turabian Style

Sergio Trilles; Carlos Granell; Auriol Degbelo; Devanjan Bhattacharya. 2020. "Interactive guidelines: Public communication of data-based research in cities." PLOS ONE 15, no. 1: e0228008.

Journal article
Published: 16 December 2019 in Sustainability
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A suitable and quick determination of air quality allows the population to be alerted with respect to high concentrations of pollutants. Recent advances in computer science have led to the development of a high number of low-cost sensors, improving the spatial and temporal resolution of air quality data while increasing the effectiveness of risk assessment. The main objective of this work is to perform a validation of a particulate matter (PM) sensor (HM-3301) in indoor and outdoor environments to study PM2.5 and PM10 concentrations. To date, this sensor has not been evaluated in real-world situations, and its data quality has not been documented. Here, the HM-3301 sensor is integrated into an Internet of things (IoT) platform to establish a permanent Internet connection. The validation is carried out using a reference sampler (LVS3 of Derenda) according to EN12341:2014. It is focused on statistical insight, and environmental conditions are not considered in this study. The ordinary Linear Model, the Generalized Linear Model, Locally Estimated Scatterplot Smoothing, and the Generalized Additive Model have been proposed to compare and contrast the outcomes. The low-cost sensor is highly correlated with the reference measure ( R 2 greater than 0.70), especially for PM2.5, with a very high accuracy value. In addition, there is a positive relationship between the two measurements, which can be appropriately fitted through the Locally Estimated Scatterplot Smoothing model.

ACS Style

Sergio Trilles; Ana Belen Vicente; Pablo Juan; Francisco Ramos; Sergi Meseguer; Laura Serra. Reliability Validation of a Low-Cost Particulate Matter IoT Sensor in Indoor and Outdoor Environments Using a Reference Sampler. Sustainability 2019, 11, 7220 .

AMA Style

Sergio Trilles, Ana Belen Vicente, Pablo Juan, Francisco Ramos, Sergi Meseguer, Laura Serra. Reliability Validation of a Low-Cost Particulate Matter IoT Sensor in Indoor and Outdoor Environments Using a Reference Sampler. Sustainability. 2019; 11 (24):7220.

Chicago/Turabian Style

Sergio Trilles; Ana Belen Vicente; Pablo Juan; Francisco Ramos; Sergi Meseguer; Laura Serra. 2019. "Reliability Validation of a Low-Cost Particulate Matter IoT Sensor in Indoor and Outdoor Environments Using a Reference Sampler." Sustainability 11, no. 24: 7220.

Chapter
Published: 20 November 2019 in Manual of Digital Earth
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Digital Earth was born with the aim of replicating the real world within the digital world. Many efforts have been made to observe and sense the Earth, both from space (remote sensing) and by using in situ sensors. Focusing on the latter, advances in Digital Earth have established vital bridges to exploit these sensors and their networks by taking location as a key element. The current era of connectivity envisions that everything is connected to everything. The concept of the Internet of Things (IoT) emerged as a holistic proposal to enable an ecosystem of varied, heterogeneous networked objects and devices to speak to and interact with each other. To make the IoT ecosystem a reality, it is necessary to understand the electronic components, communication protocols, real-time analysis techniques, and the location of the objects and devices. The IoT ecosystem and the Digital Earth (DE) jointly form interrelated infrastructures for addressing today’s pressing issues and complex challenges. In this chapter, we explore the synergies and frictions in establishing an efficient and permanent collaboration between the two infrastructures, in order to adequately address multidisciplinary and increasingly complex real-world problems. Although there are still some pending issues, the identified synergies generate optimism for a true collaboration between the Internet of Things and the Digital Earth.

ACS Style

Carlos Granell; Andreas Kamilaris; Alexander Kotsev; Frank O. Ostermann; Sergio Trilles. Internet of Things. Manual of Digital Earth 2019, 387 -423.

AMA Style

Carlos Granell, Andreas Kamilaris, Alexander Kotsev, Frank O. Ostermann, Sergio Trilles. Internet of Things. Manual of Digital Earth. 2019; ():387-423.

Chicago/Turabian Style

Carlos Granell; Andreas Kamilaris; Alexander Kotsev; Frank O. Ostermann; Sergio Trilles. 2019. "Internet of Things." Manual of Digital Earth , no. : 387-423.

Dissertation
Published: 15 November 2019
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ACS Style

Sergio Trilles Oliver. Aproximación al tratamiento completo del ciclo de vida sobre datos provenientes de sensores mediante estándares GIS. 2019, 1 .

AMA Style

Sergio Trilles Oliver. Aproximación al tratamiento completo del ciclo de vida sobre datos provenientes de sensores mediante estándares GIS. . 2019; ():1.

Chicago/Turabian Style

Sergio Trilles Oliver. 2019. "Aproximación al tratamiento completo del ciclo de vida sobre datos provenientes de sensores mediante estándares GIS." , no. : 1.

Journal article
Published: 22 October 2019 in Sustainability
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A statistical modelling of PM10 concentration (2006–2015) is applied to understand the behaviour, to know the influence of the variables to exposure risk, to treat the missing data to evaluate air quality, and to estimate data for those sites where they are not available. The study area, Castellón region (Spain), is a strategic area in the framework of EU pollution control. A decrease of PM10 is observed for industrial and urban stations. In the case of rural stations, the levels remain constant throughout the study period. The contribution of anthropogenic sources has been estimated through the PM10 background of the study area. The behaviour of PM10 annual trend is tri-modal for industrial and urban stations and bi-modal in the case of rural stations. The EU Normative suggests that 90% of the data per year are necessary to control air quality. Thus, interpolation statistical methods are presented to fill missing data: Linear Interpolation, Exponential Interpolation, and Kalman Smoothing. This study also focuses on testing the goodness of these methods in order to find the ones that better approach the gaps. After analyzing graphically and using the RMSE the last method is confirmed to be the best option.

ACS Style

Ana Belen Vicente; Pablo Juan; Sergi Meseguer; Laura Serra; Sergio Trilles. Air Quality Trend of PM10. Statistical Models for Assessing the Air Quality Impact of Environmental Policies. Sustainability 2019, 11, 5857 .

AMA Style

Ana Belen Vicente, Pablo Juan, Sergi Meseguer, Laura Serra, Sergio Trilles. Air Quality Trend of PM10. Statistical Models for Assessing the Air Quality Impact of Environmental Policies. Sustainability. 2019; 11 (20):5857.

Chicago/Turabian Style

Ana Belen Vicente; Pablo Juan; Sergi Meseguer; Laura Serra; Sergio Trilles. 2019. "Air Quality Trend of PM10. Statistical Models for Assessing the Air Quality Impact of Environmental Policies." Sustainability 11, no. 20: 5857.

Journal article
Published: 24 January 2019 in Sustainable Computing: Informatics and Systems
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In recent years, some official reports, to produce best products regarding quality, quantity and economic conditions, recommend that the farming sector should benefit with new tools and techniques coming from Information and Communications Technology (ICT) realm. In this way, during last decade the deployment of sensing devices has increased considerably in the field of agriculture. This fact has led to a new concept called smart agriculture, and it contemplates activities such as field monitoring, which offer support to make decisions or perform actions, such as irrigation or fertilization. Apart from sensing devices, which use the Internet protocol to transfer data (Internet of Things), there are the so-called crop models, which are able to provide added value over the data provided by the sensors, with the aim of providing recommendations to farmers in decision-making and thus, increase the quality and quantity of their production. In this scenario, the current work uses a low-cost sensorized platform, capable of monitoring meteorological phenomena following the Internet of Things paradigm, with the goal to apply an alert disease model on the cultivation of the vine. The edge computing paradigm is used to achieve this objective; also our work follows some advances from GIScience to increase interoperability. An example of this platform has been deployed in a vineyard parcel located in the municipality of Vilafamés (Castelló, Spain).

ACS Style

Sergio Trilles; Joaquín Torres-Sospedra; Óscar Belmonte; F. Javier Zarazaga-Soria; Alberto González-Pérez; Joaquín Huerta. Development of an open sensorized platform in a smart agriculture context: A vineyard support system for monitoring mildew disease. Sustainable Computing: Informatics and Systems 2019, 28, 100309 .

AMA Style

Sergio Trilles, Joaquín Torres-Sospedra, Óscar Belmonte, F. Javier Zarazaga-Soria, Alberto González-Pérez, Joaquín Huerta. Development of an open sensorized platform in a smart agriculture context: A vineyard support system for monitoring mildew disease. Sustainable Computing: Informatics and Systems. 2019; 28 ():100309.

Chicago/Turabian Style

Sergio Trilles; Joaquín Torres-Sospedra; Óscar Belmonte; F. Javier Zarazaga-Soria; Alberto González-Pérez; Joaquín Huerta. 2019. "Development of an open sensorized platform in a smart agriculture context: A vineyard support system for monitoring mildew disease." Sustainable Computing: Informatics and Systems 28, no. : 100309.

Journal article
Published: 15 January 2019 in Sustainability
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Weather conditions are one of the main threats that can lead to diseases in crops. Unfavourable conditions, such as rain or high humidity, can produce a risk of fungal diseases. Meteorological monitoring is vital to have some indication of a possible infection. The literature contains a wide variety of models for warning for this type of disease.These are capable of warning when an infection may be present. Devices (weather stations) able to measure weather conditions in real-time are needed to know precisely when an infection occurs in a smallholding. Besides, such models cannot be executed at the same time in which the observations are collected; in fact, these models are usually executed in batches at a rate of one per day. Therefore, these models need to be adapted to run at the same frequency as that at which observations are collected so that a possible disease can be dealt with as early as possible. The primary aim of this work is to adapt disease warning models to run in (near) real-time over meteorological variables generated by Internet of Things (IoT) devices, in order to inform farmers as quickly as possible if their crop is in danger of being infected by diseases, and to enable them to tackle the infection with the appropriate treatments. The work is centered on vineyards and has been tested in four different smallholdings in the province of Castellón (Spain).

ACS Style

Sergio Trilles Oliver; Alberto González-Pérez; Joaquín Huerta Guijarro. Adapting Models to Warn Fungal Diseases in Vineyards Using In-Field Internet of Things (IoT) Nodes. Sustainability 2019, 11, 416 .

AMA Style

Sergio Trilles Oliver, Alberto González-Pérez, Joaquín Huerta Guijarro. Adapting Models to Warn Fungal Diseases in Vineyards Using In-Field Internet of Things (IoT) Nodes. Sustainability. 2019; 11 (2):416.

Chicago/Turabian Style

Sergio Trilles Oliver; Alberto González-Pérez; Joaquín Huerta Guijarro. 2019. "Adapting Models to Warn Fungal Diseases in Vineyards Using In-Field Internet of Things (IoT) Nodes." Sustainability 11, no. 2: 416.