2021
Trilles-Oliver, Sergio; Juan-Verdoy, Pablo; Chaudhuric, Somnath; Fortea, Ana Belen Vicente
Data on CO2, temperature and air humidity records in Spanish classrooms during the reopening of schools in the COVID-19 pandemic Journal Article
In: Data in Brief, vol. 39, pp. 107489, 2021, ISSN: 2352-3409.
Abstract | Links | BibTeX | Tags: Air quality sensors, Internet of things
@article{Trilles2021a,
title = {Data on CO2, temperature and air humidity records in Spanish classrooms during the reopening of schools in the COVID-19 pandemic},
author = {Sergio Trilles-Oliver and Pablo Juan-Verdoy and Somnath Chaudhuric and Ana Belen Vicente Fortea},
doi = {https://doi.org/10.1016/j.dib.2021.107489},
issn = {2352-3409},
year = {2021},
date = {2021-12-01},
journal = {Data in Brief},
volume = {39},
pages = {107489},
abstract = {In order to reduce the advance of the pandemic produced by COVID-19, many actions and restrictions have been applied and the field of education has been no exception. In Spain, during the academic year 2020–2021, face-to-face teaching generally continued in both primary and secondary schools. Throughout the year, different measures have been taken to reduce the likelihood of contagion in classrooms, one of which was to improve ventilation by opening windows and doors. One of the most commonly used techniques to check for good ventilation has been CO2 monitoring. This work provides a set of 80,000 CO2 concentration records collected by low-cost Internet of Things nodes, primarily located within twelve classrooms in two primary schools. The published observations were collected between 1 May 2020 and 23 June 2021. Additionally, the same dataset includes temperature, air humidity and battery level observations.},
keywords = {Air quality sensors, Internet of things},
pubstate = {published},
tppubtype = {article}
}
In order to reduce the advance of the pandemic produced by COVID-19, many actions and restrictions have been applied and the field of education has been no exception. In Spain, during the academic year 2020–2021, face-to-face teaching generally continued in both primary and secondary schools. Throughout the year, different measures have been taken to reduce the likelihood of contagion in classrooms, one of which was to improve ventilation by opening windows and doors. One of the most commonly used techniques to check for good ventilation has been CO2 monitoring. This work provides a set of 80,000 CO2 concentration records collected by low-cost Internet of Things nodes, primarily located within twelve classrooms in two primary schools. The published observations were collected between 1 May 2020 and 23 June 2021. Additionally, the same dataset includes temperature, air humidity and battery level observations.
Juan-Verdoy, Pablo; Trilles-Oliver, Sergio; Fortea, Ana Belén Vicente; Costa, Sergi Messeguer; Saurina, Laura Serra
Estudio de la fiabilidad de un sensor IoT de PM de bajo coste en ambientes interiores y exteriores Proceedings Article
In: Congreso Nacional de Medio Ambiente 2020 (CONAMA 2020), pp. 1-20, 2021, ISBN: 978-84-09-31739-4.
Abstract | BibTeX | Tags: Air quality sensors, Internet of things
@inproceedings{JuanVerdoy2021a,
title = {Estudio de la fiabilidad de un sensor IoT de PM de bajo coste en ambientes interiores y exteriores},
author = {Pablo Juan-Verdoy and Sergio Trilles-Oliver and Ana Belén Vicente Fortea and Sergi Messeguer Costa and Laura Serra Saurina},
isbn = {978-84-09-31739-4},
year = {2021},
date = {2021-07-01},
booktitle = {Congreso Nacional de Medio Ambiente 2020 (CONAMA 2020)},
pages = {1-20},
abstract = {El conocimiento en tiempo real de la calidad del aire permite alertar a la población frente a los episodios de alta concentración de una forma rápida y directa. Los recientes avances en el campo de la sensorización, y las tecnologías y ciencias de la computación, han facilitado el despliegue de sensores de bajo coste, mejorando la resolución espacial y temporal de los datos
de calidad del aire. El objetivo principal de este trabajo es realizar un estudio de fiabilidad de un sensor de bajo coste de partículas en suspensión (PM2.5 y PM10) en ambientes interiores y exteriores, con la finalidad de conocer si puede ser candidato a poder ser utilizado en Planes de Gestión de la Calidad del Aire. El sensor láser seleccionado (HM-3301), hasta el momento, no ha sido evaluado en condiciones ambientales reales, y la calidad de los datos generados no se encuentra documentada. Para posibilitar este estudio, el sensor HM-3301 ha sido integrado en una plataforma del Internet de las Cosas, con el objetivo de establecer una conexión permanente a Internet. La fiabilidad del sensor se ha establecido mediante la comparación con un equipo de referencia (LVS3 de Derenda) según el método estándar EN12341:2014. La fiabilidad ha sido diseñada desde el punto de vista estadístico y sin considerar las condiciones ambientales. La metodología estadística utilizada ha sido un modelo lineal ordinario, un modelo lineal generalizado, un suavizado de trazado de dispersión estimado localmente y modelos aditivos generalizados para comparar y contrastar los resultados. Los resultados obtenidos, apuntan que el sensor HM-3301 está altamente correlacionado con la medida de referencia (con correlación superior al 70%), especialmente para PM2.5, que obtiene un valor de precisión muy alto. Además, existe una relación positiva entre las dos mediciones, las que pueden ser ajustadas adecuadamente a través del modelo de suavizado de diagrama de dispersión estimado localmente.},
keywords = {Air quality sensors, Internet of things},
pubstate = {published},
tppubtype = {inproceedings}
}
El conocimiento en tiempo real de la calidad del aire permite alertar a la población frente a los episodios de alta concentración de una forma rápida y directa. Los recientes avances en el campo de la sensorización, y las tecnologías y ciencias de la computación, han facilitado el despliegue de sensores de bajo coste, mejorando la resolución espacial y temporal de los datos
de calidad del aire. El objetivo principal de este trabajo es realizar un estudio de fiabilidad de un sensor de bajo coste de partículas en suspensión (PM2.5 y PM10) en ambientes interiores y exteriores, con la finalidad de conocer si puede ser candidato a poder ser utilizado en Planes de Gestión de la Calidad del Aire. El sensor láser seleccionado (HM-3301), hasta el momento, no ha sido evaluado en condiciones ambientales reales, y la calidad de los datos generados no se encuentra documentada. Para posibilitar este estudio, el sensor HM-3301 ha sido integrado en una plataforma del Internet de las Cosas, con el objetivo de establecer una conexión permanente a Internet. La fiabilidad del sensor se ha establecido mediante la comparación con un equipo de referencia (LVS3 de Derenda) según el método estándar EN12341:2014. La fiabilidad ha sido diseñada desde el punto de vista estadístico y sin considerar las condiciones ambientales. La metodología estadística utilizada ha sido un modelo lineal ordinario, un modelo lineal generalizado, un suavizado de trazado de dispersión estimado localmente y modelos aditivos generalizados para comparar y contrastar los resultados. Los resultados obtenidos, apuntan que el sensor HM-3301 está altamente correlacionado con la medida de referencia (con correlación superior al 70%), especialmente para PM2.5, que obtiene un valor de precisión muy alto. Además, existe una relación positiva entre las dos mediciones, las que pueden ser ajustadas adecuadamente a través del modelo de suavizado de diagrama de dispersión estimado localmente.
de calidad del aire. El objetivo principal de este trabajo es realizar un estudio de fiabilidad de un sensor de bajo coste de partículas en suspensión (PM2.5 y PM10) en ambientes interiores y exteriores, con la finalidad de conocer si puede ser candidato a poder ser utilizado en Planes de Gestión de la Calidad del Aire. El sensor láser seleccionado (HM-3301), hasta el momento, no ha sido evaluado en condiciones ambientales reales, y la calidad de los datos generados no se encuentra documentada. Para posibilitar este estudio, el sensor HM-3301 ha sido integrado en una plataforma del Internet de las Cosas, con el objetivo de establecer una conexión permanente a Internet. La fiabilidad del sensor se ha establecido mediante la comparación con un equipo de referencia (LVS3 de Derenda) según el método estándar EN12341:2014. La fiabilidad ha sido diseñada desde el punto de vista estadístico y sin considerar las condiciones ambientales. La metodología estadística utilizada ha sido un modelo lineal ordinario, un modelo lineal generalizado, un suavizado de trazado de dispersión estimado localmente y modelos aditivos generalizados para comparar y contrastar los resultados. Los resultados obtenidos, apuntan que el sensor HM-3301 está altamente correlacionado con la medida de referencia (con correlación superior al 70%), especialmente para PM2.5, que obtiene un valor de precisión muy alto. Además, existe una relación positiva entre las dos mediciones, las que pueden ser ajustadas adecuadamente a través del modelo de suavizado de diagrama de dispersión estimado localmente.
2020
Iskandaryan, Ditsuhi; Ramos-Romero, Francisco; Trilles-Oliver, Sergio
Air quality prediction in smart cities using machine learning technologies based on sensor data: A Review Journal Article
In: Applied sciences, vol. 10, no. 7, pp. 2401, 2020.
Abstract | Links | BibTeX | Tags: Air quality sensors, machine learning, Sensors, Smart Cities
@article{Iskandaryan2020,
title = {Air quality prediction in smart cities using machine learning technologies based on sensor data: A Review},
author = {Ditsuhi Iskandaryan and Francisco Ramos-Romero and Sergio Trilles-Oliver},
doi = {https://doi.org/10.3390/app10072401 },
year = {2020},
date = {2020-04-15},
journal = {Applied sciences},
volume = {10},
number = {7},
pages = {2401},
abstract = {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},
keywords = {Air quality sensors, machine learning, Sensors, Smart Cities},
pubstate = {published},
tppubtype = {article}
}
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
2019
Trilles-Oliver, Sergio; Herrero, J. Velayos; Vieco, J. L. San José; Real, J. C. Gamazo
Aumentando la interoperabilidad de una red de monitorización de calidad del aire mediante el uso de estándares web IoT. Proceedings Article
In: JIDEE 2019. Cáceres, 23-25 Octubre 2019, 2019.
Abstract | Links | BibTeX | Tags: Air quality sensors, Internet of things, interoperability, OGC, Sensor networks, Sensors, Standards
@inproceedings{Trilles-Oliver2019b,
title = {Aumentando la interoperabilidad de una red de monitorización de calidad del aire mediante el uso de estándares web IoT.},
author = {Sergio Trilles-Oliver and J. Velayos Herrero and J.L. San José Vieco and J.C. Gamazo Real },
url = {https://www.idee.es/resources/presentaciones/JIIDE19/67-JIIDE2019_strilles.pdf},
year = {2019},
date = {2019-10-23},
booktitle = { JIDEE 2019. Cáceres, 23-25 Octubre 2019},
abstract = {En la actualidad, millones de dispositivos de Internet of Things (IoT) están presentes en nuestra vida diaria. Dichos dispositivos, con permanente comunicación a Internet, necesitan de normas o estándares para poder establecer conexión, tanto a nivel de conectividad como de transferencia de datos. Debido a la existencia de una gran cantidad de protocolos, se está generando un verdadero problema de interoperabilidad, lo cual dificulta la conexión entre dispositivos, o redes de éstos, y su interacción de forma remota. La necesidad de establecer un protocolo estándar que sea capaz de cubrir todas las
necesidades que requieren estos dispositivos es uno de los retos más relevantes en las ciencias de la computación. En este trabajo se pretende aplicar estándares procedentes de las ciencias geoespaciales a
dispositivos IoT, con el objetivo de dotar de interoperabilidad a una red de monitorización de calidad del aire desplegada en la ciudad de Madrid. Para ello, se define una metodología para la integración de dicha red de monitorización utilizando el estándar OGC SensorThings API y su aplicabilidad a otras redes con este tipo de dispositivos IoT. Como ejemplo de uso de dicho estándar y de la interoperabilidad de la red, se ha desarrollado un cliente web para visualizar los datos producidos por la red de calidad del aire y garantizar su compatibilidad con otras redes desarrolladas sobre el estándar OGC SensorThings API.},
keywords = {Air quality sensors, Internet of things, interoperability, OGC, Sensor networks, Sensors, Standards},
pubstate = {published},
tppubtype = {inproceedings}
}
En la actualidad, millones de dispositivos de Internet of Things (IoT) están presentes en nuestra vida diaria. Dichos dispositivos, con permanente comunicación a Internet, necesitan de normas o estándares para poder establecer conexión, tanto a nivel de conectividad como de transferencia de datos. Debido a la existencia de una gran cantidad de protocolos, se está generando un verdadero problema de interoperabilidad, lo cual dificulta la conexión entre dispositivos, o redes de éstos, y su interacción de forma remota. La necesidad de establecer un protocolo estándar que sea capaz de cubrir todas las
necesidades que requieren estos dispositivos es uno de los retos más relevantes en las ciencias de la computación. En este trabajo se pretende aplicar estándares procedentes de las ciencias geoespaciales a
dispositivos IoT, con el objetivo de dotar de interoperabilidad a una red de monitorización de calidad del aire desplegada en la ciudad de Madrid. Para ello, se define una metodología para la integración de dicha red de monitorización utilizando el estándar OGC SensorThings API y su aplicabilidad a otras redes con este tipo de dispositivos IoT. Como ejemplo de uso de dicho estándar y de la interoperabilidad de la red, se ha desarrollado un cliente web para visualizar los datos producidos por la red de calidad del aire y garantizar su compatibilidad con otras redes desarrolladas sobre el estándar OGC SensorThings API.
necesidades que requieren estos dispositivos es uno de los retos más relevantes en las ciencias de la computación. En este trabajo se pretende aplicar estándares procedentes de las ciencias geoespaciales a
dispositivos IoT, con el objetivo de dotar de interoperabilidad a una red de monitorización de calidad del aire desplegada en la ciudad de Madrid. Para ello, se define una metodología para la integración de dicha red de monitorización utilizando el estándar OGC SensorThings API y su aplicabilidad a otras redes con este tipo de dispositivos IoT. Como ejemplo de uso de dicho estándar y de la interoperabilidad de la red, se ha desarrollado un cliente web para visualizar los datos producidos por la red de calidad del aire y garantizar su compatibilidad con otras redes desarrolladas sobre el estándar OGC SensorThings API.
Vicente, A. B.; Juan-Verdoy, Pablo; Meseguer, Sergio; Serra, Laura; Trilles-Oliver, Sergio
Air Quality Trend of PM10. Statistical Models for Assessing the Air Quality Impact of Environmental Policies Journal Article
In: Sustainability , vol. 11, no. 20, pp. 5857, 2019.
Links | BibTeX | Tags: Air quality sensors, Statistics
@article{Vicente2019,
title = {Air Quality Trend of PM10. Statistical Models for Assessing the Air Quality Impact of Environmental Policies},
author = {A.B. Vicente and Pablo Juan-Verdoy and Sergio Meseguer and Laura Serra and Sergio Trilles-Oliver},
doi = {https://doi.org/10.3390/su11205857 },
year = {2019},
date = {2019-01-01},
journal = {Sustainability },
volume = {11},
number = {20},
pages = {5857},
keywords = {Air quality sensors, Statistics},
pubstate = {published},
tppubtype = {article}
}
Trilles-Oliver, Sergio; Vicente, A. B.; Juan-Verdoy, Pablo; Ramos-Romero, Francisco; Meseguer, Sergio; Serra, Laura
Reliability Validation of a Low-Cost Particulate Matter IoT Sensor in Indoor and Outdoor Environments Using a Reference Sampler Journal Article
In: Sustainability , vol. 11, pp. 7220, 2019.
Abstract | BibTeX | Tags: Air quality sensors, Internet of things, Sensors
@article{Triller-Oliver2019,
title = {Reliability Validation of a Low-Cost Particulate Matter IoT Sensor in Indoor and Outdoor Environments Using a Reference Sampler},
author = {Sergio Trilles-Oliver and A.B. Vicente and Pablo Juan-Verdoy and Francisco Ramos-Romero and Sergio Meseguer and Laura Serra},
year = {2019},
date = {2019-00-01},
journal = {Sustainability },
volume = {11},
pages = {7220},
abstract = {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 (R2 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 ppropriately fitted through the Locally Estimated Scatterplot Smoothing model.},
keywords = {Air quality sensors, Internet of things, Sensors},
pubstate = {published},
tppubtype = {article}
}
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 (R2 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 ppropriately fitted through the Locally Estimated Scatterplot Smoothing model.
2017
Martins, Jana Lodi
Measuring air quality with low-cost sensors in citizen science applications Masters Thesis
INIT, Castellón, 2017.
BibTeX | Tags: Air quality sensors, Citizen Science, Mastergeotech
@mastersthesis{Martins2017,
title = {Measuring air quality with low-cost sensors in citizen science applications},
author = {Jana Lodi Martins},
editor = {Thomas Bartoschek and Roberto Henriques and Sven Casteleyn},
year = {2017},
date = {2017-03-03},
address = {Castellón},
school = {INIT},
keywords = {Air quality sensors, Citizen Science, Mastergeotech},
pubstate = {published},
tppubtype = {mastersthesis}
}
2014
Trilles-Oliver, Sergio; Belmonte-Fernández, Óscar; Díaz-Sánchez, Laura; Huerta-Guijarro, Joaquín
Agile access to sensor network Proceedings Article
In: Huerta-Guijarro, Joaquín; Schade, Sven; Granell-Canut, Carlos (Ed.): Connecting a Digital Europe through Location and Place. Selected best short papers and posters of the AGILE 2014 Conference, 03-06 June 2014, Castellón, Spain, AGILE Digital Editions, 2014, ISBN: 978-90-816960-4-3.
Abstract | Links | BibTeX | Tags: Air quality sensors, heterogeneous sensor sources, meteorological sensors, restful services, sensor observation services
@inproceedings{TrillesOliver2014a,
title = {Agile access to sensor network},
author = {Sergio Trilles-Oliver and Óscar Belmonte-Fernández and Laura Díaz-Sánchez and Joaquín Huerta-Guijarro},
editor = {Joaquín Huerta-Guijarro and Sven Schade and Carlos Granell-Canut},
url = {http://hdl.handle.net/10234/99492},
isbn = {978-90-816960-4-3},
year = {2014},
date = {2014-01-01},
booktitle = {Connecting a Digital Europe through Location and Place. Selected best short papers and posters of the AGILE 2014 Conference, 03-06 June 2014, Castellón, Spain},
publisher = {AGILE Digital Editions},
abstract = {The work in this paper aims at increasing the interoperability and improving accessibility of data provided by sensor networks. This way, this data can be employed by different devices and with diverse context requirements, such as specific location and time. To address this problem Geographic Information System (GIS) services, such as the Sensor Observation Service (SOS), in conjunction with Representational State Transfer (RESTFul) architecture are used. A standard-based solution that increases interoperability is presented. It also allows for a better integration of data already published in different semi-structured formats in order to be used by various platforms (web or mobile). Furthermore, this system adds value to original sensor data in order to assist in the decision making process.},
keywords = {Air quality sensors, heterogeneous sensor sources, meteorological sensors, restful services, sensor observation services},
pubstate = {published},
tppubtype = {inproceedings}
}
The work in this paper aims at increasing the interoperability and improving accessibility of data provided by sensor networks. This way, this data can be employed by different devices and with diverse context requirements, such as specific location and time. To address this problem Geographic Information System (GIS) services, such as the Sensor Observation Service (SOS), in conjunction with Representational State Transfer (RESTFul) architecture are used. A standard-based solution that increases interoperability is presented. It also allows for a better integration of data already published in different semi-structured formats in order to be used by various platforms (web or mobile). Furthermore, this system adds value to original sensor data in order to assist in the decision making process.
Trilles-Oliver, Sergio; Belmonte-Fernández, Óscar; Huerta-Guijarro, Joaquín
Mobile Access to Sensor Network: A Use Case on Wildfire Monitoring Proceedings Article
In: Omatu, S.; Bersini, H.; Corchado, JM; Rodriguez, S.; Pawlewski, P.; Bucciarelli, E. (Ed.): DCAI 2014: 11th International Symposium on Distributed Computing and Artificial Intelligence, Salamanca, Spain, JUN 04-06, 2014, pp. 287-294, SPRINGER-VERLAG BERLIN, HEIDELBERGER PLATZ 3, D-14197 BERLIN, GERMANY, 2014, ISSN: 2194-5357.
Abstract | Links | BibTeX | Tags: Air quality sensors, CITYBENCH, forest fire, meteorological sensors, Sensor networks, Sensors
@inproceedings{ISI:000342905800034,
title = {Mobile Access to Sensor Network: A Use Case on Wildfire Monitoring},
author = {Sergio Trilles-Oliver and Óscar Belmonte-Fernández and Joaquín Huerta-Guijarro},
editor = {S. Omatu and H. Bersini and JM Corchado and S. Rodriguez and P. Pawlewski and E. Bucciarelli},
url = {http://hdl.handle.net/10234/160364},
doi = {10.1007/978-3-319-07593-8_34},
issn = {2194-5357},
year = {2014},
date = {2014-01-01},
booktitle = {DCAI 2014: 11th International Symposium on Distributed Computing and Artificial Intelligence, Salamanca, Spain, JUN 04-06, 2014},
volume = {290},
pages = {287-294},
publisher = {SPRINGER-VERLAG BERLIN},
address = {HEIDELBERGER PLATZ 3, D-14197 BERLIN, GERMANY},
series = {Advances in Intelligent Systems and Computing},
abstract = {These networks provide large volumes of data in many different formats, resolution and scales. The data are of different types and character: from meteorological conditions to air quality and the concentrations of pollutants due to human activity, such as transportation or other industry-related actions. The work in this paper aims at increasing the interoperability and improving accessibility of data provided by sensor networks. To address this problem Geographic Information System (GIS) services, such as the Sensor Observation Service (SOS), in conjunction with Representational State Transfer (RESTFul) architecture are used. A standard-based solution that increases interoperability is presented. It also allows for a better integration of data already published in different semi-structured formats in order to be used by various platforms (web or mobile). Finally, we apply this system in a use case as wildfire monitoring, so it offers determine the state of a wildfire.},
keywords = {Air quality sensors, CITYBENCH, forest fire, meteorological sensors, Sensor networks, Sensors},
pubstate = {published},
tppubtype = {inproceedings}
}
These networks provide large volumes of data in many different formats, resolution and scales. The data are of different types and character: from meteorological conditions to air quality and the concentrations of pollutants due to human activity, such as transportation or other industry-related actions. The work in this paper aims at increasing the interoperability and improving accessibility of data provided by sensor networks. To address this problem Geographic Information System (GIS) services, such as the Sensor Observation Service (SOS), in conjunction with Representational State Transfer (RESTFul) architecture are used. A standard-based solution that increases interoperability is presented. It also allows for a better integration of data already published in different semi-structured formats in order to be used by various platforms (web or mobile). Finally, we apply this system in a use case as wildfire monitoring, so it offers determine the state of a wildfire.
Trilles-Oliver, Sergio; Belmonte-Fernández, Óscar; Díaz-Sánchez, Laura; Huerta-Guijarro, Joaquín
Mobile Access to Sensor Networks by Using GIS Standards and RESTful Services Journal Article
In: IEEE Sensors Journal, vol. 14, no. 12, pp. 4143–4153, 2014, ISSN: 1530-437X, (IF: 1.762, Q2).
Abstract | Links | BibTeX | Tags: Air quality sensors, Geographic Information Systems (GIS), interoperability, meteorological sensors, RESTFul, sensor observation services, Standards
@article{TrillesOliver2014,
title = {Mobile Access to Sensor Networks by Using GIS Standards and RESTful Services},
author = { Sergio Trilles-Oliver and Óscar Belmonte-Fernández and Laura Díaz-Sánchez and Joaquín Huerta-Guijarro},
url = {http://hdl.handle.net/10234/145376},
doi = {10.1109/JSEN.2014.2339931},
issn = {1530-437X},
year = {2014},
date = {2014-01-01},
journal = {IEEE Sensors Journal},
volume = {14},
number = {12},
pages = {4143--4153},
abstract = {There is an increasing deployment of sensor networks that measure the physical state of the environment. These networks provide large volumes of data in many different formats, resolutions, and scales. There are different types and character of data: from meteorological conditions to air quality and the concentrations of pollutants due to human activity, such as transportation or other industry-related actions. Current sensor networks publish this data in different formats. This implies not offering standard access to different data sources. These varieties of formats lead to an interoperability problem. Also, access to these sources is not fast and agile; it prevents access through mobile devices. The work in this paper aims at increasing the interoperability and improving accessibility of data provided by sensor networks. In this way, these data can be employed by different devices and with diverse context requirements, such as specific location and time. To address this problem, geographic information system services, such as the sensor observation service, in conjunction with representational state transfer architecture are used. A standard-based solution that increases interoperability is presented. It also allows a better integration of data that has already been published in different semistructured formats in order to be used by various platforms (web or mobile). Furthermore, this system adds value to original sensor data in order to assist in the decision making process. Finally, to illustrate how to use these services, a mobile application that shows the hot-spots following air quality index has been developed},
note = {IF: 1.762, Q2},
keywords = {Air quality sensors, Geographic Information Systems (GIS), interoperability, meteorological sensors, RESTFul, sensor observation services, Standards},
pubstate = {published},
tppubtype = {article}
}
There is an increasing deployment of sensor networks that measure the physical state of the environment. These networks provide large volumes of data in many different formats, resolutions, and scales. There are different types and character of data: from meteorological conditions to air quality and the concentrations of pollutants due to human activity, such as transportation or other industry-related actions. Current sensor networks publish this data in different formats. This implies not offering standard access to different data sources. These varieties of formats lead to an interoperability problem. Also, access to these sources is not fast and agile; it prevents access through mobile devices. The work in this paper aims at increasing the interoperability and improving accessibility of data provided by sensor networks. In this way, these data can be employed by different devices and with diverse context requirements, such as specific location and time. To address this problem, geographic information system services, such as the sensor observation service, in conjunction with representational state transfer architecture are used. A standard-based solution that increases interoperability is presented. It also allows a better integration of data that has already been published in different semistructured formats in order to be used by various platforms (web or mobile). Furthermore, this system adds value to original sensor data in order to assist in the decision making process. Finally, to illustrate how to use these services, a mobile application that shows the hot-spots following air quality index has been developed
2013
Trilles-Oliver, Sergio; Díaz-Sánchez, Laura; Huerta-Guijarro, Joaquín
Acceso ágil a redes de sensores: un estudio de caso de monitorización de datos de calidad del aire y meteorológicos Proceedings Article
In: JIDEE 2013: IV Jornadas ibéricas de infraestructuras de datos espaciales. Toledo, Noviembre 2013, Toledo, 2013.
Abstract | Links | BibTeX | Tags: Air quality sensors, CITYBENCH, Internet of things, Internet of things, meteorological sensors, Sensors
@inproceedings{TrillesOliver2013a,
title = {Acceso ágil a redes de sensores: un estudio de caso de monitorización de datos de calidad del aire y meteorológicos},
author = {Sergio Trilles-Oliver and Laura Díaz-Sánchez and Joaquín Huerta-Guijarro },
url = {http://hdl.handle.net/10234/160211},
year = {2013},
date = {2013-01-01},
booktitle = {JIDEE 2013: IV Jornadas ibéricas de infraestructuras de datos espaciales. Toledo, Noviembre 2013},
address = {Toledo},
abstract = {En el presente trabajo se pretende incrementar la interoperabilidad y accesibilidad de estos datos para que los usuarios puedan utilizarlos en diferentes escenarios y con variedad de necesidades dependiendo del lugar y tiempo específico. El objetivo deriva en la publicación de estos tipos de datos ambientales y facilitando el acceso a ellos, mediante servicios que proporcionan una entrada estructurada para el consumo en dispositivos ligeros, como los teléfonos móviles},
keywords = {Air quality sensors, CITYBENCH, Internet of things, Internet of things, meteorological sensors, Sensors},
pubstate = {published},
tppubtype = {inproceedings}
}
En el presente trabajo se pretende incrementar la interoperabilidad y accesibilidad de estos datos para que los usuarios puedan utilizarlos en diferentes escenarios y con variedad de necesidades dependiendo del lugar y tiempo específico. El objetivo deriva en la publicación de estos tipos de datos ambientales y facilitando el acceso a ellos, mediante servicios que proporcionan una entrada estructurada para el consumo en dispositivos ligeros, como los teléfonos móviles
2012
Trilles-Oliver, Sergio; Díaz-Sánchez, Laura; Huerta-Guijarro, Joaquín
Monitorización de datos de calidad de aire Proceedings Article
In: JIDEE 2012: III Jornadas Ibéricas de las infraestructuras de datos espaciales. Madrid, Octubre 2012, 2012.
Abstract | Links | BibTeX | Tags: Air quality sensors, Sensors, Spatial Data Infrastructures (SDI)
@inproceedings{TrillesOliver2012a,
title = {Monitorización de datos de calidad de aire},
author = {Sergio Trilles-Oliver and Laura Díaz-Sánchez and Joaquín Huerta-Guijarro},
url = {http://hdl.handle.net/10234/160173},
year = {2012},
date = {2012-01-01},
booktitle = {JIDEE 2012: III Jornadas Ibéricas de las infraestructuras de datos espaciales. Madrid, Octubre 2012},
abstract = {Cada vez más somos testigos del despliegue de redes de sensores que miden el estado del entorno en el que vivimos. Estas redes aportan grandes volúmenes de información en formatos y escalas muy diversas. Encontramos ejemplos de datos de diversa naturaleza, desde condiciones climáticas, hasta concentraciones de elementos contaminantes debido a la actividad humana como el transporte, y la industria. En este trabajo describimos como la publicación de estos datos mediante servicios que proporcionen un acceso estructurado y basado en estándares permite una mejor integración de estos datos, tanto para su visualización desde diversas plataformas (web o móvil) como para su consumo mediante procesos de análisis que permitan extraer valor añadido y asistir en la toma de decisiones. Uno de los principales objetivos es incrementar la interoperabilidad de acceso a estos datos y que un usuario a través de diferentes dispositivos pueda conocer en tiempo real las condiciones de una ubicación concreta},
keywords = {Air quality sensors, Sensors, Spatial Data Infrastructures (SDI)},
pubstate = {published},
tppubtype = {inproceedings}
}
Cada vez más somos testigos del despliegue de redes de sensores que miden el estado del entorno en el que vivimos. Estas redes aportan grandes volúmenes de información en formatos y escalas muy diversas. Encontramos ejemplos de datos de diversa naturaleza, desde condiciones climáticas, hasta concentraciones de elementos contaminantes debido a la actividad humana como el transporte, y la industria. En este trabajo describimos como la publicación de estos datos mediante servicios que proporcionen un acceso estructurado y basado en estándares permite una mejor integración de estos datos, tanto para su visualización desde diversas plataformas (web o móvil) como para su consumo mediante procesos de análisis que permitan extraer valor añadido y asistir en la toma de decisiones. Uno de los principales objetivos es incrementar la interoperabilidad de acceso a estos datos y que un usuario a través de diferentes dispositivos pueda conocer en tiempo real las condiciones de una ubicación concreta