@article{RamosRomero2014,
title = {A Location Aware Mobile Tool for Direct and Indirect Climate Data Sensors},
author = { Francisco Ramos-Romero and Aida Monfort-Muriach and Joaquín Huerta-Guijarro},
url = {http://hdl.handle.net/10234/125826},
doi = {10.1111/tgis.12097},
issn = {1361-1682},
year = {2014},
date = {2014-01-01},
journal = {Transactions in GIS},
volume = {18},
number = {3},
pages = {385-400},
abstract = {Access to GIS data from mobile platforms continues to be a challenge and there is a wide range of fields where it is extremely useful. In this work, we combined three key aspects: climate data sensors, mobile platforms and spatial proximity operations. We published and made use of a web 2.0 network of climate data, where content is user-collected, by means of their meteorological stations, and exposed as available information for the virtual community. Moreover, we enriched this data by giving the users the opportunity to directly inform the system with different climate measures. In general, management of this type of information from a mobile application could result in an important decision tool, as it enables us to provide climate-related data according to a context and a geographical location. Therefore, we implemented a native mobile application for iPhone and iPad platforms by using ArcGIS SDK for iOS and by integrating a series of ArcGIS webmaps, which allows us to perform geospatial queries based on the user's location, offering, at the same time, access to all the data provided by the climate data sensor network and from direct users.},
note = {IF: 1.398, Q2},
keywords = {CIUDADES-SALUDABLES, meteorological sensors, Sensors},
pubstate = {published},
tppubtype = {article}
}

@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}
}