@article{Trilles2024c,

title = {Sucre4Stem: A K-12 Educational Tool for Integrating Computational Thinking and Programming Across Multidisciplinary Disciplines},

author = {Sergio Trilles-Oliver and Aida Monfort-Muriach and Enrique Cueto-Rubio and Carmen López-Girona and Carlos Granell-Canut},

doi = {https://doi.org/10.1109/TE.2024.3422666},

issn = { 0018-9359},

year  = {2024},

date = {2024-07-29},

journal = {IEEE Transactions on Education},

abstract = {This article discusses the latest developments of the Sucre4Stem tool, as part of the Sucre initiative, which aims to promote interest in computational thinking and programming skills in K-12 students. The tool follows the Internet of Things approach and consists of two prominent components: 1) SucreCore and 2) SucreCode . SucreCore incorporates an advanced microcontroller packaged in a more compact design and enables wireless connectivity. SucreCode , the block-based visual programming tool, supports two different sets of blocks depending on the education grade, and facilitates wireless communication with SucreCore . At the educational level, Sucre4Stem fosters new group dynamics and encourages students to experiment real-world projects by promoting the “programming to learn” approach to concepts from other disciplines as opposed to the strategy widely applied in schools of “learning to program” in isolation.},

keywords = {education, Internet of things, SUCRE, sucre4kids, sucre4stem},

pubstate = {forthcoming},

tppubtype = {article}

}

@article{Trilles2024a,

title = {Anomaly detection based on Artificial Intelligence of Things: A Systematic Literature Mapping},

author = {Sergio Trilles-Oliver and Sahibzada Saadoon Hammad and Ditsuhi Iskandaryan},

doi = {10.1016/j.iot.2024.101063},

issn = {2542-6605},

year  = {2024},

date = {2024-04-01},

journal = {Internet of Things},

volume = {25},

pages = {101063},

abstract = {Advanced Machine Learning (ML) algorithms can be applied using Edge Computing (EC) to detect anomalies, which is the basis of Artificial Intelligence of Things (AIoT). EC has emerged as a solution for processing and analysing information on IoT devices. This field aims to allow the implementation of Machine/Deep Learning (DL) models on MicroController Units (MCUs). Integrating anomaly detection analysis on Internet of Things (IoT) devices produces clear benefits as it ensures the use of accurate data from the initial stage. However, this process poses a challenge due to the unique characteristics of IoT. This article presents a Systematic Literature Mapping of scientific research on the application of anomaly detection techniques in EC using MCUs. A total of 18 papers published over the period 2021–2023 were selected from a total of 162 in four databases of scientific papers. The results of this paper provide a comprehensive overview of anomaly detection using TinyML and MCUs. The main contributions of this survey are the fact that it aims to: (a) study techniques for anomaly detection in ML/DL and validation metrics used in the AIoT; (b) analyse data used in the estimation of models; (c) show how ML is applied in EC using hardware or software; (d) investigate the main microcontrollers, types of power supply, and communication technology; and (e) develop a taxonomy of ML/DL algorithms used to detect anomalies in TinyML. Finally, the benefits and challenges of this kind of TinyML analysis are described.},

keywords = {Anomaly detection, Edge computing, Internet of things, TidyML},

pubstate = {published},

tppubtype = {article}

}

@article{Zurita2024a,

title = {Machine learning-based prediction model for battery levels in IoT devices using meteorological variables},

author = {Juan Emilio Zurita Macias and Sergio Trilles-Oliver},

doi = {10.1016/j.iot.2024.101109},

issn = {2542-6605},

year  = {2024},

date = {2024-04-01},

journal = {Internet of Things},

volume = {25},

pages = {101109},

abstract = {Efficient energy management is vital for the sustainability of IoT devices employing solar harvesting systems, particularly to circumvent battery depletion during periods of diminished solar incidence. Embracing the structured methodology of CRISP-DM, this study introduces machine learning (ML) models that utilise meteorological data to predict battery charge levels in solar-powered IoT devices. These models enable proactive adjustments to the devices’ data sampling frequencies, ensuring effective energy utilisation. The proposed ML models were evaluated using authentic battery charge data and weather forecast records. The empirical results of this study corroborate the predictive prowess of the models, with an average accuracy reaching as high as 94.09% in specific test cases. This substantiates the potential of the developed methodology to significantly enhance the energy autonomy of IoT devices through predictive analytics.},

keywords = {battery level prediction, Internet of things, machine learning},

pubstate = {published},

tppubtype = {article}

}

@article{Chukhno2023c,

title = {Approaching 6G Use Case Requirements with Multicasting},

author = {Nadezhda Chukhno and Olga Chukhno and Sara Pizzi and Antonella Molinaro and Antonio Iera and Giuseppe Araniti},

doi = {10.1109/MCOM.001.2200659},

issn = {1558-1896},

year  = {2023},

date = {2023-05-01},

journal = {IEEE Communications Magazine},

volume = {61},

number = {5},

pages = {144-150},

abstract = {The shift towards 6G networks is expected to be accompanied by an increased capability to support group-oriented services, such as extended reality and holographic communications, in many different contexts, from high-precision manufacturing to healthcare and remote control. This range of applications will rely heavily on multicast and mixed multicast-broadcast delivery modes. This article focuses on the technological perspectives of 6G multicasting, highlighting requirements, challenges, and enabling solutions. We then run a simulation campaign to test practical solutions and draw conclusive remarks for forthcoming 6G multicast systems.},

keywords = {6G, A-wear, Internet of things, Wi-Fi},

pubstate = {published},

tppubtype = {article}

}

@article{Chukhno2022c,

title = {Placement of Social Digital Twins at the Edge for Beyond 5G IoT Networks},

author = {Olga Chukhno and Nadezhda Chukhno and Giuseppe Araniti and Claudia Campolo and Antonio Iera and Antonella Molinaro},

doi = {0.1109/JIOT.2022.3190737},

issn = {2327-4662},

year  = {2022},

date = {2022-12-01},

journal = {IEEE Internet of Things Journal },

volume = {9},

number = {23},

pages = {23927 - 23940},

abstract = {As the fifth-generation (5G) and beyond (5G+/6G) networks move forward, and a wide variety of new advanced Internet of Things (IoT) applications are offered, effective methodologies for discovering time-relevant information, services, and resources are being demanded. To this end, computing-, storage-, and battery-constrained IoT devices are progressively augmented via digital twins (DTs) hosted on edge servers. According to recent research results, a further feature these devices may acquire is social behavior; this latter offers enormous possibilities for fast and trustworthy service discovery, although it requires new orchestration policies of DTs at the network edge. This work addresses the dynamic placement of DTs with social capabilities [social digital twins (SDTs)] at the edge, by providing an optimal solution under IoT device mobility and by accounting for edge network deployment specifics, types of devices, and their social peculiarities. The optimization problem is formulated as a particular case of the quadratic assignment problem (QAP); also, an approximation algorithm is proposed and two relaxation techniques are applied to reduce computation complexity. Results show that the proposed placement policy ensures a latency among SDTs up to 1.4 times lower than the one obtainable with a traditional proximity-based only placement while still guaranteeing appropriate proximity between physical devices and their virtual counterparts. Moreover, the proposed heuristic closely approximates the optimal solution while guaranteeing the lowest computational time.},

keywords = {A-wear, digital twin, Internet of things},

pubstate = {published},

tppubtype = {article}

}

@article{Weerapanpisit2022a,

title = {A Decentralized Location-Based Reputation Management System in the IoT Using Blockchain},

author = {Ponlawat Weerapanpisit and Sergio Trilles-Oliver and Joaquín Huerta-Guijarro and Marco Painho},

doi = {https://doi.org/10.1109/JIOT.2022.3147478},

issn = {2327-4662},

year  = {2022},

date = {2022-08-15},

journal = {IEEE Internet of Things Journal},

volume = {9},

number = {16},

pages = {15100 - 15115},

abstract = {The Internet of Things (IoT) allows an object to connect to the Internet and observe or interact with a physical phenomenon. The communication technologies allow one IoT device to discover and communicate with another in order to exchange services, in a similar way to what humans do in their social networks. Knowing the reputation of another device is important to consider whether it is trustworthy before establishing a new connection and thus, avoid possible unexpected behaviors as a consequence. Trustworthiness, as a property of a device, can be affected by different factors including its geographical location. Hence, this research work proposes an architecture to manage reputation values of end devices in an IoT system based on the area where they are located. A cloud–fog–edge architecture is proposed, where the fog layer uses the Blockchain technology to keep the reputation management system consistent and fault tolerant across different nodes. The location-based part of the system was done by storing geographical areas in smart contracts (coined as geospatial smart contracts) and making the reputation values subject to different regions depending on the geographical location of the device. To reduce the complexity of the spatial computation, the geographical data are geocoded by either one of two different spatial indexing techniques. This work also introduced two different structures for storing geocoded areas based on either cell list or tree structure. Finally, three experiments to test the proposed architecture are presented, to deploy the architecture in IoT devices, and to compare the two geocoding techniques in smart contracts.},

keywords = {blockchain, Internet of things, location-based services, spatial indexing},

pubstate = {published},

tppubtype = {article}

}

@article{Gonzalez-Perez2022b,

title = {Hypnos: A Hardware and Software Toolkit for Energy-Aware Sensing in Low-Cost IoT Nodes},

author = {Alberto González-Pérez and Sven Casteleyn},

doi = {https://doi.org/10.1109/JIOT.2022.3145338},

isbn = {2327-4662},

year  = {2022},

date = {2022-01-21},

journal = {IEEE Internet of Things Journal},

volume = {9},

number = {15},

pages = {13524-13541},

abstract = {Through the Internet of Things (IoT), autonomous sensing devices can be deployed to regularly capture environmental and other sensor measurements for a variety of usage scenarios. However, for the market segment of stand-alone, self-sustaining small IoT nodes, long-term deployment remains problematic due to the energy-constrained nature of these devices, requiring frequent maintenance. This article introduces Hypnos, an open hardware and software toolkit that aims to balance energy intake and usage through the adaptive sensing rate for low-cost Internet-connected IoT nodes. We describe the hardware architecture of the IoT node, an open hardware board based on the Arduino Uno form-factor packing the energy measurement circuitry, and the associated opensource software library, which interfaces with the sensing node’s microcontroller and provides access to the low-level energy measurements. Hypnos comes equipped with a built-in, configurable, modified sigmoid function to regulate duty-cycle frequency based on energy intake and usage, yet developers may also plug in their custom duty/sleep balancing function. An experiment was set up, whereby two identical boards ran for two months: one with the Hypnos software framework and built-in energy-balancing function to regulate sensing rate and the other with fixed sensing rate. The experiment showed that Hypnos is able to successfully balance energy usage and sensing frequency within configurable energy ranges. Hereby, it increases the reliability by avoiding the complete shutdown, while, at the same time, optimizing performance in terms of the average amount of sensor measurements.},

keywords = {Internet of things},

pubstate = {published},

tppubtype = {article}

}

@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}

}

@article{Marsh-Huhn2020,

title = {A comparative study in the standardisation of IoT devices using geospatial web standards},

author = {Daniel Marsh-Huhn and Sergio Trilles-Oliver and Alberto González-Pérez and Francisco Ramos-Romero},

doi = {https://doi.org/10.1109/JSEN.2020.3031315},

year  = {2020},

date = {2020-12-01},

journal = {IEEE Sensors},

volume = {21},

number = {4},

pages = {5512-5528},

abstract = {Although billions of devices are embedded in the World Wide Web through the Internet of Things, there is still a lack of a common, interoperable way to connect them and make them interact seamlessly. IoT has also found its way into the spatial web. Environmental monitoring and sensing platforms connected over the web by wireless sensor networks are now a common way to monitor natural phenomena. This study compares two open Web Standards ( OGC’s Sensor Observation Service and SensorThings API ) from the geospatial point of view. An IoT platform, called SEnviro , is used to integrate and evaluate implementations for each standard and contrast their qualitative and quantitative traits. The results of the study show that the SensorThings API proves to be the adequate Web Standard for IoT applications in terms of interoperability. It outperforms the contesting Web Standard in terms of flexibility and scalability, which strongly impacts on developer and user experience.	},

keywords = {API, Internet of things, Mastergeotech, Sensors},

pubstate = {published},

tppubtype = {article}

}

@article{Chukhno2020a,

title = {Optimal Placement of Social Digital Twins in Edge IoT Networks},

author = {Olga Chukhno and Nadezhda Chukhno and Giuseppe Araniti and Claudia Campolo and Antonio Iera and Antonella Molinaro},

doi = {https://doi.org/10.3390/s20216181},

issn = {1424-8220},

year  = {2020},

date = {2020-10-30},

journal = {Sensors},

volume = {20},

number = {21},

pages = {6181},

abstract = {In next-generation Internet of Things (IoT) deployments, every object such as a wearable device, a smartphone, a vehicle, and even a sensor or an actuator will be provided with a digital counterpart (twin) with the aim of augmenting the physical object’s capabilities and acting on its behalf when interacting with third parties. Moreover, such objects can be able to interact and autonomously establish social relationships according to the Social Internet of Things (SIoT) paradigm. In such a context, the goal of this work is to provide an optimal solution for the social-aware placement of IoT digital twins (DTs) at the network edge, with the twofold aim of reducing the latency (i) between physical devices and corresponding DTs for efficient data exchange, and (ii) among DTs of friend devices to speed-up the service discovery and chaining procedures across the SIoT network. To this aim, we formulate the problem as a mixed-integer linear programming model taking into account limited computing resources in the edge cloud and social relationships among IoT devices.},

keywords = {A-wear, digital twin, Internet of things},

pubstate = {published},

tppubtype = {article}

}

@article{Subina2020a,

title = {Survey of Decentralized Solutions with Mobile Devices for User Location Tracking, Proximity Detection, and Contact Tracing in the COVID-19 Era},

author = {Viktoriia Shubina and Sylvia Holcer and Michael Gould and Elena Simona Lohan},

doi = {https://doi.org/10.3390/data5040087},

issn = {2306-5729},

year  = {2020},

date = {2020-09-23},

journal = {Data},

volume = {5},

number = {4},

pages = {87},

abstract = {Some of the recent developments in data science for worldwide disease control have involved research of large-scale feasibility and usefulness of digital contact tracing, user location tracking, and proximity detection on users’ mobile devices or wearables. A centralized solution relying on collecting and storing user traces and location information on a central server can provide more accurate and timely actions than a decentralized solution in combating viral outbreaks, such as COVID-19. However, centralized solutions are more prone to privacy breaches and privacy attacks by malevolent third parties than decentralized solutions, storing the information in a distributed manner among wireless networks. Thus, it is of timely relevance to identify and summarize the existing privacy-preserving solutions, focusing on decentralized methods, and analyzing them in the context of mobile device-based localization and tracking, contact tracing, and proximity detection. Wearables and other mobile Internet of Things devices are of particular interest in our study, as not only privacy, but also energy-efficiency, targets are becoming more and more critical to the end-users. This paper provides a comprehensive survey of user location-tracking, proximity-detection, and digital contact-tracing solutions in the literature from the past two decades, analyses their advantages and drawbacks concerning centralized and decentralized solutions, and presents the authors’ thoughts on future research directions in this timely research field.},

keywords = {A-wear, Internet of things, wearables},

pubstate = {published},

tppubtype = {article}

}

@article{Trilles-Oliver2020c,

title = {An IoT platform based on microservices and serverless paradigms for smart farming purposes},

author = {Sergio Trilles-Oliver and Alberto González-Pérez and Joaquín Huerta-Guijarro},

doi = {10.3390/s20082418 },

year  = {2020},

date = {2020-05-23},

journal = {Sensors},

volume = {20},

pages = {2418},

abstract = {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},

keywords = {Internet of things, precision agriculture, Sensors},

pubstate = {published},

tppubtype = {article}

}

@article{Trilles-Oliver2019,

title = {Adapting models to warn fungal diseases in vineyards using in-field Internet of Things (IoT) nodes},

author = {Sergio Trilles-Oliver and Alberto González-Pérez and Joaquín Huerta-Guijarro },

year  = {2019},

date = {2019-02-01},

journal = {Sustainability  },

volume = {11},

pages = {416},

keywords = {Internet of things, senviro},

pubstate = {published},

tppubtype = {article}

}

@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}

}

@article{Trilles-Oliver2018,

title = {A Comprehensive IoT Node Proposal Using Open Hardware. A Smart Farming Use Case to Monitor Vineyards},

author = {Sergio Trilles-Oliver and Alberto González-Pérez and Joaquín Huerta-Guijarro},

doi = {10.3390/electronics7120419},

year  = {2018},

date = {2018-03-28},

journal = {Electronics},

volume = {7},

number = {12},

pages = {419},

abstract = {The last decade has witnessed a significant reduction in prices and an increased performance of electronic components, coupled with the influence of the shift towards the generation of open resources, both in terms of knowledge (open access), programs (open-source software), and components (open hardware). This situation has produced different effects in today’s society, among which is the empowerment of citizens, called makers, who are themselves able to  generate citizen science or build assembly developments. Situated in the context described above, the current study follows a Do-It-Yourself (DIY) approach. In this way, it attempts to define a conceptual design of an Internet of Things (IoT) node, which is reproducible at both physical and behavioral levels, to build IoT nodes which can cover any scenario. To test this conceptual design, this study proposes a sensorization node to monitor meteorological phenomena. The node is called SEnviro (node) and features different improvements such as: the possibility of remote updates using Over-the-Air (OTA) updates; autonomy, using 3G connectivity, a solar panel, and applied energy strategies to prolong its

life; and replicability, because it is made up of open hardware and other elements such as 3D-printed pieces. The node is validated in the field of smart agriculture, with the aim of monitoring different meteorological phenomena, which will be used as input to disease detection models to detect possible diseases within vineyards.},

note = {IF: },

keywords = {Agriculture, crop monitoring, Internet of things, senviro},

pubstate = {published},

tppubtype = {article}

}

@article{Trilles2017,

title = {Deployment of an open sensorized platform in a smart city context },

author = {Sergio Trilles-Oliver and Andrea Calia and Óscar Belmonte and Joaquín Torres-Sospedra and Raul Montoliu and Joaquín Huerta-Guijarro and 

},

doi = {http://dx.doi.org/10.1016/j.future.2016.11.005},

issn = {0167-739X},

year  = {2017},

date = {2017-02-28},

journal = {Future Generation Computer Systems},

volume = {76},

pages = {221-233},

abstract = {The race to achieve smart cities is producing a continuous effort to adapt new developments and knowledge, for administrations and citizens. Information and Communications Technology are called on to be one of the key players to get these cities to use smart devices and sensors (Internet of Things) to know at every moment what is happening within the city, in order to make decisions that will improve the management of resources. The proliferation of these “smart things” is producing significant deployment of networks in the city context. Most of these devices are proprietary solutions, which do not offer free access to the data they provide. Therefore, this prevents the interoperability and compatibility of these solutions in the current smart city developments.

This paper presents how to embed an open sensorized platform for both hardware and software in the context of a smart city, more specifically in a university campus. For this integration, GIScience comes into play, where it offers different open standards that allow full control over “smart things” as an agile and interoperable way to achieve this. To test our system, we have deployed a network of different sensorized platforms inside the university campus, in order to monitor environmental phenomena.},

keywords = {environmental monitoring, GEOEvent, GIScience, Internet of things, Open-hardware, senviro, Smart Cities},

pubstate = {published},

tppubtype = {article}

}

@article{TrillesOliver16,

title = {A domain-independent methodology to analyze IoT data streams in real-time. A proof of concept implementation for anomaly detection from environmental data},

author = { Sergio Trilles-Oliver and Óscar Belmonte-Fernández and Sven Schade and Joaquín Huerta-Guijarro},

issn = {1753-8947},

year  = {2017},

date = {2017-01-01},

journal = {International Journal of Digital Earth},

volume = {10},

number = {1},

pages = {103-120},

abstract = {Pushed by the Internet of Things (IoT) paradigm modern sensor networks monitor a wide range of phenomena, in areas such as environmental monitoring, health care, industrial processes, and smart cities. These networks provide a continuous pulse of the almost infinite activities that are happening in the physical space and are thus, key enablers for a Digital Earth Nervous System. Nevertheless, the rapid processing of these sensor data streams still continues to challenge traditional data handling solutions and new approaches are being requested. We propose a generic answer to this challenge, which has the potential to support any form of distributed real-time analysis. This neutral methodology follows a brokering approach to work with different kinds of data sources and uses web-based standards to achieve interoperability. As a proof of concept, we implemented the methodology to detect anomalies in real-time and applied it to the area of environmental monitoring. The developed system is capable of detecting anomalies, generating notifications, and displaying the recent situation to the user.},

keywords = {environmental monitoring, Internet of things, Real time analysis, real-time sensor streams},

pubstate = {published},

tppubtype = {article}

}

@article{Granell20161,

title = {Future Internet technologies for environmental applications},

author = {Carlos Granell-Canut and Denis Havlik and Sven Schade and Zoheir Sabeur and Conor Delaney and Jasmin Pielorz and Thomas Usländer and Paolo Mazzetti and Katharina Schleidt and Mike Kobernus and Fuada Havlik and Nils Rune Bodsberg and Arne Berre and Jose Lorenzo Mon},

url = {http://www.sciencedirect.com/science/article/pii/S1364815215301298},

doi = {http://dx.doi.org/10.1016/j.envsoft.2015.12.015},

issn = {1364-8152},

year  = {2016},

date = {2016-04-08},

journal = {Environmental Modelling & Software},

volume = {78},

pages = {1 - 15},

abstract = {This paper investigates the usability of Future Internet technologies (aka “Generic Enablers of the Future Internet”) in the context of environmental applications. The paper incorporates the best aspects of the state-of-the-art in environmental informatics with geospatial solutions and scalable processing capabilities of Internet-based tools. It specifically targets the promotion of the “Environmental Observation Web” as an observation-centric paradigm for building the next generation of environmental applications. In the Environmental Observation Web, the great majority of data are considered as observations. These can be generated from sensors (hardware), numerical simulations (models), as well as by humans (human sensors). Independently from the observation provenance and application scope, data can be represented and processed in a standardised way in order to understand environmental processes and their interdependencies. The development of cross-domain applications is then leveraged by technologies such as Cloud Computing, Internet of Things, Big Data Processing and Analytics. For example, “the cloud” can satisfy the peak-performance needs of applications which may occasionally use large amounts of processing power at a fraction of the price of a dedicated server farm. The paper also addresses the need for Specific Enablers that connect mainstream Future Internet capabilities with sensor and geospatial technologies. Main categories of such Specific Enablers are described with an overall architectural approach for developing environmental applications and exemplar use cases.},

note = {IF: 4.404 - 6/105 (Q1) Computer Science, Interdisciplinary Applications

IF: 4.404 - 8/49 (Q1) Engineering, Environmental

IF: 4.404 - 25/229 (Q1) Environmental Sciences

},

keywords = {Big data, Cloud computing, Crowdtasking, Environmental informatics, Environmental observation web, Environmental specific enablers, Future internet, Internet of things, Volunteered geographic information},

pubstate = {published},

tppubtype = {article}

}

@article{TrillesOliver2015a,

title = {SEnviro: A sensorized platform proposal using open hardware and open standards},

author = {Sergio Trilles-Oliver and Alejandro Luján and Óscar Belmonte-Fernández and Raúl Montoliu-Colás and Joaquín Torres-Sospedra and Joaquín Huerta-Guijarro},

url = {http://hdl.handle.net/10234/150305},

doi = {10.3390/s150305555},

issn = {14248220},

year  = {2015},

date = {2015-01-01},

journal = {Sensors},

volume = {15},

number = {3},

pages = {5555--5582},

abstract = {The need for constant monitoring of environmental conditions has produced an increase in the development of wireless sensor networks (WSN). The drive towards smart cities has produced the need for smart sensors to be able to monitor what is happening in our cities. This, combined with the decrease in hardware component prices and the increase in the popularity of open hardware, has favored the deployment of sensor networks based on open hardware. The new trends in Internet Protocol (IP) communication between sensor nodes allow sensor access via the Internet, turning them into smart objects (Internet of Things and Web of Things). Currently, WSNs provide data in different formats. There is a lack of communication protocol standardization, which turns into interoperability issues when connecting different sensor networks or even when connecting different sensor nodes within the same network. This work presents a sensorized platform proposal that adheres to the principles of the Internet of Things and the Web of Things. Wireless sensor nodes were built using open hardware solutions, and communications rely on the HTTP/IP Internet protocols. The Open Geospatial Consortium (OGC) SensorThings API candidate standard was used as a neutral format to avoid interoperability issues. An environmental WSN developed following the proposed architecture was built as a proof of concept. Details on how to build each node and a study regarding energy concerns are presented.12pt},

note = {IF: 2.033, Q1},

keywords = {Internet of things, Interoperability, Open hardware, Sensor networks, Sensor networks, senviro, Web of things},

pubstate = {published},

tppubtype = {article}

}