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The vast amount of information stemming from the deployment of the Internet of Things and open data portals is poised to provide significant benefits for both the private and public sectors, such as the development of value-added services or an increase in the efficiency of public services. This is further enhanced due to the potential of semantic information models such as NGSI-LD, which enable the enrichment and linkage of semantic data, strengthened by the contextual information present by definition. In this scenario, advanced data processing techniques need to be defined and developed for the processing of harmonised datasets and data streams. Our work is based on a structured approach that leverages the principles of linked-data modelling and semantics, as well as a data enrichment toolchain framework developed around NGSI-LD. Within this framework, we reveal the potential for enrichment and linkage techniques to reshape how data are exploited in smart cities, with a particular focus on citizen-centred initiatives. Moreover, we showcase the effectiveness of these data processing techniques through specific examples of entity transformations. The findings, which focus on improving data comprehension and bolstering smart city advancements, set the stage for the future exploration and refinement of the symbiosis between semantic data and smart city ecosystems. [ABSTRACT FROM AUTHOR]

Nowadays, there are plenty of data sources generating massive amounts of information that, combined with novel data analytics frameworks, are meant to support optimisation in many application domains. Nonetheless, there are still shortcomings in terms of data discoverability, accessibility and interoperability. Open Data portals have emerged as a shift towards openness and discoverability. However, they do not impose any condition to the data itself, just stipulate how datasets have to be described. Alternatively, the NGSI-LD standard pursues harmonisation in terms of data modelling and accessibility. This paper presents a solution that bridges these two domains (i.e., Open Data portals and NGSI-LD-based data) in order to keep benefiting from the structured description of datasets offered by Open Data portals, while ensuring the interoperability provided by the NGSI-LD standard. Our solution aggregates the data into coherent datasets and generate high-quality descriptions, ensuring comprehensiveness, interoperability and accessibility. The proposed solution has been validated through a real-world implementation that exposes IoT data in NGSI-LD format through the European Data Portal (EDP). Moreover, the results from the Metadata Quality Assessment that the EDP implements, show that the datasets' descriptions generated achieve excellent ranking in terms of the Findability, Accessibility, Interoperability and Reusability (FAIR) data principles. [ABSTRACT FROM AUTHOR]

Locating underground microseismic events is important for monitoring subsurface activity and understanding the planetary subsurface evolution. Due to bandwidth limitations, especially in applications involving planetarily-distributed sensor networks, networks should be designed to perform the localization algorithm in-situ, so that only the source location information needs to be sent out, not the raw data. In this paper, we propose a decentralized Gaussian beam time-reverse imaging (GB-TRI) algorithm that can be incorporated to the distributed sensors to detect and locate underground microseismic events with reduced usage of computational resources and communication bandwidth of the network. After the in-situ distributed computation, the final real-time location result is generated and delivered. We used a real-time simulation platform to test the performance of the system. We also evaluated the stability and accuracy of our proposed GB-TRI localization algorithm using extensive experiments and tests. [ABSTRACT FROM AUTHOR]

The evolution of computing devices and ubiquitous computing has led to the development of the Internet of Things (IoT). Smart Grids (SGs) stand out among the many applications of IoT and comprise several embedded intelligent technologies to improve the reliability and the safety of power grids. SGs use communication protocols for information exchange, such as the Open Smart Grid Protocol (OSGP). However, OSGP does not support the integration with devices compliant with the Constrained Application Protocol (CoAP), a communication protocol used in conventional IoT systems. In this sense, this article presents an efficient software interface that provides integration between OSGP and CoAP. The results obtained demonstrate the effectiveness of the proposed solution, which presents low communication overhead and enables the integration between IoT and SG systems. [ABSTRACT FROM AUTHOR]

Traditional physiotherapy rehabilitation systems are evolving into more advanced systems based on exoskeleton systems and Virtual Reality (VR) environments that enhance and improve rehabilitation techniques and physical exercise. In addition, due to current connected systems and paradigms such as the Internet of Things (IoT) or Ambient Intelligent (AmI) systems, it is possible to design and develop advanced, effective, and low-cost medical tools that patients may have in their homes. This article presents a low-cost exoskeleton for the elbow that is connected to a Context-Aware architecture and thanks to a VR system the patient can perform rehabilitation exercises in an interactive way. The integration of virtual reality technology in rehabilitation exercises provides an intensive, repetitive and task-oriented capacity to improve patient motivation and reduce work on medical professionals. One of the system highlights is the intelligent ability to generate new exercises, monitor the exercises performed by users in search of progress or possible problems and the dynamic modification of the exercises characteristics. The platform also allows the incorporation of commercial medical sensors capable of collecting valuable information for greater accuracy in the diagnosis and evolution of patients. A case study with real patients with promising results has been carried out. [ABSTRACT FROM AUTHOR]

Smart grid systems have become popular and necessary for the development of a sustainable power grid. These systems use different technologies to provide optimized services to the users of the network. Regarding computing, these systems optimize electrical services by processing a large amount of the data generated. However, privacy and security are essential in this kind of system. With a large amount of data generated, it is necessary to protect the privacy of users, because this data may reveal the users' personal information. Today, blockchain technology has proven to be an efficient architecture for solving privacy and security problems in different scenarios. Over the years, different blockchain platforms have emerged, attempting to solve specific problems in different areas. However, the use of different platforms fragmented the market, which was no different in the smart grid scenario. This work proposes a blockchain architecture that uses sidechains to make the system scalable and adaptable. We used three blockchains to ensure privacy, security, and trust in the system. To universalize the proposed solution, we used the Open Smart Grid Protocol and smart contracts. The results show that architecture security and privacy are guaranteed, making it feasible for implementation in real systems; although scalability issues regarding the storage of the data generated still exist. [ABSTRACT FROM AUTHOR]

Nowadays, the Internet of Things (IoT) ecosystem is experiencing a lack of interoperability across the multiple competing platforms that are available. Consequently, service providers can only access vertical data silos that imply high costs and jeopardize their solutions market potential. It is necessary to transform the current situation with competing non-interoperable IoT platforms into a common ecosystem enabling the emergence of cross-platform, cross-standard, and cross-domain IoT services and applications. This paper presents a platform that has been implemented for realizing this vision. It leverages semantic web technologies to address the two key challenges in expanding the IoT beyond product silos into web-scale open ecosystems: data interoperability and resources identification and discovery. The paper provides extensive description of the proposed solution and its implementation details. Regarding the implementation details, it is important to highlight that the platform described in this paper is currently supporting the federation of eleven IoT deployments (from heterogeneous application domains) with over 10,000 IoT devices overall which produce hundreds of thousands of observations per day. [ABSTRACT FROM AUTHOR]

The Internet of Things (IoT) is unanimously identified as one of the main technology enablers for the development of future intelligent environments. However, the current IoT landscape is suffering from large fragmentation with many platforms and vendors competing with their own solution. This fragmented scenario is now jeopardizing the uptake of the IoT, as investments are not carried out partly because of the fear of being captured in lock-in situations. To overcome these fears, interoperability solutions are being put forward in order to guarantee that the deployed IoT infrastructure, independently of its manufacturer and/or platform, can exchange information, data and knowledge in a meaningful way. This paper presents a Global IoT Services (GIoTS) use case demonstrating how semantic interoperability among five different smart city IoT deployments can be leveraged to develop a smart urban mobility service. The application that has been developed seamlessly consumes data from them for providing parking guidance and mobility suggestions at the five locations (Santander and Barcelona in Spain and Busan, Seoul and Seongnam in South Korea) where the abovementioned IoT deployments are installed. The paper is also presenting the key aspects of the system enabling the interoperability among the three underlying heterogeneous IoT platforms. [ABSTRACT FROM AUTHOR]

The Internet of Things (IoT) concept has attracted a lot of attention from the research and innovation community for a number of years already. One of the key drivers for this hype towards the IoT is its applicability to a plethora of different application domains. However, infrastructures enabling experimental assessment of IoT solutions are scarce. Being able to test and assess the behavior and the performance of any piece of technology (i.e., protocol, algorithm, application, service, etc.) under real-world circumstances is of utmost importance to increase the acceptance and reduce the time to market of these innovative developments. This paper describes the federation of eleven IoT deployments from heterogeneous application domains (e.g., smart cities, maritime, smart building, crowd-sensing, smart grid, etc.) with over 10,000 IoT devices overall which produce hundreds of thousands of observations per day. The paper summarizes the resources that are made available through a cloud-based platform. The main contributions from this paper are twofold. In the one hand, the insightful summary of the federated data resources are relevant to the experimenters that might be seeking for an experimental infrastructure to assess their innovations. On the other hand, the identification of the challenges met during the testbed integration process, as well as the mitigation strategies that have been implemented to face them, are of interest for testbed providers that can be considering to join the federation. [ABSTRACT FROM AUTHOR]