Towards Data Sharing across Decentralized and Federated IoT Data Analytics Platforms

In the past decade the Internet-of-Things concept has overwhelmingly entered all of the fields where data are produced and processed, thus, resulting in a plethora of IoT platforms, typically cloud-based, that centralize data and services management. In this scenario, the development of IoT services in domains such as smart cities, smart industry, e-health, automotive, are possible only for the owner of the IoT deployments or for ad-hoc business one-to-one collaboration agreements. The realization of "smarter" IoT services or even services that are not viable today envisions a complete data sharing with the usage of multiple data sources from multiple parties and the interconnection with other IoT services. In this context, this work studies several aspects of data sharing focusing on Internet-of-Things. We work towards the hyperconnection of IoT services to analyze data that goes beyond the boundaries of a single IoT system. This thesis presents a data analytics platform that: i) treats data analytics processes as services and decouples their management from the data analytics development; ii) decentralizes the data management and the execution of data analytics services between fog, edge and cloud; iii) federates peers of data analytics platforms managed by multiple parties allowing the design to scale into federation of federations; iv) encompasses intelligent handling of security and data usage control across the federation of decentralized platforms instances to reduce data and service management complexity. The proposed solution is experimentally evaluated in terms of performances and validated against use cases. Further, this work adopts and extends available standards and open sources, after an analysis of their capabilities, fostering an easier acceptance of the proposed framework. We also report efforts to initiate an IoT services ecosystem among 27 cities in Europe and Korea based on a novel methodology. We believe that this thesis open a viable path towards a hyperconnection of IoT data and services, minimizing the human effort to manage it, but leaving the full control of the data and service management to the users' will

A proof-of-concept for semantically interoperable federation of IoT experimentation facilities

The Internet-of-Things (IoT) is unanimously identified as one of the main pillars of future smart scenarios. The potential of IoT technologies and deployments has been already demonstrated in a number of different application areas, including transport, energy, safety and healthcare. However, despite the growing number of IoT deployments, the majority of IoT applications tend to be self-contained, thereby forming application silos. A lightweight data centric integration and combination of these silos presents several challenges that still need to be addressed. Indeed, the ability to combine and synthesize data streams and services from diverse IoT platforms and testbeds, holds the promise to increase the potentiality of smart applications in terms of size, scope and targeted business context. In this article, a proof-of-concept implementation that federates two different IoT experimentation facilities by means of semantic-based technologies will be described. The specification and design of the implemented system and information models will be described together with the practical details of the developments carried out and its integration with the existing IoT platforms supporting the aforementioned testbeds. Overall, the system described in this paper demonstrates that it is possible to open new horizons in the development of IoT applications and experiments at a global scale, that transcend the (silo) boundaries of individual deployments, based on the semantic interconnection and interoperability of diverse IoT platforms and testbeds.This work is partially funded by the European projectzFederated Interoperable Semantic IoT/cloud Testbeds and Applications (FIESTA-IoT) from the European Union’s Horizon 2020 Programme with the Grant Agreement No. CNECT-ICT-643943. The authors would also like to thank the FIESTA-IoT consortium for the fruitful discussions

Embracing the future Internet of Things

All of the objects in the real world are envisioned to be connected and/or represented, through an infrastructure layer, in the virtual world of the Internet, becoming Things with status information. Services are then using the available data from this Internet-of-Things (IoT) for various social and economical benefits which explain its extreme broad usage in very heterogeneous fields. Domain administrations of diverse areas of application developed and deployed their own IoT systems and services following disparate standards and architecture approaches that created a fragmentation of things, infrastructures and services in vertical IoT silos. Coordination and cooperation among IoT systems are the keys to build “smarter” IoT services boosting the benefits magnitude. This article analyses the technical trends of the future IoT world based on the current limitations of the IoT systems and the capability requirements. We propose a hyper-connected IoT framework in which “things” are connected to multiple interdependent services and describe how this framework enables the development of future applications. Moreover, we discuss the major limitations in today’s IoT and highlight the required capabilities in the future. We illustrate this global vision with the help of two concrete instances of the hyper-connected IoT in smart cities and autonomous driving scenarios. Finally, we analyse the trends in the number of connected “things” and point out open issues and future challenges. The proposed hyper-connected IoT framework is meant to scale the benefits of IoT from local to global

Toward understanding crowd mobility in smart cities through the Internet of Things

Understanding crowd mobility behaviors would be a key enabler for crowd management in smart cities, benefiting various sectors such as public safety, tourism and transportation. This article discusses the existing challenges and the recent advances to overcome them and allow sharing information across stakeholders of crowd management through Internet of Things (IoT) technologies. The article proposes the usage of the new federated interoperable semantic IoT platform (FIESTA-IoT), which is considered as "a system of systems". The platform can support various IoT applications for crowd management in smart cities. In particular, the article discusses two integrated IoT systems for crowd mobility: 1) Crowd Mobility Analytics System, 2) Crowd Counting and Location System (from the SmartSantander testbed). Pilot studies are conducted in Gold Coast, Australia and Santander, Spain to fulfill various requirements such as providing online and offline crowd mobility analyses with various sensors in different regions. The analyses provided by these systems are shared across applications in order to provide insights and support crowd management in smart city environments.The pilot study in Gold Coast is conducted in collaboration with NEC Australia. This work has been partially funded by the Spanish Government (MINECO) under Grant Agreement No. TEC2015-71329-C2-1-R ADVICE (Dynamic Provisioning of Connectivity in High Density 5G Wireless Scenarios) project and by the EU Horizon 2020 Programme under Grant Agreements No. 731993 AUTOPILOT (Automated Driving Progressed by Internet Of Things), 643943 FIESTAIoT (Federated Interoperable Semantic IoT Testbeds and Applications), and 643275 FESTIVAL (Federated Interoperable Smart ICT Services Development and Testing Platforms) projects and the joint project by NEC Laboratories Europe and Technische Universität Dortmund. The content of this paper does not reflect the official opinion of the Spanish Government or European Union. Responsibility for the information and views expressed therein lies entirely with the authors

Experimentation as a service over semantically interoperable Internet of Things testbeds

Infrastructures enabling experimental assessment of Internet of Things (IoT) solutions are scarce. Moreover, such infrastructures are typically bound to a specific application domain, thus, not facilitating the testing of solutions with a horizontal approach. This paper presents a platform that supports Experimentation as s Service (EaaS) over a federation of IoT testbeds. This platform brings two major advances. Firstly, it leverages semantic web technologies to enable interoperability so that testbed agnostic access to the underlying facilities is allowed. Secondly, a set of tools ease both the experimentation workflow and the federation of other IoT deployments, independently of their domain of interest. Apart from the platform specification, the paper presents how this design has been actually instantiated into a cloud-based EaaS platform that has been used for supporting a wide variety of novel experiments targeting different research and innovation challenges. In this respect, the paper summarizes some of the experiences from these experiments and the key performance metrics that this instance of the platform has exhibited during the experimentation

Enabling data spaces : existing developments and challenges

This paper focuses on the concept of data spaces, which can serve as a basis for the future data economy. In data spaces, applicable to various business domains, stakeholders will be able to share data with each other in a controlled way. First, the paper describes the real motivations and needs for enabling data spaces. Second, it highlights the major technical developments in the area of data spaces in the light of open ecosystems and standards. Lastly, it focuses on two key challenges for enabling data spaces: 1) Data interoperability, 2) Data value generation. As a concrete data spaces solution example, this paper proposes the "Green Twin" use case that can be developed as a carbon neutrality solution in the domains of mobility and smart cities

Global variations in diabetes mellitus based on fasting glucose and haemogloblin A1c

Fasting plasma glucose (FPG) and haemoglobin A1c (HbA1c) are both used to diagnose diabetes, but may identify different people as having diabetes. We used data from 117 population-based studies and quantified, in different world regions, the prevalence of diagnosed diabetes, and whether those who were previously undiagnosed and detected as having diabetes in survey screening had elevated FPG, HbA1c, or both. We developed prediction equations for estimating the probability that a person without previously diagnosed diabetes, and at a specific level of FPG, had elevated HbA1c, and vice versa. The age-standardised proportion of diabetes that was previously undiagnosed, and detected in survey screening, ranged from 30% in the high-income western region to 66% in south Asia. Among those with screen-detected diabetes with either test, the agestandardised proportion who had elevated levels of both FPG and HbA1c was 29-39% across regions; the remainder had discordant elevation of FPG or HbA1c. In most low- and middle-income regions, isolated elevated HbA1c more common than isolated elevated FPG. In these regions, the use of FPG alone may delay diabetes diagnosis and underestimate diabetes prevalence. Our prediction equations help allocate finite resources for measuring HbA1c to reduce the global gap in diabetes diagnosis and surveillance.peer-reviewe