IoT is More Than Just Connecting Devices: The OpenIoT Stack Explained
The way the Internet of Things (IoT) has evolved technologically in the last years and the level of expected IoT services immersion have impacted daily aspects of people's lives. A clear example where IoT has influenced big changes is in the cities. Today there are cities technologically equipped and socially organized in a way that the generation and deployment of better citizen services and solutions are more rapidly adopted (e.g. Smart Cities).
Today citizens have more sensed-enabled services and a greater awareness of them . If the operation of a city, for example, relies on sensor-based systems and their collected data services its citizens have a better reference of what is happening in the city by means of "smart city" indicators. In other words the Internet of Things is the instrument towards enabling a full sensor-enabled and IoT services life experience. IoT is already considered the scientific evolution of the internet that comes with a technology deployment wave of connected devices.
The OpenIoT Stack
The Internet of Things has evolved too fast in recent years and the term IoT usually refers, erroneously, only to device capacity and the way connected devices called "objects" or "things" interact with each other and with a gateway. However there are more than just devices and their performance in the IoT, even for devices with good computing capacity such as smartphones, the information collected surpasses the limits of their constrained environment in terms of processing capacity and storage. The support that information systems and the IoT service infrastructure (cloud) can provide for using that information are therefore part of the same Internet of Things paradigm. The elements described in the so called “OpenIoT Stack” are part of a process with relations and interactions for the IoT landscape.
The OpenIoT stack  has been designed in the context of IoT systems and cloud infrastructures. It is the methodology that defines and establishes the relations between the operations and the role that "things" can play in the whole IoT system(s), likewise it represents the functionality or services that applications are able to provide and support. Intermediate functions and methods are also defined as part of an identified middle/mediation process. The stack for service delivery models and interoperability for the Internet of Things is shown in Figure 1.
Figure 1: IoT stack for service delivery and interoperability
The main characteristics and functional layers of the IoT Stack rely on the capacities of an IoT system to allocate functions and operations accordingly across those layers. From the Physical Device Level where raw data formats are handled and collected, identified and handled seamlessly to a more organised virtualized architecture with a well-defined format-driven information system that (as much as possible) follows standards supporting applications and enabling services at a more high business level. At this business level of the IoT Stack the general interoperability process relies more on "intelligence" supported by information services, and as result of monitoring, statistical and analytical processes  rather than physical device capacity. In between there are some layers, between them; there is a Sensor Middleware Level for data transformation and adaptation. Semantic Level data management tools are provided to query information and offer intermediate access from application to data by means of linked data and at the Application Level data formal representations reduce the burden of performing common aggregation. At the Business Level also provisioning and visualizations for end users are offered as a service.
The OpenIoT Architecture
The emerging multiple IoT systems demand to have convergence platforms able to mediate between all the IoT data and solutions. OpenIoT was incepted in 2010 with the main goal of converging sensor data systems using cloud infrastructures with IoT applications in a way that ensures re-usability, repurposing and interoperability of diverse services and sensor data sets known also as streams (typically a stream is defined as a large dynamic set of information). OpenIoT focuses on the IoT Data Stream management and interoperability of sensor platforms by using cloud computing integration . OpenIoT is a blueprint implemented sensor platform of the IoT Stack.
The main features of OpenIoT address some needs in principle to: (A) ensure semantic interoperability of diverse IoT data services and sensor data streams in the cloud; (B) maintain and support about the provided solutions for relating sensor-data sets (i.e. Linked Sensor Data); (C) maintain the open source project, that provides the blueprint implementation for semantically interoperable IoT cloud applications using semantics; (D) enable the delivery of IoT applications through cloud-based platforms on a utility-based pay-as-you-go model  enabling sensing as a service; (E) facilitate the creation of information services based on the collected sensor data using the IoT middleware and cloud infrastructure provided or available.
The OpenIoT project's main outcome is the Open Source platform with the same name . OpenIoT can be seen as the main vehicle for realising the semantic interoperability in IoT. The OpenIoT platform representation is shown in Figure 2.
Figure 2: The OpenIoT platform implementing the IoT Stack
The OpenIoT platform  is available at https://github.com/OpenIotOrg/openiot/, which has already attracted several IoT researchers, developers and open source contributors including industry and standards organisations.
Experiments and M2M Trials following IoT Stack design
IoT use cases are implemented in different areas, including Smart Cities, Smart Manufacturing, Smart Agriculture (Agrifood) Sector and Assisted Living use cases. However the big challenge across all of them is to demonstrate the analytics performed on live sensor streams acquired through the IoT platform(s) and here is where the OpenIoT platform following the IoT Stack is focused.
In smart cities, for example, solutions are focused on urban crowd sensing, an example is air quality monitoring in order to monitor particular densely populated city areas, both in time and space, to understand air pollution dynamics and its impact on human health.
In manufacturing plants IoT is a real dynamic scenario where large numbers of sensors are installed in order to monitor production processes. As reference, mid-sized plants are likely to comprise many hundreds of sensors of different types and for various purposes. Sensors generate a great volume of information, while they are associated with an always-increasing rate of information.
In smart agriculture networks of wireless sensor nodes collecting information over a field of experimental crops is the best representation of how IoT technology and associated systems can be deployed for analysing growth and performance.
In the above use cases the OpenIoT framework has been tested for capturing, storing and processing IoT sensor data. Figure 3 depicts the OpenIoT Integrated Development Environment (IDE) and the core functions: Authenticate users into OpenIoT platform, Discover available sensors, Configure new sensors technology, Define IoT services based on flow diagrams to Visualize and Present analytical results and finally statistical graphs as part of an IoT-designed Monitor service. OpenIoT has been used to semantically interconnect technology and leverage diverse data into a single format by means of enabling data analytics .
Figure 3: The OpenIoT IDE (integrated development environment)
The IoT stack focuses on leveraging service delivery models and interoperability in the Internet of Things. IoT Stack was designed following the service requirements and lifecycle formulations for connected devices. The main characteristics and functional layers of the IoT Stack are described following the principles for interoperability in the framework of the OpenIoT project.
The design and specification of M2M/IoT use cases and services using the OpenIoT stack and the implemented middleware is optimal for real-time analysis and particularly for sensor data acquisition, transformation management and sharing. By the nature of the design of the IoT solutions enabling IoT data analytics for IoT systems intelligent servers can be updated and enhanced for real-time data processing.
Part of this work has been carried out in the scope of the project ICT OpenIoT Project, which is co-funded by the European Commission under seventh framework program, contract number FP7-ICT-2011-7-287305-OpenIoT and the Insight Centre for Data analytics with Grant No. 12/RC/2289 (Insight).
 Martin Serrano, Hoan Nguyen M. Quoc, Manfred Hauswirth, Wei Wang, Payam Barnaghi, Philippe Cousin "Open Services for IoT Cloud Applications in the Future Internet" procs of the 2nd IEEE WoWMoM 2013 workshop on the IoT and Smart Objects (IoT-SoS 2013),http://www2.ing.unipi.it/iot-sos2013, Spain.
 Martin Serrano, Hoan Nguyen M. Quoc, Danh Le Phuoc, Manfred Hauswirth, John Soldatos, Nikos Kefalakis, Prem Jayaraman and Arkady Zaslavsky "Defining the Stack for Service Delivery Models and Interoperability in the Internet of Things: A Practical Case With OpenIoT-VDK", IEEE Journal on Selected Areas in Communications - JSAC, 2015.
 John Soldatos; Nikos Kefalakis; Martin Serrano; Manfred Hauswirth "Design principles for utility-driven services and cloud-based computing modelling for the Internet of Things" Journal: Int. J. of Web and Grid Services, 2014 Vol.10, pp.139–167 DOI: 10.1504/IJWGS.2014.060254.
 Anh Le Tuan, Hoan N. Mau Quoc, Martin Serrano, Manfred Hauswirth, John Soldatos, Thanasis Papaioannou, Karl Aberer "Global Sensor Modeling and Constrained Application Methods Enabling Cloud-Based Open Space Smart Services" IEEE 9th Intl Conference on Ubiquitous Intelligence and Computing (IEEE UIC 2012).
 Myriam Leggieri, Martin Serrano, Manfred Hauswirth "Data Modeling for Cloud-Based Internet-of-Things Systems" IEEE International Conference on Internet of Things 2012.
 Martín Serrano, et al. "A Self-Organizing Architecture for Cloud by means of Infrastructure Performance and Event Data", 2013 IEEE Cloudcom, Bristol, UK.ISBN: 978-0-7695-5095-4, ISSN: 2330-2186
 Serrano, J. Martin. "Applying Semantics and Data Interoperability Principles for Cloud Management Systems". Book Series: Lecture Notes in Computer Science, Vol. LNCS 7092, Subseries: Innovations in Intelligent Machines-4. Colette Faucher and Lakhmi Jain (Eds.) 2013, Vol.514, 2014, pp 257-277, Springer Publishers. Print ISBN: 978-3-319-01865-2.
 Serrano, J. Martin "Applied Ontology Engineering in Cloud Services, Networks and Management Systems", Springer Publishers, March 2012. Hardcover, p.p. 222 pages, ISBN-10: 1461422353, ISBN-13: 978-1461422358.
Martin Serrano is an ICT expert with more than 12 years experience in industry and applied research, at the technical and management levels, within a wide range of Pan-European international collaborative research Projects and also with experience on large scale Integrated Platforms experimentation. Dr. Martin Serrano is a lecturer at the National University of Ireland with a worldwide-recognized activity using semantics for communications and management systems, sensor-networks and cloud computing. Dr. Serrano has co-authored more than 70 papers published in international journals and conference proceedings and is the author of an academic book and several book chapters. Dr. Serrano serves as a reviewer in major journals (e.g., IEEE Wireless Magazine, IEEE Communications Magazine, IEEE Transactions in Communications). Dr. Serrano's contributions in smart cities and the Internet of Things have been adopted and included in Santa Clara University (SCU Silicon Valley area), the California Polytechnic State University (CalPoly), Monash University in Australia and the National University of Ireland (NUI-Maynooth) academic programs. Dr. Serrano was Senior Engineer Supervisor at Panasonic-AKME at the Product Design Engineering department. He was also Research Intern at National/Panasonic in Japan. Dr. Serrano is an active member of IEEE (Computer and Communication Societies). email@example.com.
John Soldatos is with Athens Information Technology, where he is currently an Associate Professor. He has technically participated in a number of research projects, which were co-funded by the EU. He has also had an active involvement in several (more than eight) projects of the General Secretariat for Research and Technology. Dr. Soldatos has experience in several enterprise IT projects (including high-budget integrated projects), where he worked for leading Greek enterprises. Dr. Soldatos has lectured extensively in NTUA, AIT, while he has also given a host of invited lectures to other Greek and international universities. He has also conducted numerous corporate training courses (over 30 seminars) with topics relating to implementation and technical management of large scale IT projects (main topics being J2EE, Oracle, RUP/XP). Dr. Soldatos has co-authored more than 120 papers published in international journals (more than 30) and conference proceedings. Dr. Soldatos serves as a reviewer in major journals (e.g., Journal of Grid Computing, IEEE Communications Magazine, IEEE Communications Surveys), while he has also served as organizing chair, tutorial chair, and technical programme committee member in a host of related conferences. firstname.lastname@example.org.
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