Yann Bocchi

Semantic Web of Things: an analysis of the application semantics for the IoT moving towards the IoT convergence

The Internet of Things IoT is being applied for stovepipe solutions, since it presents a semantic description limited to a specific domain. IoT needs to be pushed towards a more open, interoperable and collaborative IoT. The first step has been the Web of Things WoT. WoT evolves the IoT with a common stack based on web services. But, even when a homogeneous access is reached through web protocols, a common understanding is not yet acquired. For this purpose, the Semantic Web of Things SWoT is proposed for the integration of the semantic web on the WoT. This work analyses the SWoT, presenting its different levels to offer an IoT convergence. Specifically, we analyse the trends for capillary networks and for cellular networks with standards such as IPSO, ZigBee, OMA, and the oneM2M initiative. This work also analyses the impact of the semantic-annotations/metadata in the performance of the resources.

A Transparent IPv6 Multi-protocol Gateway to Integrate Building Automation Systems in the Internet of Things

The future Internet of Things (IoT) should enable machine-to-machine interaction for devices out of numerous domains. Recent developments and standards focus on how to deploy IP directly on devices and investigate application protocols that fit the constrained environments, whereas research on the integration of widely deployed legacy devices of technologies like BACnet, Lon Works and KNX is still neglected. For a success of the ambitions towards an IoT we identify it of highest importance to research various integration styles for non-IP based devices already deployed in home and building automation. Therefore, this paper contributes an overview of various possible integration styles, provides a concrete multi-protocol integration architecture and presents evaluation results of a proof of concept implementation.

Big data for smart cities with KNIME a real experience in the SmartSantander testbed

Big data techniques are conceived as the powerful tool to exploit all the potential of the Internet of Things and the smart cities. A new dimension of understanding about the human behaviours is expected to be reached through all the gathered data in the emerging smart environment. The described potential, so‐called Human Dynamics, pursues to describe in real‐time the human behaviours and activities. This work presents our experiences for big data analytics in smart cities, in terms of sensors data management, data fusion and knowledge discovery from the data. The data used is from the European Project SmartSantander, where the traffic behaviour has been correlated with respect to the temperature in the Santander City. The evolution of both flows present a similar behaviour, in detail, a fine grain correlation is discovered. On the one hand, the traffic distribution, aggregated by temperature bins, follows up a Poisson distribution model. The Poisson modelling allows to interpolate and predict complex behaviours based on simple measures such as the temperature. At the same time, on the other hand, the isolated traffic density distribution, without taking into account the temperature‐based aggregation has been analysed. The traffic distribution has presented a burst behaviour, which presents a closer model to the human dynamics. Therefore, this work presents as the smart cities data can be modelled as Poisson or Human Dynamics (burst models). Finally, reference data analytics process, data sets and models are offered for the Open Source Data analytics platform Konstanz Information Miner (KNIME). Copyright

Big Data in Smart Cities: From Poisson to Human Dynamics

Big Data is conceived as the powerful tool to exploit all the potential of the Internet of Things and the Smart Cities. Historically several of the human-related behaviours have been modelled with Poisson distribution, but a new dimension of understanding about the human behaviours is reached through all the gathered data in the emerging smart environment. This work analyses the data from the European Project SmartSantander. This work has correlated the traffic behaviour with respect to the temperature in the Santander City. This has been presented as the evolution of both flows present a similar behaviour. The traffic distribution, aggregated by temperature bins, follows up a Poisson distribution model. Thereby, allowing interpolate and predict complex behaviours based on simple measures such as the temperature. At the same time, this data presents a burst behaviour (human dynamics), when the data is analysed in sequence, instead of aggregated by temperature bins. Therefore, this work concludes that human-related behaviours can be described with both, Poisson and Human Dynamics distribution, depending on how the data is represented and aggregated.

Big Data for Cyber Physical Systems: An Analysis of Challenges, Solutions and Opportunities

Cyber-Physical Systems (CPS) covers from M2M and Internet of Things (IoT) communications, heterogeneous data integration from multiple sources, security / privacy and its integration into the cloud computing and Big Data platforms. The integration of Big Data into CPS solutions presents several challenges and opportunities. Big Data for CPS is not suitable with conventional solutions based on offline or batch processing. The interconnection with the real-world, in industrial and critical environments, requires reaction in real-time. Therefore, real-time will be a vertical requirement from communication to Big Data analytics. Big Data for CPS requires on the one hand, real-time streams processing for real-time control, and on the other hand, batch processing for modeling and behaviors learning. This paper describes the existing solutions and the pending challenges, providing some guidelines to address the challenges.

Internet of Things for Cultural Heritage of Smart Cities and Smart Regions

Different from big cities, small towns call for culture preservation in addition to revitalization. IoT technologies could potentially serve this need. This article develops an IoT architecture, and choose best IoT enabling technologies, and IoT services, applications, and standards, towards this goal. In this article, we focus on the opportunities and challenges of applying IoT to culture preservation and revitalization of smart towns. We expect that the intelligent use of IoT could breathe new life into traditional, close-knit culture of small towns.

Social Internet of Things: The Potential of the Internet of Things for Defining Human Behaviours

The potential of the artificial intelligence, data mining and the so-called Big Data to build solutions based on the understanding of human behaviours is being extended with the capabilities of the Future Internet and the Internet of Things (IoT). The described potential of data and networks have been analyzed by the complex network theory, offering a specialized branch, the defined as Human Dynamics. The goal with the Internet of Things in the social area is to describe in real-time the human behaviours and activities. These goals are starting to be feasible through the quantity of data provided by the personal devices such as smart phone, and the smart environments such as Smart cities that makes more intelligent the environment and offer a smart space that sense our movements, actions, and the evolution of the ecosystem. This work analyses the ecosystem defined through the triangle formed by Big Data, Smart Cities and Personal/Wearable Computing to determinate human behaviours and human dynamics. For this purpose, the life-cycle of human dynamics determinations in Smart Cities have been analysed in order to determinate the current status of the technology, challenges, and opportunities.

Determining Human Dynamics through the Internet of Things

The potential of the artificial intelligence to build solutions based on the understanding of human behaviours, and the capacity to discover patterns through their interactions with the world is being extended with the capabilities of the Internet of Things. The described potential, so-called Human Dynamics, pursues to describe in real-time the human behaviours and activities. These goals are starting to be feasible through the quantity of data provided by two of the main areas of the Internet of Things, on the one hand, the Smart cities to make more intelligent the environment and offer a smart space that sense our movements, actions, and the evolution of the ecosystem, and on the other hand, the wearable and mobile computing which allows to provide data from the humans itself, i.e., from their pockets (smart phones), wrists (smart watches), hearts (wearable sensors), and eyes (glasses). This work analyses the ecosystem defined through the triangle formed by Big Data, Smart Cities and Wearable Computing to determinate human dynamics. For this purpose, the life-cycle of human dynamics determinations in Smart Cities have been analysed in order to determinate the current status of the technology, challenges, and opportunities.

Enabling federated emergencies and Public Safety Answering Points with wearable and mobile Internet of Things support: An approach based on EENA and OMA LWM2M emerging standards

We are witnessing the emergence of a new technology paradigm, one which focuses on the large scale integration and simplification of distributed technologies along with their fundamental realignment around the needs of people and society. The new Human Centric Intelligent Society results from these changes is connecting information from many different sources across the physical and virtual worlds, using the power of integration to achieve new insights and to enact change in ways which are quicker and more context aware than ever before. The Human Centric integration will lead to safer, more comfortable and more prosperous societies, but before arriving to this status, we have several challenges for the existing platforms to be migrated and digitalized into a common Cloud Computing ecosystem, and enable the common things with a Web of Things capabilities that can enable new forms of social infrastructure that react to the needs of people in real time. In this work, we present the contributions and extensions to the EENA Public Safety Answering Points standards and data structure (PIDFLO), in order to enable it with the capabilities to be integrated with data coming from personal and wearable sensors (Internet of Things). In details, we have extended PIDF-LO with the support of OMA LwM2M Web Objects, in order to offer a scalable and interoperable integration of the Internet of Things and the European Emergencies Services based on Open Standards.

Short paper: Sensors data fusion for Smart Cities with KNIME: A real experience in the SmartSantander Testbed

Big Data is conceived as the powerful tool to exploit all the potential of the Internet of Things and the Smart Cities. A new dimension of understanding about the human behaviours is expected to be reached through all the gathered data in the emerging smart environment. This work analyses the data from the European Project SmartSantander. This work has correlated the traffic behaviour with respect to the temperature in the Santander City. This has been presented as the evolution of both flows present a similar behaviour. Specifically, they present a fine grain correlation of over the 57%. Finally, it has been also presented as the traffic distribution, aggregated by temperature bins, follows up a Poisson distribution model. Thereby, allowing interpolate and predict complex behaviours based on simple measures such as the temperature.