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Über dieses Buch

The Internet of Things (IoT) usually refers to a world-wide network of interconnected heterogeneous objects (sensors, actuators, smart devices, smart objects, RFID, embedded computers, etc) uniquely addressable, based on standard communication protocols. Beyond such a definition, it is emerging a new definition of IoT seen as a loosely coupled, decentralized system of cooperating smart objects (SOs). A SO is an autonomous, physical digital object augmented with sensing/actuating, processing, storing, and networking capabilities. SOs are able to sense/actuate, store, and interpret information created within themselves and around the neighbouring external world where they are situated, act on their own, cooperate with each other, and exchange information with other kinds of electronic devices and human users. However, such SO-oriented IoT raises many in-the-small and in-the-large issues involving SO programming, IoT system architecture/middleware and methods/methodologies for the development of SO-based applications. This Book will specifically focus on exploring recent advances in architectures, algorithms, and applications for an Internet of Things based on Smart Objects. Topics appropriate for this Book include, but are not necessarily limited to: - Methods for SO development - IoT Networking - Middleware for SOs - Data Management for SOs - Service-oriented SOs - Agent-oriented SOs - Applications of SOs in Smart Environments: Smart Cities, Smart Health, Smart Buildings, etc. Advanced IoT Projects.

Inhaltsverzeichnis

Frontmatter

Middlewares for Smart Objects and Smart Environments: Overview and Comparison

Abstract
In the last few years, the Internet of Things (IoT) is gaining more and more attention both in the academic and in the industrial worlds. IoT is a concept describing a vision in which everyday objects will be connected to the Internet, will be identified, and will, possibly, communicate with other devices. These objects are typically referred as “smart objects”, which can be defined as real artifacts augmented with computing, communication, sensing/actuation and storing functionalities. Their importance resides in the capabilities they have to make physical environments “smart” so as to provide novel cyberphysical services to people. In the last years, several middlewares for SOs were proposed. Middlewares, widely used in conventional distributed systems, are fundamental tools for the design and implementation of smart objects as well as of smart environment applications. They provide general and specific abstractions (e.g. object computation model, inter-object communication, sensory/actuation interfaces, discovery service, knowledge management) through which smart objects and their related applications can be easily built up. In this chapter, we present an overview of middlewares for smart objects and smart environments and compare them according to the most important general and specific requirements that have been identified in the literature so far. Moreover, such middlewares are also compared according to a feature-oriented framework to better highlight their distinctive properties. The comparison therefore provides a clear picture about the suitability of such middlewares to support the development of SO-based IoT systems. Finally, the chapter will briefly discuss on-going challenges in this research area.
Giancarlo Fortino, Antonio Guerrieri, Wilma Russo, Claudio Savaglio

Mobile Agents-Based Smart Objects for the Internet of Things

Abstract
We propose mobile agents for enabling interoperability and global intelligence with smart objects in the Internet of Things, with heterogeneous low-power resource-constrained devices where the systems span over disparate networks and protocols. As the Internet of Things systems are in continuous transition, requiring software adaptation and system evolution, an adaptable composition is presented for the mobile agents. The composition complies with the Representational State Transfer principles, which are then utilized in agent creation, migration and control. Moreover, the smart objects’ resources, their capabilities, their information and provided services are exposed to the Web for human-machine interactions. We consider the requirements for enabling mobile agents in the Internet of Things from multiple perspectives: the smart object, the mobile agent and the system. We present interfaces for smart object internal architecture to enable mobile agents and to enable their interactions. An application programming interface is suggested with a system reference architecture, which includes components in the information infrastructure. Lastly, an evaluation metrics for the mobile agent composition and for the smart objects’ resource utilization are suggested, taking the different types of system resources and their utilization into account, assisting in the system, application, smart object and the mobile agent design.
Teemu Leppänen, Jukka Riekki, Meirong Liu, Erkki Harjula, Timo Ojala

Service-Oriented Middleware for the Cooperation of Smart Objects and Web Services

Abstract
Many physical devices can be interconnected and cooperate by Internet of Things (IoT), providing and consuming information available on the network. These will not only provide information by monitoring the real-world, but create complex collaborations, interacting also with business processes, in order to provide sophisticated value-added services. In addition, business processes can also adapt their behavior in response to real-time context updates. Web services technology offers a promising approach to provide information and functionalities of physical objects to business processes, since it facilitates interoperability and encapsulates the heterogeneity and specificity of physical objects. To address the dynamic composition of web services in a decentralized, distributed manner, with no single point of failure, a choreography execution model can be used. This chapter describes an approach to support adaptable business processes (workflows) considering changes in the state of Things; likewise, whenever needed, the software controlling the behavior of sensors can be dynamically configured as a result of changes in the functional specifications of business processes.
Andrea Giordano, Giandomenico Spezzano

CO-Based Outdoor Smart Lighting for Energy Aware Factory

Abstract
Energy awareness together with holistic perception of consumption processes are one of the main factors contributing to efficient and sustainable performance of such complex systems as buildings, cities, and factories. Availability of relevant data and possibility for cross-domain integration become minimum requirements defining the success of the implementation. Emergence of cooperating smart objects, resulting from evolution in IoT and embedded devices, helps achieving both energy awareness and efficiency by offering possibility of sensing and acting over complex environments and overcome challenges associated with cross-domain integration. This chapter describes smart lighting application for the industrial outdoor environment implemented using cooperating objects featuring Semantic Web Service middleware. Presented use-case considers the university campus area comprising multipurpose outdoor area and neighbouring industrial laboratory facilities. The application is aiming efficient use of energy and possibility for integration with relevant industrial systems.
Anna Florea, Ahmed Farahat, Corina Postelnicu, Jose L. Martinez Lastra, Francisco J. Azcondo Sánchez

A Service-Oriented Discovery Framework for Cooperating Smart Objects

Abstract
The chapter presents a service-oriented framework designed to support indexing, discovery and selection of network-enabled Smart objects. The framework allows the dynamical discovery of distributed Smart objects and, specifically, the services and operations they provide. To this end, a new metadata model has been defined to describe features, services, and operations of network-enabled Smart objects, and a service-oriented service, accessible through a REST interface, has been implemented for registering, searching and selecting Smart objects on the basis of application needs. The chapter describes the metadata model, the framework architecture and implementation, and the programming APIs.
Marco Lackovic, Paolo Trunfio

Smart Manufacturing Through Cloud-Based Smart Objects and SWE

Abstract
Smart manufacturing is a key aspect for innovation and competitiveness, and involves several dimensions of the production chain to be analysed, assessed and enhanced within a factory. To target this issue, concepts and ideas behind the IoT (Internet of Things) are applied, so that connected smart entities cooperate in order to achieve broader goals or increase the overall knowledge in the factory through information sharing. Smart entities in the IoT are typically referred as WSNs (Wireless Sensor Networks) that capture physical (real) data and events and produce virtual (digital) information to be processed. Unfortunately, current WSNs have limited interoperability and processing capabilities, reducing the integration degree with existing applications. This chapter proposes a solution for both previous technical challenges within a factory. Interoperability is achieved by means of SWE (Sensor Web Enablement) whereas processing capabilities are provided through virtualizing smart objects in a datacentre, placed commonly in the factory but it could also be located elsewhere, applying cloud-based techniques. The architecture and deployment has been arranged for the specific use case of a manufacturing company and a risk prevention scenario. Experimentation results show that smart objects could be provided at runtime with fine granularity level depending on the tasks to be performed. Moreover, smart objects are able to co-operate forming meta-objects to satisfy global tasks or minimize certain risks. Finally, smart objects are able to encapsulate private (health and/or personal) data that should not be shared with other objects or processes.
Pablo Giménez, Benjamín Molina, Carlos E. Palau, Manuel Esteve, Jaime Calvo

The Cloud of Things Empowered Smart Grid Cities

Abstract
The emergence of the Smart Grid era fuels a new generation of innovative applications and services that are built upon fine-grained monitoring and control capabilities pertaining the underlying infrastructure, such as that of future Smart Cities. Collection, processing and analytics on the Internet of Things of massively generated data, as well as potential management functions will emerge; therefore making a reality informed real-time decision making as well as its enforcement in a timely manner over complex infrastructures. The prevalence of the Cloud and its services, can very well complement the Internet of Things when it comes to massive data management, giving rise to the Cloud of Things (CoT). For the next generation applications, the CoT can enable access to generic multi-modal energy services, on-top of which development of more sophisticated solutions can be realized. We depict here such Smart Grid services for the Smart City of the future, as well as experiences from their realization.
Stamatis Karnouskos

Trajectory Data Analysis Over a Cloud-Based Framework for Smart City Analytics

Abstract
The chapter presents a Cloud-based framework that can be tailored to be used in different scenarios of urban planning and management occuring in Smart Cities. The focus is on the management of large-scale socio-geographic data obtained through the trajectories traced by smart objects. Our goal is to mine human activities and routines from this socio-geographic data in order to catch user’s behaviour. To this aim, we introduce a methodology for trajectory pattern mining consisting in (a) finding frequent regions, more densely passed through ones, and (b) extracting trajectory patterns from those regions. Experimental evaluation shows that due to complexity and large data involved in the application scenario, the trajectory pattern mining process can take advantage from a parallel execution environment offered by a Cloud architecture.
Eugenio Cesario, Carmela Comito, Domenico Talia

People-Centric Service for mHealth of Wheelchair Users in Smart Cities

Abstract
Urban dwellers are soul of smart cities, and all final aims of city applications are people-centric. mHealth is a new generation method for personal healthcare, specially smart phone is widely used to interact with surroundings by the disabled and elderly people in smart cities. Existing massive of sensors, actuators, and smart objects are separated and controlled in different owners and community. Mobile devices of people-centric sensing (PCS) can receive data in opportunistic sensing according to mobile geo-location, dynamic social relationship, and interests of people, etc. In this work, we present a real-time health-driven model for people-centric healthcare context, and present a social-aware architecture to support smart objects mapping to online social networks, then present discovering and interacting with shared smart objects in a virtual community. Finally, we present a prototype system to validate the people-centric mHealth service model.
Lin Yang, Wenfeng Li, Yanhong Ge, Xiuwen Fu, Raffaele Gravina, Giancarlo Fortino

Experiments with a Sensing Platform for High Visibility of the Data Center

Abstract
Data centers are large energy consumers and a substantial portion of this power consumption is due to the control of physical parameters, which bring the need of high efficiency environmental control systems. In this work, we describe a hardware sensing platform specifically tailored to collect physical parameters (temperature, pressure, humidity and power consumption) in large data centers. Our system architecture is composed of Smart Objects, the datacenter racks, that cooperate to contribute for the overall goal of finding opportunities to optimize energy consumption and achieving energy-efficient data centers. We also introduce an analysis of the delay to obtain the sensing data from the sensor network. This analysis provides an insight into the time scales supported by our platform, and also allows to study the delay for different data center topologies. Finally, we exemplify some capabilities of the system with a real deployment.
João Loureiro, Nuno Pereira, Pedro Santos, Eduardo Tovar
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