Enabling IoT in Manufacturing: from device to the cloud

Industrial automation platforms are experiencing a paradigm shift. With the new technol-ogies and strategies that are being applied to enable a synchronization of the digital and real world, including real-time access to sensorial information and advanced networking capabilities to actively cooperate and form a nervous system within the enterprise, the amount of data that can be collected from real world and processed at digital level is growing at an exponential rate. Indeed, in modern industry, a huge amount of data is coming through sensorial networks em-bedded in the production line, allowing to manage the production in real-time. This dissertation proposes a data collection framework for continuously collecting data from the device to the cloud, enabling resources at manufacturing industries shop floors to be handled seamlessly. The framework envisions to provide a robust solution that besides collecting, transforming and man-aging data through an IoT model, facilitates the detection of patterns using collected historical sensor data. Industrial usage of this framework, accomplished in the frame of the EU C2NET project, supports and automates collaborative business opportunities and real-time monitoring of the production lines

Internet Predictions

More than a dozen leading experts give their opinions on where the Internet is headed and where it will be in the next decade in terms of technology, policy, and applications. They cover topics ranging from the Internet of Things to climate change to the digital storage of the future. A summary of the articles is available in the Web extras section

Internet of things: Vision, applications and research challenges

The term “Internet-of-Things” is used as an umbrella keyword for covering various aspects related to the extension of the Internet and the Web into the physical realm, by means of the widespread deployment of spatially distributed devices with embedded identification, sensing and/or actuation capabilities. Internet-of-Things envisions a future in which digital and physical entities can be linked, by means of appropriate information and communication technologies, to enable a whole new class of applications and services. In this article, we present a survey of technologies, applications and research challenges for Internet-of-Things

When things matter: A survey on data-centric Internet of Things

With the recent advances in radio-frequency identification (RFID), low-cost wireless sensor devices, and Web technologies, the Internet of Things (IoT) approach has gained momentum in connecting everyday objects to the Internet and facilitating machine-to-human and machine-to-machine communication with the physical world. IoT offers the capability to connect and integrate both digital and physical entities, enabling a whole new class of applications and services, but several significant challenges need to be addressed before these applications and services can be fully realized. A fundamental challenge centers around managing IoT data, typically produced in dynamic and volatile environments, which is not only extremely large in scale and volume, but also noisy and continuous. This paper reviews the main techniques and state-of-the-art research efforts in IoT from data-centric perspectives, including data stream processing, data storage models, complex event processing, and searching in IoT. Open research issues for IoT data management are also discussed

Rover: Architectural Support for Exposing and Using Context

Technology has advanced to the point where many people feel it has created a world with an insurmountable amount of information. Information includes messages people send to each other, logged data from their activities, and the services available to them. This problem has been exaggerated in modern societies by high availability of Internet connectivity. All types of information contains context, whether they have been stated explicitly or understood implicitly. Understanding, handling, and using context represents one of the most critical steps towards coping with the amount of information available today. In this dissertation, we examine two topics: context and the design of a context-aware platform. We describe fundamental types of context associated with every piece of information and discuss issues which may occur when implementing a system which utilizes context. We present a context-aware platform called Rover. The Rover architecture provides a conceptual framework geared towards understanding how application developers can utilize a variety of aspects of context to assist the development of modern applications. To aid developers in figuring out what context may be useful in their application, we describe the concept of a Rover ecosystem: a logical organization analogous to how similar groups of people interact with each other. We also discuss how information and context can be shared between ecosystems. To examine the feasibility of the Rover architecture's conceptual framework, we have implemented a reference implementation of the core unit of a Rover ecosystem: the Rover server. We discuss the details of the Rover server and describe the implementation of an emergency response application which demonstrates the utility of the conceptual framework