In recent year, the Internet of Things (IoT) has drawn significant research attention. IoT is considered as a part of the Internet of the future and will comprise billions of intelligent communicating `things'. The future of the Internet will consist of heterogeneously connected devices that will further extend the borders of the world with physical entities and virtual components. The Internet of Things (IoT) will empower the connected things with new capabilities. In this survey, the definitions, architecture, fundamental technologies, and applications of IoT are systematically reviewed. Firstly, various definitions of IoT are introduced; secondly, emerging techniques for the implementation of IoT are discussed; thirdly, some open issues related to the IoT applications are explored; finally, the major challenges which need addressing by the research community and corresponding potential solutions are investigated.

The internet of things: a survey

Internet of Things (IoT) has provided a promising opportunity to build powerful industrial systems and applications by leveraging the growing ubiquity of radio-frequency identification (RFID), and wireless, mobile, and sensor devices. A wide range of industrial IoT applications have been developed and deployed in recent years. In an effort to understand the development of IoT in industries, this paper reviews the current research of IoT, key enabling technologies, major IoT applications in industries, and identifies research trends and challenges. A main contribution of this review paper is that it summarizes the current state-of-the-art IoT in industries systematically.

Internet of Things in Industries: A Survey

We propose the task of free-form and open-ended Visual Question Answering (VQA). Given an image and a natural language question about the image, the task is to provide an accurate natural language answer. Mirroring real-world scenarios, such as helping the visually impaired, both the questions and answers are open-ended. Visual questions selectively target different areas of an image, including background details and underlying context. As a result, a system that succeeds at VQA typically needs a more detailed understanding of the image and complex reasoning than a system producing generic image captions. Moreover, VQA is amenable to automatic evaluation, since many open-ended answers contain only a few words or a closed set of answers that can be provided in a multiple-choice format. We provide a dataset containing ~0.25M images, ~0.76M questions, and ~10M answers (www.visualqa.org), and discuss the information it provides. Numerous baselines for VQA are provided and compared with human performance.

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VQA: Visual Question Answering

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 Internetof-Things.

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Internet of things: Vision, applications and research challenges

We propose the task of free-form and open-ended Visual Question Answering (VQA). Given an image and a natural language question about the image, the task is to provide an accurate natural language answer. Mirroring real-world scenarios, such as helping the visually impaired, both the questions and answers are open-ended. Visual questions selectively target different areas of an image, including background details and underlying context. As a result, a system that succeeds at VQA typically needs a more detailed understanding of the image and complex reasoning than a system producing generic image captions. Moreover, VQA is amenable to automatic evaluation, since many open-ended answers contain only a few words or a closed set of answers that can be provided in a multiple-choice format. We provide a dataset containing ~0.25M images, ~0.76M questions, and ~10M answers (this http URL), and discuss the information it provides. Numerous baselines and methods for VQA are provided and compared with human performance. Our VQA demo is available on CloudCV (this http URL).

Creating networks of “smart things” found in the physical world (e.g., with RFID, wireless sensor and actuator networks, embedded devices) on a large scale has become the goal of a variety of recent research activities. Rather than exposing real-world data and functionality through vertical system designs, we propose to make them an integral part of the Web. As a result, smart things become easier to build upon. In such an architecture, popular Web technologies (e.g., HTML, JavaScript, Ajax, PHP, Ruby) can be used to build applications involving smart things, and users can leverage well-known Web mechanisms (e.g., browsing, searching, bookmarking, caching, linking) to interact with and share these devices. In this chapter, we describe the Web of Things (WoT) architecture and best practices based on the RESTful principles that have already contributed to the popular success, scalability, and evolvability of the Web. We discuss several prototypes using these principles, which connect environmental sensor nodes, energy monitoring systems, and RFID-tagged objects to the Web. We also show how Web-enabled smart things can be used in lightweight ad-hoc applications, called “physical Mashups”, and discuss some of the remaining challenges towards the global World Wide Web of Things.

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From the Internet of Things to the Web of Things: Resource-oriented Architecture and Best Practices

Many efforts are centered around creating large-scale networks of “smart things” found in the physical world (e.g., wireless sensor and actuator networks, embedded devices, tagged objects). Rather than exposing real-world data and functionality through proprietary and tightly-coupled systems, we propose to make them an integral part of the Web. As a result, smart things become easier to build upon. Popular Web languages (e.g., HTML, Python, JavaScript, PHP) can be used to easily build applications involving smart things and users can leverage well-known Web mechanisms (e.g., browsing, searching, bookmarking, caching, linking) to interact and share these devices. In this paper, we begin by describing the Web of Things architecture and best-practices based on the RESTful principles that have already contributed to the popular success, scalability, and modularity of the traditional Web. We then discuss several prototypes designed in accordance with these principles to connect environmental sensor nodes and an energy monitoring system to the World Wide Web. We finally show how Web-enabled smart things can be used in lightweight ad-hoc applications called “physical mashups”.

A resource oriented architecture for the Web of Things

Loose coupling is often quoted as a desirable property of systems architectures. One of the main goals of building systems using Web technologies is to achieve loose coupling. However, given the lack of a widely accepted definition of this term, it becomes hard to use coupling as a criterion to evaluate alternative Web technology choices, as all options may exhibit, and claim to provide, some kind of "loose" coupling effects. This paper presents a systematic study of the degree of coupling found in service-oriented systems based on a multi-faceted approach. Thanks to the metric introduced in this paper, coupling is no longer a one-dimensional concept with loose coupling found somewhere in between tight coupling and no coupling. The paper shows how the metric can be applied to real-world examples in order to support and improve the design process of service-oriented systems.

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Why is the web loosely coupled?: a multi-faceted metric for service design

This article introduces and discusses the concept of academic search engine optimization (ASEO). Based on three recently conducted studies, guidelines are provided on how to optimize scholarly literature for academic search engines in general, and for Google Scholar in particular. In addition, we briefly discuss the risk of researchers' illegitimately ‘over-optimizing’ their articles.

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Academic Search Engine Optimization ( ASEO ): Optimizing Scholarly Literature for Google Scholar & Co.

Integrating resources into the Web is an important aspect of making them accessible as part of this global information system. The integration of physical things into the Web so far has not been done on a large scale, which makes it harder to realize network effects that could emerge by the combination of today's Web content, and the integration of physical things into the Web. This paper presents a path towards a Web where physical objects are made available through RESTful principles. By using this architectural style for pervasive and ubiquitous computing scenarios, they will scale better, integrate better with other applications, and pave the path towards a Web of Things that seamlessly integrates conceptual and physical resources.

https://escholarship.org/content/qt1786t1dm/qt1786t1dm.pdf

Erik Wilde

Papers

From the Internet of Things to the Web of Things: Resource-oriented Architecture and Best Practices

A resource oriented architecture for the Web of Things

Why is the web loosely coupled?: a multi-faceted metric for service design

Academic Search Engine Optimization ( ASEO ): Optimizing Scholarly Literature for Google Scholar & Co.

Putting Things to REST