As we are moving towards the Internet of Things (IoT), the number of sensors deployed around the world is growing at a rapid pace. Market research has shown a significant growth of sensor deployments over the past decade and has predicted a significant increment of the growth rate in the future. These sensors continuously generate enormous amounts of data. However, in order to add value to raw sensor data we need to understand it. Collection, modelling, reasoning, and distribution of context in relation to sensor data plays critical role in this challenge. Context-aware computing has proven to be successful in understanding sensor data. In this paper, we survey context awareness from an IoT perspective. We present the necessary background by introducing the IoT paradigm and context-aware fundamentals at the beginning. Then we provide an in-depth analysis of context life cycle. We evaluate a subset of projects (50) which represent the majority of research and commercial solutions proposed in the field of context-aware computing conducted over the last decade (2001-2011) based on our own taxonomy. Finally, based on our evaluation, we highlight the lessons to be learnt from the past and some possible directions for future research. The survey addresses a broad range of techniques, methods, models, functionalities, systems, applications, and middleware solutions related to context awareness and IoT. Our goal is not only to analyse, compare and consolidate past research work but also to appreciate their findings and discuss their applicability towards the IoT.

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Context Aware Computing for The Internet of Things: A Survey

A smart phone senses audio, imagery, and/or other stimulus from a user's environment, and acts autonomously to fulfill inferred or anticipated user desires. In one aspect, the detailed technology concerns phone-based cognition of a scene viewed by the phone's camera. The image processing tasks applied to the scene can be selected from among various alternatives by reference to resource costs, resource constraints, other stimulus information (e.g., audio), task substitutability, etc. The phone can apply more or less resources to an image processing task depending on how successfully the task is proceeding, or based on the user's apparent interest in the task. In some arrangements, data may be referred to the cloud for analysis, or for gleaning. Cognition, and identification of appropriate device response(s), can be aided by collateral information, such as context. A great number of other features and arrangements are also detailed.

Intuitive computing methods and systems

The book aims to provide a broad overview of various topics of the Internet of Things (IoT) from the research and development priorities to enabling technologies, architecture, security, privacy, interoperability and industrial applications. It is intended to be a standalone book in a series that covers the Internet of Things activities of the IERC ? Internet of Things European Research Cluster from technology to international cooperation and the global "state of play". The book builds on the ideas put forward by the European research Cluster on the Internet of Things Strategic Research Agenda and presents global views and state of the art results on the challenges facing the research, development and deployment of IoT at the global level.

Internet of Things: Converging Technologies for Smart Environments and Integrated Ecosystems

Arrangements involving portable devices (e.g., smartphones and tablet computers) are disclosed. One arrangement enables a content creator to select software with which that creator's content should be rendered—assuring continuity between artistic intention and delivery. Another utilizes a device camera to identify nearby subjects, and take actions based thereon. Others rely on near field chip (RFID) identification of objects, or on identification of audio streams (e.g., music, voice). Some technologies concern improvements to the user interfaces associated with such devices. Others involve use of these devices in connection with shopping, text entry, sign language interpretation, and vision-based discovery. Still other improvements are architectural in nature, e.g., relating to evidence-based state machines, and blackboard systems. Yet other technologies concern use of linked data in portable devices—some of which exploit GPU capabilities. Still other technologies concern computational photography. A great variety of other features and arrangements are also detailed.

Smartphone-based methods and systems

Smart object technology, sometimes called the Internet of Things, is having a profound impact on our day-to-day lives. Interconnecting Smart Objects with IP is the first book that takes a holistic approach to the revolutionary area of IP-based smart objects. Smart objects are the intersection of networked embedded systems, wireless sensor networks, ubiquitous and pervasive computing, mobile telephony and telemetry, and mobile computer networking. This book consists of three parts, Part I focuses on the architecture of smart objects networking, Part II covers the hardware, software, and protocols for smart objects, and Part III provides case studies on how and where smart objects are being used today and in the future. The book covers the fundamentals of IP communication for smart objects, IPv6, and web services, as well as several newly specified low-power IP standards such as the IETF 6LoWPAN adaptation layer and the RPL routing protocol. This book contains essential information not only for the technical reader but also for policy makers and decision makers in the area of smart objects both for private IP networks and the Internet.



Shows in detail how connecting smart objects impacts our lives with practical implementation examples and case studies 
Provides an in depth understanding of the technological and architectural aspects underlying smart objects technology 
Offers an in-depth examination of relevant IP protocols to build large scale smart object networks in support of a myriad of new services 

Table of Contents

Part I: The Architecture Chapter 1: What are Smart objects? Chapter 2: The IP protocol architecture Chapter 3: Why IP for smart objects? Chapter 4: IPv6 for Smart Object Networks and The Internet of Things Chapter 5: Routing Chapter 6: Transport Protocols Chapter 7: Service Discovery Chapter 8: Security for Smart Objects Chapter 9: Web services For Smart Objects Chapter 10: Connectivity models for smart object networks 
Part II: The Technology Chapter 11: What is a Smart Object? Chapter 12: Low power link layer for smart objects networks Chapter 13: uIP A Lightweight IP Stack Chapter 14: Standardization Chapter 15: IPv6 for Smart Object Networks - A Technology Refresher Chapter 16: The 6LoWPAN Adaptation Layer Chapter 17: RPL Routing in Smart Object Networks Chapter 18: The IPSO Alliance Chapter 19: Non IP Technology

Part III: The Applications Chapter 20: Smart Grid Chapter 21: Industrial Automation Chapter 22: Smart Cities and Urban Networks Chapter 23: Home Automation Chapter 24: Building Automation Chapter 25: Structural Health Monitoring Chapter 26: Container Tracking

Interconnecting Smart Objects with IP: The Next Internet

Video sensors are used in wireless multimedia sensor networks (WMSNs) to enhance the capability for event description. Due to the limited transmission capacity of sensor nodes, a single path often cannot meet the requirement of video transmission. Consequently, multi-path transmission is needed. However, not every path found by multi-path routing algorithms may be suitable for transmitting video, because a long routing path with a long end to end transmission delay may not satisfy the time constraint of the video. Furthermore, each video stream includes two kinds of information: image and audio streams. In different applications, image and audio streams play different roles, and the importance levels are different. Higher priority should be given to the more important stream (either the image stream or the audio stream) to guarantee the using of limited bandwidth and energy in WMSNs. In this paper, we propose a Multi-priority Multi-path Selection (MPMPS) scheme in transport layer to choose the maximum number of paths from all found node-disjoint routing paths for maximizing the throughput of streaming data transmission. Simulation results show that MPMPS can effectively choose the maximum number of paths for video transmission.

Multi-priority Multi-path Selection for Video Streaming in Wireless Multimedia Sensor Networks

We present RDF On the Go, a full-fledged RDF storage and SPARQL query processor for mobile devices. Implemented by adapting the widely used Jena and ARQ Semantic Web Toolkit and query engine, it uses Berkeley DB for storing the RDF data, R-Trees for indexing spatial data indexing and a query processor that supports both standard and spatial queries.

By storing and querying RDF data locally at the user's mobile device, RDF On the Go contributes to improving scalability, decreasing transmission costs, and controlling access to user's personal information. It also enables the development of a next generation of mobile applications. RDF On the Go is available for the Android platform and can be downloaded at http://rdfonthego.googlecode.com/.

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RDF on the go: an RDF storage and query processor for mobile devices

Sensors have begun to infiltrate people's everyday lives. They can provide information about a car's condition, can enable smart buildings, and are being used in various mobile applications, to name a few. Generally, sensors provide information about various aspects of the real world. Online social networks, another emerging trend over the past six or seven years, can provide insights into the communication links and patterns between people. They have enabled novel developments in communications as well as transforming the Web from a technical infrastructure to a social platform, very much along the lines of the original Web as proposed by Tim Berners-Lee, which is now often referred to as the Social Web. In this position paper, we highlight some of the interesting research areas where sensors and social networks can fruitfully interface, from sensors providing contextual information in context-aware and personalized social applications, to using social networks as "storage infrastructures" for sensor information.

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Integrating Social Networks and Sensor Networks

During the development of context aware applications a context management component must traditionally be created. This task requires specialist context lifecycle management expertise and hence can be a significant deterrent to application development. It also removes the developers focus from differentiation of their application to an oft repeated development task. This issue can be addressed by encapsulating the context management lifecycle within a web-service, thus providing applications with a low-overhead alternative to managing their context data. The adoption of a web-based approach maximizes the potential number of interacting applications, including smart spaces, web and mobile applications, due to ease of access and widespread support of web technologies. The contribution of this paper is the development of a lifecycle, based on existing work on enterprise data and context aware lifecycles, which is optimized for web-based context management services (WCXMS) and the provision of a web-service implementation of the lifecycle.

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A context lifecycle for web-based context management services

We can envision that future sensor networks (WSNs) are ubiquitous, large-scale, interconnected, which we call worldwide sensor network (WWSN). Currently, most of the WSNs are working as isolated islands. Without sharing sensor data across different domains, the most important features of ubiquitous computing (e.g. context awareness) will not be easily achieved. For sharing among WWSN, the first nut to crack is to interconnect different WSNs which are spatially deployed in different locations with IP based Internet; the second one is to integrate them into a single WWSN over the Internet for publishing, sharing and searching of sensor data. In this paper, we present the challenge issues that should be addressed for sharing WWSN, by conducting a short survey on existing approaches.

Vinny Reynolds

Papers

Multi-priority Multi-path Selection for Video Streaming in Wireless Multimedia Sensor Networks

RDF on the go: an RDF storage and query processor for mobile devices

Integrating Social Networks and Sensor Networks

A context lifecycle for web-based context management services

Sharing Worldwide Sensor Network