Supporting service discovery, querying and interaction in ubiquitous computing environments.

In this paper, we contend that ubiquitous computing environments will be highly heterogeneous, service rich domains. Moreover, future applications will consequently be required to interact with multiple, specialised service location and interaction protocols simultaneously. We argue that existing service discovery techniques do not provide sufficient support to address the challenges of building applications targeted to these emerging environments. This paper makes a number of contributions. Firstly, using a set of short ubiquitous computing scenarios we identify several key limitations of existing service discovery approaches that reduce their ability to support ubiquitous computing applications. Secondly, we present a detailed analysis of requirements for providing effective support in this domain. Thirdly, we provide the design of a simple extensible meta-service discovery architecture that uses database techniques to unify service discovery protocols and addresses several of our key requirements. Lastly, we examine the lessons learnt through the development of a prototype implementation of our architecture

Software Platforms for Smart Cities: Concepts, Requirements, Challenges, and a Unified Reference Architecture

Making cities smarter help improve city services and increase citizens' quality of life. Information and communication technologies (ICT) are fundamental for progressing towards smarter city environments. Smart City software platforms potentially support the development and integration of Smart City applications. However, the ICT community must overcome current significant technological and scientific challenges before these platforms can be widely used. This paper surveys the state-of-the-art in software platforms for Smart Cities. We analyzed 23 projects with respect to the most used enabling technologies, as well as functional and non-functional requirements, classifying them into four categories: Cyber-Physical Systems, Internet of Things, Big Data, and Cloud Computing. Based on these results, we derived a reference architecture to guide the development of next-generation software platforms for Smart Cities. Finally, we enumerated the most frequently cited open research challenges, and discussed future opportunities. This survey gives important references for helping application developers, city managers, system operators, end-users, and Smart City researchers to make project, investment, and research decisions.Comment: Accepted for publication in ACM Computing Survey

Managing large amounts of data generated by a Smart City internet of things deployment

The Smart City concept is being developed from a lot of different axes encompassing multiple areas of social and technical sciences. However, something that is common to all these approaches is the central role that the capacity of sharing information has. Hence, Information and Communication Technologies (ICT) are seen as key enablers for the transformation of urban regions into Smart Cities. Two of these technologies, namely Internet of Things and Big Data, have a predominant position among them. The capacity to "sense the city" and access all this information and provide added-value services based on knowledge derived from it are critical to achieving the Smart City vision. This paper reports on the specification and implementation of a software platform enabling the management and exposure of the large amount of information that is continuously generated by the IoT deployment in the city of Santander.This work has been partially funded by the research project SmartSantander, under FP7- ICT-2009-5 of the 7th Framework Programme of the European Community. The authors would also like to express their gratitude to the Spanish government for the funding in the following project: "Connectivity as a Service: Access for the Internet of the Future", COSAIF (TEC2012-38574-C02-01)

Context Aware Computing for The Internet of Things: A Survey

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.Comment: IEEE Communications Surveys & Tutorials Journal, 201

Internet of Things Strategic Research Roadmap

Internet of Things (IoT) is an integrated part of Future Internet including existing and evolving Internet and network developments and could be conceptually defined as a dynamic global network infrastructure with self configuring capabilities based on standard and interoperable communication protocols where physical and virtual “things” have identities, physical attributes, and virtual personalities, use intelligent interfaces, and are seamlessly integrated into the information network

Systematizing Decentralization and Privacy: Lessons from 15 Years of Research and Deployments

Decentralized systems are a subset of distributed systems where multiple authorities control different components and no authority is fully trusted by all. This implies that any component in a decentralized system is potentially adversarial. We revise fifteen years of research on decentralization and privacy, and provide an overview of key systems, as well as key insights for designers of future systems. We show that decentralized designs can enhance privacy, integrity, and availability but also require careful trade-offs in terms of system complexity, properties provided, and degree of decentralization. These trade-offs need to be understood and navigated by designers. We argue that a combination of insights from cryptography, distributed systems, and mechanism design, aligned with the development of adequate incentives, are necessary to build scalable and successful privacy-preserving decentralized systems

SmartSantander: Internet of Things research and innovation through citizen participation

The Smart City concept relates to improving efficiency of city services and facilitating a more sustainable development of cities. However, it is important to highlight that, in order to effectively progress towards such smart urban environments, the people living in these cities must be tightly engaged in this endeavour. This paper presents two novel services that have been implemented in order to bring the Smart City closer to the citizen. The Participatory Sensing service we are proposing exploits the advanced features of smartphones to make the user part of the ubiquitous sensing infrastructure over which the Smart City concept is built. The Augmented Reality service is connected to the smart city platform in order to create an advanced visualization tool where the plethora of available information is presented to citizens embedded in their natural surroundings. A brief description of the smart city platform on top of which these services are built is also presented.Although only a few names appear in this paper’s list of authors, this work would not have been possible without the contribution and encouragement of the enthusiastic team of the SmartSantander project which has been partially funded by the European Commission under the contract number FP7-ICT-257992

Creating human digital memories with the aid of pervasive mobile devices

The abundance of mobile and sensing devices, within our environment, has led to a society in which any object, embedded with sensors, is capable of providing us with information. A human digital memory, created with the data from these pervasive devices, produces a more dynamic and data rich memory. Information such as how you felt, where you were and the context of the environment can be established. This paper presents the DigMem system, which utilizes distributed mobile services, linked data and machine learning to create such memories. Along with the design of the system, a prototype has also been developed, and two case studies have been undertaken, which successfully create memories. As well as demonstrating how memories are created, a key concern in human digital memory research relates to the amount of data that is generated and stored. In particular, searching this set of big data is a key challenge. In response to this, the paper evaluates the use of machine learning algorithms, as an alternative to SPARQL, and treats searching as a classification problem. In particular, supervised machine learning algorithms are used to find information in semantic annotations, based on probabilistic reasoning. Our approach produces good results with 100% sensitivity, 93% specificity, 93% positive predicted value, 100% negative predicted value, and an overall accuracy of 97%