Smart City Domain Research Articles

A Platform for Smart Object Virtualization and Composition

One of the most challenging objectives of the Internet of Things (IoT) domain is the identification of interaction paradigms and communication standards to integrate smart objects (SOs), i.e., physical objects able to interact with the network. Such interaction paradigms and communication protocols belong to what can be called the IoT application layer, on which this paper focuses. This paper presents app execution platform (AEP), a platform that supports the design, deployment, execution, and management of IoT applications in the domain of smart home, smart car, and smart city. AEP was designed to coherently fulfill a set of requirements covered only partially or in a fragmented way by other IoT application platforms. AEP focuses on SO virtualization and on composite application (CA) orchestration and supports dynamic object availability.

Applications of big data to smart cities

Many governments are considering adopting the smart city concept in their cities and implementing big data applications that support smart city components to reach the required level of sustainability and improve the living standards. Smart cities utilize multiple technologies to improve the performance of health, transportation, energy, education, and water services leading to higher levels of comfort of their citizens. This involves reducing costs and resource consumption in addition to more effectively and actively engaging with their citizens. One of the recent technologies that has a huge potential to enhance smart city services is big data analytics. As digitization has become an integral part of everyday life, data collection has resulted in the accumulation of huge amounts of data that can be used in various beneficial application domains. Effective analysis and utilization of big data is a key factor for success in many business and service domains, including the smart city domain. This paper reviews the applications of big data to support smart cities. It discusses and compares different definitions of the smart city and big data and explores the opportunities, challenges and benefits of incorporating big data applications for smart cities. In addition it attempts to identify the requirements that support the implementation of big data applications for smart city services. The review reveals that several opportunities are available for utilizing big data in smart cities; however, there are still many issues and challenges to be addressed to achieve better utilization of this technology.

SensorHUB: An IoT Driver Framework for Supporting Sensor Networks and Data Analysis

The Internet of Things (IoT) is transforming the surrounding everyday physical objects into an ecosystem of information that enriches our everyday life. The IoT represents the convergence of advances in miniaturization, wireless connectivity, and increased data storage and is driven by various sensors. Sensors detect and measure changes in position, temperature, light, and many others; furthermore, they are necessary to turn billions of objects into data-generating “things” that can report on their status and often interact with their environment. Application and service development methods and frameworks are required to support the realization of solutions covering data collection, transmission, data processing, analysis, reporting, and advanced querying. This paper introduces the SensorHUB framework that utilizes the state-of-the-art open source technologies and provides a unified tool chain for IoT related application and service development. SensorHUB is both a method and an environment to support IoT related application and service development; furthermore, it supports the data monetization approach, that is, provides a method to define data views on top of different data sources and analyzed data. The framework is available in a Platform as a Service (PaaS) model and has been applied for the vehicle, health, production lines, and smart city domains.

Developments and challenges ahead in smart city frameworks - lessons from SmartSantander

The domain of smart cities is currently burgeoning, with a lot of potential for scientific and socio-economic innovation gradually being revealed. It is also becoming apparent that cross-discipline research will be instrumental in designing and building smarter cities, where IoT technology is becoming omnipresent. SmartSantander is an FP7 project that built a massive city-scale IoT testbed aiming to provide both a tool for the research community and a functional system for the local government to implement operational city services. In this work, we present key smart cities projects, main application domains and representative smart city frameworks that reflect the latest advances in the smart cities domain and our own experience through SmartSantander. The project has deployed 51.910 IoT endpoints, offering a massive infrastructure to the community, as well as functional system services and a number of end-user applications. Based on these aspects, we identify and discuss a number of key scientific and technological challenges. We also present an overview of the developed system components and applications, and discuss the ways that current smart city challenges were handled in the project.

A vision of social media in the Spanish smartest cities

Purpose– The purpose of this study is to analyse whether it is the Spanish urban environments that can be considered smart cities that are making the greatest efforts to ensure that citizens have better access to city information and, thus, participate to a greater degree in its governance.Design/methodology/approach– This analysis of the use made of social networks, as an integral part of democratisation, is divided into two phases: first, a descriptive study was made of the cities’ use of their social networks; we then examined, by multiple linear regression analysis, whether the urban areas classed as smart cities are those that make more or less use or application of social networks.Findings– Although, in general terms, the “smartest” smart cities are those which obtain the best overall results in terms of social networks, further improvements are needed, especially in the field of activity and interaction with citizens via these networks.Originality/value– The impact made by social media is one of the emerging research themes in the domain of smart cities, e-government and their information policies. Nevertheless, few studies have examined whether the smart cities are also those whose governments have achieved a greater degree of citizen participation through social networks. Therefore, this study contributes to our understanding of the importance of social media in the local government context, by establishing a relationship between democratic participation, through Facebook and Twitter, and the development of smart cities.

On the application of Big Data in future large-scale intelligent Smart City installations

Purpose – The purpose of this article is to propose and evaluate a novel system architecture for Smart City applications which uses ontology reasoning and a distributed stream processing framework on the cloud. In the domain of Smart City, often methodologies of semantic modeling and automated inference are applied. However, semantic models often face performance problems when applied in large scale. Design/methodology/approach – The problem domain is addressed by using methods from Big Data processing in combination with semantic models. The architecture is designed in a way that for the Smart City model still traditional semantic models and rule engines can be used. However, sensor data occurring at such Smart Cities are pre-processed by a Big Data streaming platform to lower the workload to be processed by the rule engine. Findings – By creating a real-world implementation of the proposed architecture and running simulations of Smart Cities of different sizes, on top of this implementation, the authors found that the combination of Big Data streaming platforms with semantic reasoning is a valid approach to the problem. Research limitations/implications – In this article, real-world sensor data from only two buildings were extrapolated for the simulations. Obviously, real-world scenarios will have a more complex set of sensor input values, which needs to be addressed in future work. Originality/value – The simulations show that merely using a streaming platform as a buffer for sensor input values already increases the sensor data throughput and that by applying intelligent filtering in the streaming platform, the actual number of rule executions can be limited to a minimum.

Approach to Manage Complexity in Internet of Things

Complexity research is a main concern in disparate science fields such as computing, city planning, Internet, etc. In computing and programming, complexity became early an issue and a target for software engineering, but in fact the pattern concept was born in architecture and city planning environment. The universe is not made of “things,” but of patterns of complex and interactive geometries. In this paper, we generalize such a concept to Internet of Things and Smart Cities domain and consider more complex abstract structures called semi lattices. Furthermore, an approach to model them is proposed.