An Architecture for Integrated Intelligence in Urban Management using Cloud Computing

With the emergence of new methodologies and technologies it has now become possible to manage large amounts of environmental sensing data and apply new integrated computing models to acquire information intelligence. This paper advocates the application of cloud capacity to support the information, communication and decision making needs of a wide variety of stakeholders in the complex business of the management of urban and regional development. The complexity lies in the interactions and impacts embodied in the concept of the urban-ecosystem at various governance levels. This highlights the need for more effective integrated environmental management systems. This paper offers a user-orientated approach based on requirements for an effective management of the urban-ecosystem and the potential contributions that can be supported by the cloud computing community. Furthermore, the commonality of the influence of the drivers of change at the urban level offers the opportunity for the cloud computing community to develop generic solutions that can serve the needs of hundreds of cities from Europe and indeed globally.Comment: 6 pages, 3 figure

(De)convergence in TV: a comparative analysis of the development of Smart TV

Against the backdrop of media convergence, Smart TVs are developing rapidly in large parts of the world. Smart TV refers to the integration of broadband Internet and social media features into TV sets. From a media business perspective, the proliferation of Smart TV services may put pressure on the market structure of the TV landscape, and urge for new business models in order to capture the dynamics of media convergence. By means of a comparative analysis in four European markets (Belgium, Germany, the Netherlands and the United Kingdom), the development of Smart TV is sketched in terms of viewing patterns, business models and standardization. The conclusion is that national TV markets are evolving quite differently, so that service providers must adapt their marketing strategies to reflect local market conditions. Hence, the success of Smart TV ultimately depends on the local package of value-added services and the amount of strategic partnerships with content owners, TV broadcasters and pay-TV operators

Internet of things

Manual of Digital Earth / Editors: Huadong Guo, Michael F. Goodchild, Alessandro Annoni .- Springer, 2020 .- ISBN: 978-981-32-9915-3Digital Earth was born with the aim of replicating the real world within the digital world. Many efforts have been made to observe and sense the Earth, both from space (remote sensing) and by using in situ sensors. Focusing on the latter, advances in Digital Earth have established vital bridges to exploit these sensors and their networks by taking location as a key element. The current era of connectivity envisions that everything is connected to everything. The concept of the Internet of Things(IoT)emergedasaholisticproposaltoenableanecosystemofvaried,heterogeneous networked objects and devices to speak to and interact with each other. To make the IoT ecosystem a reality, it is necessary to understand the electronic components, communication protocols, real-time analysis techniques, and the location of the objects and devices. The IoT ecosystem and the Digital Earth (DE) jointly form interrelated infrastructures for addressing today’s pressing issues and complex challenges. In this chapter, we explore the synergies and frictions in establishing an efficient and permanent collaboration between the two infrastructures, in order to adequately address multidisciplinary and increasingly complex real-world problems. Although there are still some pending issues, the identified synergies generate optimism for a true collaboration between the Internet of Things and the Digital Earth

Internet of robotic things : converging sensing/actuating, hypoconnectivity, artificial intelligence and IoT Platforms

The Internet of Things (IoT) concept is evolving rapidly and influencing newdevelopments in various application domains, such as the Internet of MobileThings (IoMT), Autonomous Internet of Things (A-IoT), Autonomous Systemof Things (ASoT), Internet of Autonomous Things (IoAT), Internetof Things Clouds (IoT-C) and the Internet of Robotic Things (IoRT) etc.that are progressing/advancing by using IoT technology. The IoT influencerepresents new development and deployment challenges in different areassuch as seamless platform integration, context based cognitive network integration,new mobile sensor/actuator network paradigms, things identification(addressing, naming in IoT) and dynamic things discoverability and manyothers. The IoRT represents new convergence challenges and their need to be addressed, in one side the programmability and the communication ofmultiple heterogeneous mobile/autonomous/robotic things for cooperating,their coordination, configuration, exchange of information, security, safetyand protection. Developments in IoT heterogeneous parallel processing/communication and dynamic systems based on parallelism and concurrencyrequire new ideas for integrating the intelligent “devices”, collaborativerobots (COBOTS), into IoT applications. Dynamic maintainability, selfhealing,self-repair of resources, changing resource state, (re-) configurationand context based IoT systems for service implementation and integrationwith IoT network service composition are of paramount importance whennew “cognitive devices” are becoming active participants in IoT applications.This chapter aims to be an overview of the IoRT concept, technologies,architectures and applications and to provide a comprehensive coverage offuture challenges, developments and applications

Streamlining governmental processes by putting citizens in control of their personal data

Governments typically store large amounts of personal information on their citizens, such as a home address, marital status, and occupation, to offer public services. Because governments consist of various governmental agencies, multiple copies of this data often exist. This raises concerns regarding data consistency, privacy, and access control, especially under recent legal frameworks such as GDPR. To solve these problems, and to give citizens true control over their data, we explore an approach using the decentralised Solid ecosystem, which enables citizens to maintain their data in personal data pods. We have applied this approach to two high-impact use cases, where citizen information is stored in personal data pods, and both public and private organisations are selectively granted access. Our findings indicate that Solid allows reshaping the relationship between citizens, their personal data, and the applications they use in the public and private sector. We strongly believe that the insights from this Flemish Solid Pilot can speed up the process for public administrations and private organisations that want to put the users in control of their data