The Fourth Industrial Revolution has become a global buzz word since the World Economic Forum adopted it as an annual issue in 2016. It is represented by hyper automation and hyper connectivity based on artificial intelligence, big data, robotics, and Internet of things. AI, big data, and robotics can contribute to developing hyper automation that can increase productivity and intensify industrial production. Particularly, robots using AI can make decision by themselves as human being on complicated processes. Along with the hyper (...) automation, the hyper connectivity increases not only at national, but also global level by using information and communication technologies. IoT is the core technology to create the hyper connectivity in Cyber Physical System that connects technology, nature, and human being. Accordingly, a perfect convergence between ICT and manufacturing can be completed in the Fourth Industrial Revolution era and an extremely efficient flexible production system by spreading IoT in CPS will be established. Under such a condition, innovative clusters must play their traditional roles in cradles of technology innovation and commercialization. It must be difficult challenges for innovative clusters to meet their targets and to be adjusted by the changing new environment at the same time. This paper argues how the Fourth Industrial Revolution can change the global production chain and how core technologies function in industries. Furthermore, it focuses on how innovative clusters have to evolve to respond the Fourth Industrial Revolution. Last, but not least it also analyzes whether or not innovative clusters can play their roles as technology innovation hubs in the real world and CPS in the Fourth Industrial Revolution era. (shrink)

In this paper, it is argued that although data mining (DM) is being touted as a solution to many business problems and is basking in the glory of electronic business environments of today, as practiced currently, it reflects a preoccupation with short-run commercial applications and a neglect of the underlying theoretical issues. Although an argument can be made that theoretical precedence is not a necessary prerequisite for practical application or for commercial success, it can also be argued that an exclusive (...) reliance on data-driven and exploratory components of pattern recognition without a corresponding attention to the causal schemas underlying patterns is destined to limit the potential for DM to evolve into a long-term solution to business problems or into an intellectual discipline in its own right. This paper presents an overview of key features and assumptions in DM and examines some of the key practical, philosophical, and foundational issues in DM. (shrink)

IoT connects devices, humans, places, and even abstract items like events. Driven by smart sensors, powerful embedded microelectronics, high-speed connectivity and the standards of the internet, IoT is on the brink of disrupting today’s value chains. Big Data, characterized by high volume, high velocity and a high variety of formats, is a result of and also a driving force for IoT. The datafication of business presents completely new opportunities and risks. To hedge the technical risks posed by the interaction between (...) “everything”, IoT requires comprehensive modelling tools. Furthermore, new IT platforms and architectures are necessary to process and store the unprecedented flow of structured and unstructured, repetitive and non-repetitive data in real-time. In the end, only powerful analytic tools are able to extract “sense” from the exponentially growing amount of data and, as a consequence, data science becomes a strategic asset. The era of IoT relies heavily on standards for technologies which guarantee the interoperability of everything. This paper outlines some fundamental standardization activities. Big Data approaches for real-time processing are outlined and tools for analytics are addressed. As consequence, IoT is a evolutionary process whose success in penetrating all dimensions of life heavily depends on close cooperation between standardization organizations, open source communities and IT experts. (shrink)

In a modern, calculative world, the techniques of tracking are everywhere in the ascendant. Enhanced by algorithmic procedures and analytics, they have been incorporated into distributed network systems, augmented by new sensing and locationing technologies, and embedded into mobile devices, urban structures and environments. Simultaneously, new practices of tracking and sensing have emerged across the consumer, state and corporate sectors. These practices are amplified in the case of megacities as they strive to keep pace with rapid urban development. All movement (...) is subordinated to a condition of 'calculative mobilization’, whereby the urban realm is understood through the spatialization of algorithmic operations. And yet, due to their unique large- and multi-scaled accumulations of data-enhanced actors and their complex, stratified modes of proximity and interoperable relationality, the particular densities of megacities challenge conventional spatial formats of movement and positioning. This article offers new formats of analysis for these calculative practices and the agential and ontological status of the hybrid urban entities that they register and engender. It also offers new structuring principles and political orientations, which are particularly urgent as we witness the ascendance of 'Spatial Data Infrastructures’ that are often promoted as participatory and inclusive while remaining largely inaccessible, pursuing proprietary aims, and infused with the potential not only to protect and inform but also to violate. (shrink)

Recent changes in service environments have changed the preconditions of their production and consumption. These changes include unbundling services from production processes, growth of the information-rich economy and society, the search for creativity in service production and consumption and continuing growth of digital technologies. These contextual changes affect city governments because they provide a range of infrastructure and welfare services to citizens. Concepts such as ‘smart city’, ‘intelligent city’ and ‘knowledge city’ build new horizons for cities in undertaking their challenging (...) service functions in an increasingly cost-conscious, competitive and environmentally oriented setting. What is essential in practically all of them is that they paint a picture of cities with smooth information processes, facilitation of creativity and innovativeness, and smart and sustainable solutions promoted through service platforms. This article discusses this topic, starting from the nature of services and the new service economy as the context of smart local public services. On this basis, we build an overall framework for understanding the basic forms and dimensions of smart public services. The focus is on conceptual systematisation of the key dimensions of smart services and the conceptual modelling of smart service platforms through which digital technology is increasingly embedded in social creativity. We provide examples of real-life smart service applications within the European context. (shrink)