2,522 research outputs found

    Supporting Cyber-Physical Systems with Wireless Sensor Networks: An Outlook of Software and Services

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    Sensing, communication, computation and control technologies are the essential building blocks of a cyber-physical system (CPS). Wireless sensor networks (WSNs) are a way to support CPS as they provide fine-grained spatial-temporal sensing, communication and computation at a low premium of cost and power. In this article, we explore the fundamental concepts guiding the design and implementation of WSNs. We report the latest developments in WSN software and services for meeting existing requirements and newer demands; particularly in the areas of: operating system, simulator and emulator, programming abstraction, virtualization, IP-based communication and security, time and location, and network monitoring and management. We also reflect on the ongoing efforts in providing dependable assurances for WSN-driven CPS. Finally, we report on its applicability with a case-study on smart buildings

    Tool Support for Design Science Research—Towards a Software Ecosystem: A Report from a DESRIST 2017 Workshop

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    The information systems (IS) field contains a rich body of knowledge on approaches, methods, and frameworks that supports researchers in conducting design science research (DSR). It also contains some consensus about the key elements of DSR projects—such as problem identification, design, implementation, evaluation, and abstraction of design knowledge. Still, we lack any commonly accepted tools that address the needs of DSR scholars who seek to structure, manage, and present their projects. Indeed, DSR endeavors, which are often complex and multi-faceted in nature and involve various stakeholders (e.g., researchers, developers, practitioners, and others), require the support that such tools provide. Thus, to investigate the tools that DSR scholars actually need to effectively and efficiently perform their work, we conducted an open workshop with DSR scholars at the 2017 DESRIST conference in Karlsruhe, Germany, to debate 1) the general requirement categories of DSR tool support and 2) the more specific requirements. This paper reports on the results from this workshop. Specifically, we identify nine categories of requirements that fall into the three broad phases (pre-design, design, and post design) and that contribute to a software ecosystem for supporting DSR endeavors

    Logic-based Technologies for Multi-agent Systems: A Systematic Literature Review

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    Precisely when the success of artificial intelligence (AI) sub-symbolic techniques makes them be identified with the whole AI by many non-computerscientists and non-technical media, symbolic approaches are getting more and more attention as those that could make AI amenable to human understanding. Given the recurring cycles in the AI history, we expect that a revamp of technologies often tagged as “classical AI” – in particular, logic-based ones will take place in the next few years. On the other hand, agents and multi-agent systems (MAS) have been at the core of the design of intelligent systems since their very beginning, and their long-term connection with logic-based technologies, which characterised their early days, might open new ways to engineer explainable intelligent systems. This is why understanding the current status of logic-based technologies for MAS is nowadays of paramount importance. Accordingly, this paper aims at providing a comprehensive view of those technologies by making them the subject of a systematic literature review (SLR). The resulting technologies are discussed and evaluated from two different perspectives: the MAS and the logic-based ones

    Automated Transit Networks (ATN): A Review of the State of the Industry and Prospects for the Future, MTI Report 12-31

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    The concept of Automated Transit Networks (ATN) - in which fully automated vehicles on exclusive, grade-separated guideways provide on-demand, primarily non-stop, origin-to-destination service over an area network – has been around since the 1950s. However, only a few systems are in current operation around the world. ATN does not appear “on the radar” of urban planners, transit professionals, or policy makers when it comes to designing solutions for current transit problems in urban areas. This study explains ATN technology, setting it in the larger context of Automated Guideway Transit (AGT); looks at the current status of ATN suppliers, the status of the ATN industry, and the prospects of a U.S.-based ATN industry; summarizes and organizes proceedings from the seven Podcar City conferences that have been held since 2006; documents the U.S./Sweden Memorandum of Understanding on Sustainable Transport; discusses how ATN could expand the coverage of existing transit systems; explains the opportunities and challenges in planning and funding ATN systems and approaches for procuring ATN systems; and concludes with a summary of the existing challenges and opportunities for ATN technology. The study is intended to be an informative tool for planners, urban designers, and those involved in public policy, especially for urban transit, to provide a reference for history and background on ATN, and to use for policy development and research

    What constitutes a machine-learning-driven business model? A taxonomy of B2B start-ups with machine learning at their core

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    Artificial intelligence, specifically machine learning (ML), technologies are powerfully driving business model innovation in organizations against the backdrop of increasing digitalization. The resulting novel business models are profoundly shaped by ML, a technology that brings about unique opportunities and challenges. However, to date, little research examines what exactly constitutes these business models that use ML at their core and how they can be distinguished. Therefore, this study aims to contribute to an increased understanding of the anatomy of ML-driven business models in the business-to-business segment. To this end, we develop a taxonomy that allows researchers and practitioners to differentiate these ML-driven business models according to their characteristics along ten dimensions. Additionally, we derive archetypes of ML-driven business models through a cluster analysis based on the characteristics of 102 start-ups from the database Crunchbase. Our results are cross-industry, providing fertile soil for expansion through future investigations

    Method Engineering as Design Science

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    In this paper, we motivate, devise, demonstrate, and evaluate an approach for the research-based development of information systems development methods (ISDMs). This approach, termed “method engineering as design science” (ME-DS), emerged from the identified need for scholars to develop ISDMs using proper research methods that meet the standards of both rigor and relevance. ISDMs occupy a position of central importance to information systems development and scholars have therefore invested extensive resources over the years in developing such methods. The method engineering (ME) discipline has developed different frameworks and methods to guide such development work and, for that purpose, they are well-suited. Still, there remains a need for applications and evaluations of ISDMs based on the demands for knowledge justification. Unfortunately, in many cases, scholars come up short with regard to how ISDMs are generated and empirically validated. While design science (DS) stresses knowledge justification, prominent DS approaches seem to be biased toward the development of IT artifacts, making this approach ill-suited for the development of method artifacts. We therefore propose eight principles that marry ME and DS, resulting in a process model with six activities to support research-based development of ISDMs. We demonstrate and evaluate ME-DS by assessing three existing research papers that propose ISDMs. These retrospectives show how ME-DS directs attention to certain aspects of the research process and provides support for future ISDM development

    ERP implementation methodologies and frameworks: a literature review

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    Enterprise Resource Planning (ERP) implementation is a complex and vibrant process, one that involves a combination of technological and organizational interactions. Often an ERP implementation project is the single largest IT project that an organization has ever launched and requires a mutual fit of system and organization. Also the concept of an ERP implementation supporting business processes across many different departments is not a generic, rigid and uniform concept and depends on variety of factors. As a result, the issues addressing the ERP implementation process have been one of the major concerns in industry. Therefore ERP implementation receives attention from practitioners and scholars and both, business as well as academic literature is abundant and not always very conclusive or coherent. However, research on ERP systems so far has been mainly focused on diffusion, use and impact issues. Less attention has been given to the methods used during the configuration and the implementation of ERP systems, even though they are commonly used in practice, they still remain largely unexplored and undocumented in Information Systems research. So, the academic relevance of this research is the contribution to the existing body of scientific knowledge. An annotated brief literature review is done in order to evaluate the current state of the existing academic literature. The purpose is to present a systematic overview of relevant ERP implementation methodologies and frameworks as a desire for achieving a better taxonomy of ERP implementation methodologies. This paper is useful to researchers who are interested in ERP implementation methodologies and frameworks. Results will serve as an input for a classification of the existing ERP implementation methodologies and frameworks. Also, this paper aims also at the professional ERP community involved in the process of ERP implementation by promoting a better understanding of ERP implementation methodologies and frameworks, its variety and history

    2007-2011

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