Fraunhofer-Institut für Angewandte Informationstechnik FIT

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  • Publication
    IoT solutions for large open-air events
    ( 2020)
    Sottile, F.
    ;
    Foglietti, J.
    ;
    Pastrone, C.
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    Spirito, M.A.
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    Defina, A.
    ;
    Eisenhauer, M.
    ;
    Devasya, S.
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    Schoneveld, A.
    ;
    Frey, N.
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    Pierre-Yves, H.
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    Remagnino, P.
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    Oghaz, M.M.
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    Haddad, K.
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    Kouzinopoulos, C.S.
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    Stavropoulos, G.
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    Munoz, P.
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    Carra, S.
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    Kool, P.
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    Rosengren, P.
    This chapter presents the main results of the MONICA project, one of the five large-scale pilot projects funded by the European Commission. MONICA focuses on the adoption of wearable IoT solutions for the management of safety and security in large open-air events as well as on the reduction of noise level for neighbours. The project addresses several challenges in eleven pilots of six major European cities using a large number of IoT wearables and sensors. The chapter first introduces all MONICA challenges in the context of large open-air events and then presents the corresponding adopted technical solutions, the defined IoT architecture and the perspective in integrating a wide range of heterogeneous sensors. On one side, the focus is on the solutions that have been adopted to improve the crowd management, crowd safety and emergency responses by using wearables for both visitors and the security staff at the events, including also the adoption of video processing and d ata fusion algorithms to estimate the number of visitors and its distribution in the event area and to detect suspicious activity patterns. On the other hand, it describes how innovative Sound Level Meters (SLMs) can be deployed to monitor the sound propagation within the event area while reducing the noise impact on the neighbourhood. © 2020 River Publishers. All rights reserved.
  • Publication
    Smart data and the industrial internet of things
    ( 2018)
    Beecks, C.
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    Rasheed, H.
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    Grass, A.
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    Devasya, S.
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    Jentsch, M.
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    Soto, J.A.C.
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    Tavakolizadeh, F.
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    Linnemann, A.
    ;
    Eisenhauer, M.
    Many modern production processes are nowadays equipped with cyber-physical systems in order to capture, manage, and process large amounts of sensor data including information about machines, processes, and products. The proliferation of cyber-physical systems (CPS) and the advancement of Internet of Things (IoT) technologies have led to an explosive digitization of the industrial sector. Driven by the high-tech strategy of the federal government in Germany, many manufacturers across all industry segments are accelerating the adoption of cyber-physical system and IoT technologies to gain actionable insight into their industrial production processes and finally improve their processes by means of data-driven methodology. In this work, we aim to give insights into our recent research regarding the domains of Smart Data and Industrial Internet of Things (IIoT). To this end, we are focusing on the EU projects MONSOON and COMPOSITION as examples for the Public-Private Partnership (PPP) initiatives Factories of the Future (FoF) and Sustainable Process Industry (SPIRE) and show how to approach data analytics via scalable and agile analytic platforms. Along these analytic platforms, we provide an overview of our recent Smart Data activities and exemplify data-driven analysis of industrial production processes from the process and manufacturing industries.
  • Publication
    The next generation internet of things - Hyperconnectivity and embedded intelligence at the edge
    ( 2018)
    Vermesan, O.
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    Eisenhauer, M.
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    Serrano, M.
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    Guillemin, P.
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    Sundmaeker, H.
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    Tragos, E.Z.
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    Valino, J.
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    Copigneaux, B.
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    Presser, M.
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    Aagaard, A.
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    Bahr, R.
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    Darmois, E.C.
    The Internet of Things (IoT) and the Industrial Internet of Things (IIoT) are evolving towards the next generation of Tactile IoT/IIoT, which will bring together hyperconnectivity, edge computing, Distributed Ledger Technologies (DLTs) and Artificial Intelligence (AI). Future IoT applications will apply AI methods, such as machine learning (ML) and neural networks (NNs), to optimize the processing of information, as well as to integrate robotic devices, drones, autonomous vehicles, augmented and virtual reality (AR/VR), and digital assistants. These applications will engender new products, services and experiences that will offer many benefits to businesses, consumers and industries. A more human-centred perspective will allow us to maximise the effects of the next generation of IoT/IIoT technologies and applications as we move towards the integration of intelligent objects with social capabilities that need to address the interactions between autonomous systems and humans in a seamless way.
  • Publication
    IoT European Large-Scale Pilots
    ( 2017)
    Guillén, S.G.
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    Sala, P.
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    Fico, G.
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    Arredondo, M.T.
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    Cano, A.
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    Posada, J.
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    Gutierrez, G.
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    Palau, C.
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    Votis, K.
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    Verdouw, C.N.
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    Wolfert, S.
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    Beers, G.
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    Sundmaeker, H.
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    Chatzikostas, G.
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    Ziegler, S.
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    Hemmens, C.
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    Holst, M.
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    Ståhlbröst, A.
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    Scudiero, L.
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    Reale, C.
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    Krco, S.
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    Drajic, D.
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    Eisenhauer, M.
    ;
    Jahn, M.
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    Valino, J.
    ;
    Gluhak, A.
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    Brynskov, M.
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    Vermesan, O.
    ;
    Fischer, F.
    ;
    Lenz, O.
    The IoT European Large-Scale Pilots Programme includes the innovation consortia that are collaborating to foster the deployment of IoT solutions in Europe through the integration of advanced IoT technologies across the value chain, demonstration of multiple IoT applications at scale and in a usage context, and as close as possible to operational conditions. The programme projects are targeted, goal-driven initiatives that propose IoT approaches to specific real-life industrial/societal challenges. They are autonomous entities that involve stakeholders from the supply side to the demand side, and contain all the technological and innovation elements, the tasks related to the use, application and deployment as well as the development, testing and integration activities. This chapter describes the IoT Large Scale Pilot Programme initiative together with all involved actors. These actors include the coordination and support actions CREATE-IoT and U4IoT, being them drivers of the programme, and all five IoT Large-Scale Pilot projects, namely ACTIVAGE, IoF2020, MONICA, SynchroniCity and AUTOPILOT.
  • Publication
    Internet of Things beyond the Hype: Research, innovation and deployment
    ( 2015)
    Vermesan, O.
    ;
    Friess, P.
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    Guillemin, P.
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    Giaffreda, R.
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    Grindvoll, H.
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    Eisenhauer, M.
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    Serrano, M.
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    Moessner, K.
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    Spirito, M.
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    Blystad, L.-C.
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    Tragos, E.Z.
  • Publication
    SEAM4US
    ( 2014)
    Simon, J.
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    Jentsch, M.
    ;
    Eisenhauer, M.
  • Publication
    Prototyping the Internet of Things for the Future Factory Using a SOA-based Middleware and reliable WSNs
    ( 2013)
    Pramudianto, Ferry
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    Simon, J.
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    Eisenhauer, M.
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    Khaleel, H.
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    Pastrone, C.
    ;
    Spirito, M.
    In this paper, we describe a SOA-based middleware to integrate Internet-of-Things technologies in industrial setups. The middleware allows a seamless horizontal integration among heterogeneous technologies and vertical integration with applications and business systems. Using the middleware, we evaluated an approach to improve the reliability of 6LoWPAN-based sensor networks with self-configuration and self-healing capabilities to support an innovative monitoring and control framework in a manufacturing line. The sensor networks were evaluated in a test bed consisting of various physical devices that emulates a welding station.
  • Publication
    MICA: A mobile support system for warehouse workers
    ( 2013)
    Prause, C.R.
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    Jentsch, M.
    ;
    Eisenhauer, M.
    Thousands of small and medium-sized companies world-wide have non-automated warehouses. Picking orders are manually processed by blue-collar workers; however, this process is highly error-prone. There are various kinds of picking errors that can occur, which cause immense costs and aggravate customers. Even experienced workers are not immune to this problem. In turn, this puts a high pressure on the warehouse personnel. In this paper, the authors present a mobile assistance system for warehouse workers that realize the new Interaction-by-Doing principle. MICA unobtrusively navigates the worker through the warehouse and effectively prevents picking errors using RFID. In a pilot project at a medium-sized enterprise the authors evaluate the usability, efficiency, and sales potential of MICA. Findings show that MICA effectively reduces picking times and error rates. Consequentially, job training periods are shortened, while at the same time pressure put on the individual wo rker is reduced. This leads to lower costs for warehouse operators and an increased customer satisfaction.
  • Publication
    MICA: A mobile support system for warehouse workers
    ( 2011)
    Prause, C.
    ;
    Jentzsch, A.
    ;
    Eisenhauer, M.
    Thousands of small- and medium-sized companies world-wide have non-automated warehouses. Picking orders are manually processed by blue-collar workers. However, this process is highly error-prone. There are various kinds of picking errors that can occur. These cause immense costs and aggravate customers, too. Even experienced workers are not immune to this problem. In turn, this puts a high pressure on the warehouse personnel. We present a mobile assistance system for warehouse workers that realizes the new Interaction-by-Doing principle. MICA unobtrusively navigates the worker through the warehouse and effectively prevents picking errors using RFID. In a pilot project at a medium-sized enterprise we evaluate the usability, efficiency and sales potential of MICA. We find that MICA effectively reduces picking times and error rates. Consequentially, job training periods are shortened, while at the same time pressure put on the individual worker is reduced. This leads to lower costs for warehouse operators and an increased customer satisfaction.
  • Publication
    Middleware for wireless devices and sensors
    ( 2010)
    Eisenhauer, M.
    ;
    Prause, C.
    ;
    Jahn, M.
    ;
    Jentsch, M.
    The HYDRA project develops middleware for networked embedded systems that allows developers to create ambient intelligence applications based on wireless devices and sensors. Through its unique combination of Service-oriented Architecture (SoA) and a semantic-based Model Driven Architecture, HYDRA will enable the development of generic services based on open standards. A smart home application is built that facilitates intelligent communication of heterogeneous embedded devices through an overlay P2P network. We interconnect common devices available in private households and integrate wireless power metering plugs to gain access to energy consumption data. These data are used for monitoring and analyzing consumed energy on device level in near real-time.