Conceptual Framework for Appling Internet of Things in Production Systems for Sensing Enterprises

Sensing Enterprise is a new concept, which appears with the Internet of Things (IoT) application in industry. This technology applied in production systems provides many benefits like better transparency or real time information. This approach proposes a conceptual framework for IoT application in Production Systems. The aim of this framework is helping enterprises to identify the main elements to apply IoT in Production Systems. To create this framework, a literature re-view has been made and the main components of IoT in Sensing Enterprise in production proposals have been identify. Thus, these elements and its relations have been the source for the conceptual framework proposed.Boza, A.; Cortés-Santamaría, B.; Alemany Díaz, MDM.; Cuenca, L. (2016). Conceptual Framework for Appling Internet of Things in Production Systems for Sensing Enterprises. Brazilian Journal of Operations and Production Management. 13(1):66-71. doi:10.14488/BJOPM.2016.v13.n1.a7S667113

Towards Sensing Information Systems

Recent advances in the field of pervasive computing, including the approaches and technologies related to Wireless Sensor Networks (WSN), Internet of Things (IoT) and Cyber Physical Systems (CPS) are changing the way we perceive computing capability. Although the scientific communities have already started to discuss about the visionary concepts that will exploit these advances, such as Sensing and Liquid Enterprise, the truly smart and interoperable CPS networks are still confined to the ‘valley of death’ - between prototyping and mass-production. In this position paper, we propose the concept of Sensing Information System, a novel paradigm that will facilitate the transformation of CPS to Cyber Physical Ecosystems - borderless technical environments in which the devices will become capable to sense, perceive, decide and act, based on the external, common behavioural and context models. A case study is used to demonstrating the use of Sensing Information Systems for extended clinical workflows

Towards the development of the framework for inter sensing enterprise architecture

[EN] Inter-enterprise architecture (IEA) is a new concept that seeks to apply the tools and methodologies of enterprise architecture (EA) in a collaborative context, in order to model collaborative organizations in an inclusive manner. According to the main enterprise architectures proposed to this point, an EA should be conformed at least for a framework, a methodology and a modelling language. Sensing enterprise (SE) is an attribute of an enterprise or a network that allows it to react to business stimuli originating on the Internet. These fields have come into focus recently, and there is not evidence of the use of IEA for modelling a SE, while finding an interesting gap to work on. Thus, this paper proposes an initial framework for inter sensing enterprise architecture (FISEA), which seeks to classify, organize, store and communicate, at the conceptual level, all the elements for inter-sensing enterprise architectures and their relationships, ensuring their consistency and integrity. This FISEA provides a clear idea about the elements and views that create collaborative network and their inter-relationships, based on the support of Future Internet.This work was supported by the European Commission FP7 UNITE Project, through its Secondment Programme and the Universitat Politecnica de Valencia ADENPRO-PJP project (ref. SP20120703).Vargas, A.; Cuenca, L.; Boza, A.; Sacala, I.; Moisescu, M. (2016). Towards the development of the framework for inter sensing enterprise architecture. Journal of Intelligent Manufacturing. 27(1):55-72. https://doi.org/10.1007/s10845-014-0901-zS5572271Adaba, G., Rusu, L., & Mekawy, M. (2010). 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Reingeniería del proceso productivo empresarial mediante la incorporación de propuestas del campo de internet de las cosas

[ES] Nuevas tecnologías afectan a los sistemas empresariales. Una de estas tendencias se dirige hacia el concepto de empresa sensible (Sensing Enterprise), donde la empresa recibe información en tiempo real sobre su entorno, un entorno que es "global" por la naturaleza (mediante tweets, sensores de información, RFID o GPS como ejemplos) y alimenta constantemente su proceso de toma de decisiones, pudiendo este estar controlado por los "sujetos" (es decir, los seres humanos), o por los "objetos" (es decir, varios tipos de artefactos ¿things¿ habilitados). Así, nuevas aplicaciones en este ámbito permiten aumentar la sensibilidad al contexto global y físico de los sistemas de negocio. El objetivo que se persigue es mejorar el proceso de planificación de la producción mediante la incorporación de las nuevas tecnologías que estan surgiendo el campo de ¿sensing enterprises¿ e ¿Internet of Things¿ para la mejora de la toma de decisiones en el ámbito productivo.[EN] New technologies affecting business systems. One of these trends is directed towards the concept of sensitive company (Sensing Enterprise), where the company receives real-time information about their environment, an environment that is "global" by nature (through tweets or sensory information, such as RFID or GPS) and constantly feeds its decisionmaking process. This Decision making process can be controlled by “individuals” (ie humans) or objects (that is, various kinds of devices “things” enabled). Thus, new applications in this field allow more sensitive to the physical context of global business systems. The objective pursued is to improve the planning of production by incorporating new technologies emerging field “sensing enterprises” and “Internet of Things” to improve decision making in the production area.Climent Pascual, R. (2015). Reingeniería del proceso productivo empresarial mediante la incorporación de propuestas del campo de internet de las cosas. http://hdl.handle.net/10251/54028.TFG

Ontology-based model-driven patterns for notification-oriented data-intensive enterprise information systems

International audienceIn the fourth industrial revolution, the current Enterprise Information Systems (EIS) are facing a set of new challenges raised by the applications of Cyber-Physical Systems (CPS) and Internet of Things (IoT). In this scenario, a data-intensive EIS involves networks of physical objects with sensing, data collection, transmission and actuation capabilities, and vast endpoints in the cloud, thereby offering large amounts of data. Such systems can be considered as a multidisciplinary complex system with strong interrelations between the involved components. In order to cope with the big heterogeneousness of those physical objects and their intrinsic information, the authors propose a notification-based approach derived from the so-called Notification Oriented Paradigm (NOP), a new rule and event driven approach for software and hardware specification and execution. However, the heterogeneity of those information and their interpretation relatively to an evolving context impose the definition of model-driven patterns based on some formal knowledge modelled by a set of skill-based ontologies. Thus, the paper focuses on the open issue related to the formalisation of such ontology-based patterns for their verification, ensuring the coherence of the whole set of data in each contextual engineering domain involved in the EIS

Special section Industry 4.0: Challenges for the future in manufacturing

International audienceThe sensing enterprise is a digital business innovation concept making Cyber-Physical Systems, service-oriented architectures and advanced human-computer interactions converge, supporting a more agile, flexible, and proactive management of unexpected events in today’s global value networks. In essence, it concerns the adoption of future Internet technologies in virtual enterprises. Translating this concept to a general approach to smart systems (smart manufacturing, smart cities, smart logistics, etc.), requires new capabilities by next-generation information systems to perform sensing, modelling, and interpretation of “any” signal from the real world, thus providing the systems with higher flexibility and possibilities for reconfiguration (Panetto et al. 2016). Intuitively, a sensing system requires resources and machineries to be constantly monitored, configured, and easily controlled by human operators. All these functions, and much more indeed, are now implemented by the so-called (Industrial) Internet of Things or Cyber-Physical Systems. With the advent of the new cyber-physical system design paradigm, the number and diversity of systems that need to work together in the future enterprises have significantly increased (Weichhart et al. 2016). This trend highlights the need to shift from the classic central control of systems, towards systems interoperability as a capability to control, sense, and perceive distributed and heterogeneous systems and their environments, as well as to purposefully and socially act upon their perceptions. Such a shift could have important consequences on the future architecture design of the control of these systems. The emergence of cloud-based technologies will also have a significant impact on the design and implementation of cyber-physical systems; using such novel technologies, collaborative engineering practises will increase globally, thus enabling a new generation of small-scale industrial organizations to function in an information-centric manner and enabling industry 4.0 transformations (Cimini, et al, 2017). The potential of such technologies in fostering a leaner and more agile approach towards engineering is very high. Engineers and engineering organizations no longer have to be restricted to the availability of advanced processing capabilities, as they can adopt a ‘pay as you go’ approach, which will enable them to access and use software resources for engineering activities from any remote location in the world

End-to-End Privacy for Open Big Data Markets

The idea of an open data market envisions the creation of a data trading model to facilitate exchange of data between different parties in the Internet of Things (IoT) domain. The data collected by IoT products and solutions are expected to be traded in these markets. Data owners will collect data using IoT products and solutions. Data consumers who are interested will negotiate with the data owners to get access to such data. Data captured by IoT products will allow data consumers to further understand the preferences and behaviours of data owners and to generate additional business value using different techniques ranging from waste reduction to personalized service offerings. In open data markets, data consumers will be able to give back part of the additional value generated to the data owners. However, privacy becomes a significant issue when data that can be used to derive extremely personal information is being traded. This paper discusses why privacy matters in the IoT domain in general and especially in open data markets and surveys existing privacy-preserving strategies and design techniques that can be used to facilitate end to end privacy for open data markets. We also highlight some of the major research challenges that need to be address in order to make the vision of open data markets a reality through ensuring the privacy of stakeholders.Comment: Accepted to be published in IEEE Cloud Computing Magazine: Special Issue Cloud Computing and the La

The Emerging Internet of Things Marketplace From an Industrial Perspective: A Survey

The Internet of Things (IoT) is a dynamic global information network consisting of internet-connected objects, such as Radio-frequency identification (RFIDs), sensors, actuators, as well as other instruments and smart appliances that are becoming an integral component of the future internet. Over the last decade, we have seen a large number of the IoT solutions developed by start-ups, small and medium enterprises, large corporations, academic research institutes (such as universities), and private and public research organisations making their way into the market. In this paper, we survey over one hundred IoT smart solutions in the marketplace and examine them closely in order to identify the technologies used, functionalities, and applications. More importantly, we identify the trends, opportunities and open challenges in the industry-based the IoT solutions. Based on the application domain, we classify and discuss these solutions under five different categories: smart wearable, smart home, smart, city, smart environment, and smart enterprise. This survey is intended to serve as a guideline and conceptual framework for future research in the IoT and to motivate and inspire further developments. It also provides a systematic exploration of existing research and suggests a number of potentially significant research directions.Comment: IEEE Transactions on Emerging Topics in Computing 201