Internet of Things-Aware Process Modeling: Integrating IoT Devices as Business Process Resources

Meyer, Sonja; Ruppen, Andreas; Magerkurth, Carsten

doi:10.1007/978-3-642-38709-8_6

Cited by 133 publications

(88 citation statements)

References 11 publications

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“…The need to extend BPMN. Existing work already recognize how the existing BPMN standard is insufficient when integrating ubiquitous embedded technology [17], [41], [42]. In our case, BPMN is unable to express many of the concepts required to export meta-and concrete abstractions at the modeling layer, as we explained in the following.…”

Section: The Bpmn Standardmentioning

confidence: 93%

makeSense: Simplifying the Integration of Wireless Sensor Networks into Business Processes

Mottola

Picco

Oppermann³

et al. 2019

IIEEE Trans. Software Eng.

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Abstract-A wide gap exists between the state of the art in developing Wireless Sensor Network (WSN) software and current practices concerning the design, execution, and maintenance of business processes. WSN software is most often developed based on low-level OS abstractions, whereas business process development leverages high-level languages and tools. This state of affairs places WSNs at the fringe of industry. The makeSense system addresses this problem by simplifying the integration of WSNs into business processes. Developers use BPMN models extended with WSN-specific constructs to specify the application behavior across both traditional business process execution environments and the WSN itself, which is to be equipped with application-specific software. We compile these models into a high-level intermediate language-also directly usable by WSN developers-and then into OS-specific deployment-ready binaries. Key to this process is the notion of meta-abstraction, which we define to capture fundamental patterns of interaction with and within the WSN. The concrete realization of meta-abstractions is application-specific; developers tailor the system configuration by selecting concrete abstractions out of the existing codebase or by providing their own. Our evaluation of makeSense shows that i) users perceive our approach as a significant advance over the state of the art, providing evidence of the increased developer productivity when using makeSense; ii) in large-scale simulations, our prototype exhibits an acceptable system overhead and good scaling properties, demonstrating the general applicability of makeSense; and, iii) our prototype-including the complete tool-chain and underlying system support-sustains a real-world deployment where estimates by domain specialists indicate the potential for drastic reductions in the total cost of ownership compared to wired and conventional WSN-based solutions.

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Section: The Bpmn Standardmentioning

confidence: 93%

makeSense: Simplifying the Integration of Wireless Sensor Networks into Business Processes

Mottola

Picco

Oppermann³

et al. 2019

IIEEE Trans. Software Eng.

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“…The IoT management process integrates activities for fault detection and diagnosis. Our work relates to business process improvement (Jalali & Leake, 2013;Meyer, Ruppen, & Magerkurth, 2013;Zhang, Zhou, & Gao, 2006). These works focus on improving a general business process based on different input criteria and process' goals.…”

Section: Related Workmentioning

confidence: 99%

“…By embracing the concept of business management process, the IoT management process has abilities to monitor and control physical or virtual resources when operating IoT devices for cultivating (Meyer et al, 2013).…”

Section: Knowledge For Fault Detectionmentioning

confidence: 99%

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On improving agricultural IoT management process for fault detection

Nguyen

Chiem

Duong

et al. 2017

Journal of Information and Telecommunication

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In recent years, the emerging development of Internet of things (IoT) has created new opportunities for IoT service provider, device manufacturer and customer (end user). In agriculture, employing IoT can help reducing manpower as well as standardizing agricultural processes, thus increasing the benefit for customer who does agricultural business. Beside the opportunities, there are also issues while doing maintenance for an agricultural IoT system. One of them is how to automate the process to detect faults of IoT devices in a large deployment area. While previous studies focus on investigating algorithms as well as theoretical model to detect faults for specific IoT devices, automatically expanding of IoT management process for detecting faults of sensor/actuator has not been investigated yet. To achieve this, we should be able to deal with the relationship between IoT device manufacturer, service provider and customer. In this study, we conceptualize the knowledge of IoT devices, management process and fault detection requirement. To realize this model, we introduce a runtime system to expand the IoT management process for detecting sensor/actuator faults which is able to provide the above features. We do several experiments to show the effectiveness and usefulness of the proposed solution.ARTICLE HISTORY

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“…Kagermann et al 2012), not only the communication among technical IoT devices (e.g., sensors, actuators) and humans became vital to reach organizational goals but also the integration of different organizational levels (i.e., vertical integration of business processes with production planning systems and production control systems) has become an important aspect (cf. Meyer et al 2013;Schüller and Elger 2013;Bassi et al 2013;Kagermann et al 2012). The vertical integration of business processes and technical manufacturing processes targets towards the need of production companies to be able to flexibly change requirements, reconfigure processes, get immediate feedback about the current state of production processes for the management, and to reach information integration between all process levels (Schüller and Elger 2013;Kannengiesser and Müller 2013).…”

Section: Technological Challenges Of Future Production Systemsmentioning

confidence: 99%

Industrial Challenges

Stary

Neubauer

2016

S-BPM in the Production Industry

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Recently, the German "Industry 4.0" initiative gained momentum, and sketches a vision for future production industries. This chapter reviews industrial challenges in the area of "Industry 4.0". The findings are structured along the fundamental understanding of production companies as socio-technical systems. Socio-technical systems consist of three important aspects-(i) human, (ii) organizational structures and technology-and, most importantly their mutual relations, and thus, the interdependencies of these aspects. The review reveals that humans need to remain a vital element of future production and need to drive organizational development efforts and continuous workplace improvement. Organizational structures are challenged by changing business models of production companies. Enabling organizational change requires an open organizational culture (e.g., in terms of digital readiness), learning support and digital literacy of all involved stakeholders. In order to create value from Industry 4.0 developments, still technical challenges, in particular vertical and horizontal process integration need be resolved. IntroductionToday's industry needs to survive in a volatile environment. Changing customer demands, high degree of product individualization, increasing digitalization and system integration, effective and efficient manufacturing operations to meet high quality at low cost, well-being of employees, etc., are just some factors that challenge daily work in industry. In general, an industry refers to the production of certain goods or services within an economy (e.g., automotive industry in Germany). Different Industry classification systems like the ISIC (2008), NAICS (2012) or NACE exist that organize companies with respect to production processes or similar products. (cf. https://en.wikipedia.org/wiki/Industry_classification). According to the NAICS (2012) Manufacturing "comprises establishments primarily engaged in the chemical, mechanical or physical transformation of materials or substances into new products. These products may be finished, in the sense that they are ready to be used or consumed, or semi-finished, in the sense of becoming a raw material for an establishment to use in further manufacturing. Related activities, such as the assembly of the component parts of manufactured goods; the blending of materials; and the finishing of manufactured products by dyeing, heat-treating, plating and similar operations are also treated as manufacturing activities. Manufacturing establishments are known by a variety of trade designations, such as plants, factories or mills". Compared to the definition of manufacturing, the understanding of "Production" is more generic in terms of any conversion from input to output. This also includes intangible products like the delivery of services in areas as government and health care or even knowledge production.In this book, production companies are understood as complex, socio-technical systems of people, processes and machines that flexibly interact within ...

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Internet of Things-Aware Process Modeling: Integrating IoT Devices as Business Process Resources

Cited by 133 publications

References 11 publications

makeSense: Simplifying the Integration of Wireless Sensor Networks into Business Processes

makeSense: Simplifying the Integration of Wireless Sensor Networks into Business Processes

On improving agricultural IoT management process for fault detection

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