Introduction to the Minitrack on Software Development for Mobile Devices, the Internet-of-Things, and Cyber-Physical Systems

2023 | HICSS | Citations: 0

Authors: Grønli, Tor-Morten; Kaindl, Hermann; Majchrzak, Tim A.

Abstract: Applications for mobile devices (apps) have facilitated the success of smartpho ... Expand

Abstract: Applications for mobile devices (apps) have facilitated the success of smartphones and tablets. By using apps, the multi-purpose hardware of modern devices can be utilized to the full extent. Despite much progress in development methods, software development kits, and frameworks, app development poses many challenges. This is even more so for novel mobile devices such as wearables and for the hardware that constitutes the Internet-of-Things (IoT) and Cyber-Physical Systems (CPS). Compatibility, performance, battery-saving, and security and safety are only some of the issues that are mainly driven by the quality of the used software. A satisfying level of this quality in many cases is very hard to achieve and proper techniques for testing and formal verification are needed.Experiences and methods from classical software development can only be utilized to some degree. Moreover, the inherent challenges of the respective new devices ask for novel solutions. The challenges sketched above are reinforced by the conditions that development activities meet. Typical particularities include the need for multi-platform development, device fragmentation, context-sensitivity, low computational power, little memory, energy conservation requirements, and the heterogeneity of users. With the emergence of multi-platform and multi-device, the new golden standard are applications not only across software ecosystems, but across hardware platforms such as laptop, mobile, tablets, embedded devices, sensors, and wearables. Therefore, new threads of research are needed to tackle these issues and to pave the way for improved software development, better business producibility and improved user experience (UX). Collapse

Topics: cyber-physical system

Methods: meta analysis

Information Systems Research for Smart Sustainable Mobility: A Framework and Call for Action

2023 | Information Systems Research | Citations: 0

Authors: Ketter, Wolfgang; Schroer, Karsten; Valogianni, Konstantina

Abstract: Transportation is a backbone of modern globalized societies. It also causes appr ... Expand

Abstract: Transportation is a backbone of modern globalized societies. It also causes approximately one third of all European Union and U.S. greenhouse gas emissions, represents a major health hazard for global populations, and poses significant economic costs (e.g., due to traffic congestion). However, rapid innovation in vehicle technology, mobile connectivity, computing hardware, and artificial intelligence–powered information systems heralds a deep socio-technical transformation of the sector. The emergence of connected, autonomous, shared, and electric vehicle technology has created a digital layer that resides on top of the traditional physical mobility system. The resulting layered modular architecture is similar to that seen in other cyber-physical systems. Yet, it also comes with several characteristics and challenges that are unique to the domain of mobility and require entirely new solution approaches. Although other management and domain-specific research disciplines have started to embrace the new opportunities for research resulting from this deep structural change, the information systems (IS) community’s involvement in smart mobility research has been marginal. Yet, we argue that our field’s uniquely multidisciplinary, data-driven, and socio-technical research lens puts it in a strong position to address many of the large-scale societal challenges encountered in the mobility sector. Therefore, we make the case for IS research to play an active role in delivering a smart sustainable mobility ecosystem that is beneficial to users, mobility providers and the environment. We contribute a research framework to direct IS research efforts while providing a shared understanding of the smart sustainable mobility domain. We also present seven IS research opportunities along the dimensions of this framework and propose concrete angles of attack which we hope will spur an impactful and structured research agenda in the area. History: Ahmed Abbasi, Senior Editor; Gautam Pant, Associate Editor. Supplemental Material: The online appendix is available at https://doi.org/10.1287/isre.2022.1167. Collapse

Topics: unintended consequence computer aided software engineering innovation management big data IS economics

Methods: causality analysis survey design science machine learning literature sample

Enterprise Information Systems vs. Digital Twins – A Case Study on the Properties, Purpose, and Future Relationship in the Logistics Sector

2023 | HICSS | Citations: 0

Authors: Lachenmaier, Jens; Weber, Patrick; Lasi, Heiner

Abstract: Traditional enterprise information systems have been around for more than 40 yea ... Expand

Abstract: Traditional enterprise information systems have been around for more than 40 years. They are designed to support business processes and deliver information to the people within a company who require it for their work. However, there are blind spots that these systems are unable to address. In this article, we investigate how digital twins, which are based on the technology and architecture of the Industrial Internet of Things, as well as the principles of cyber-physical systems, can be used to fill such gaps and elucidate how their application will affect the prospective relationship between internal information systems and digital twins. The insights are based on a single case study within the logistics department of an industrial company and its service provider. From the case study, properties of both system types were identified that provided a basis for comparison and stimulated discussion about their future dependencies. Collapse

Topics: enterprise information system digital twin enterprise resource planning cyber-physical system database system

Methods: literature study case study single case study design science longitudinal case study

Survey and Systematization of Prescriptive Analytics Systems: Towards Archetypes from a Human-Machine-Collaboration Perspective

2023 | European Conference On Information Systems | Citations: 0

Authors: Wissuchek, Christopher; Zschech, Patrick

Abstract: Prescriptive analytics systems (PAS) represent the most mature form of business ... Expand

Abstract: Prescriptive analytics systems (PAS) represent the most mature form of business analytics (BA), offering advanced decision support. However, current research predominantly focuses on technical facets while neglecting social-technical design aspects. A pluralist research methodology was employed to address this gap, starting with a systematic literature review of over 200 papers. We used these papers to derive a concept matrix of fundamental elements that guided the development of a taxonomy conceptualizing the interplay and collaboration between humans and machines in PAS-based decision-making processes. Based on this taxonomy, we identified four recurring PAS archetypes with salient design characteristics: Informative, executive, adaptive, and autonomous PAS. Our findings have important implications for the BA community, including the need to investigate design options for executive, adaptive, and autonomous PAS; the underrepresentation of the human perspective; the missing links to the broader organizational landscape; and the potential for interpretable machine learning and reinforcement learning in PAS. Collapse

Topics: decision making mobile system internet of things organizational value explainable artificial intelligence

Methods: literature study structured literature research literature sample survey design principle

Theories: decision theory

Heterogeneous Energy-aware Load Balancing for Industry 4.0 and IoT Environments

2022 | ACM Transactions on Management Information Systems | Citations: 0

Authors: Ahmed, Usman; Lin, Jerry Chun-Wei; Srivastava, Gautam

Abstract: With the improvement of global infrastructure, Cyber-Physical Systems (CPS) have ... Expand

Abstract: With the improvement of global infrastructure, Cyber-Physical Systems (CPS) have become an important component of Industry 4.0. Both the application as well as the machine work together to improve the task of interdependencies. Machine learning methods in CPS require the monitoring of computational algorithms, including adopting optimizations, fine-tuning cyber systems, improving resource utilization, as well as reducing vulnerability and also computation time. By leveraging the tremendous parallelism provided by General-Purpose Graphics Processing Units (GPGPU) as well as OpenCL, it is possible to dramatically reduce the execution time of data-parallel programs. However, when running an application with tiny amounts of data on a GPU, GPU resources are wasted because the program may not be able to fully utilize the GPU cores. This is because there is no mechanism for kernels to share a GPU due to the lack of OS support for GPUs. Optimal device selection is required to reduce the high power of the GPU. In this paper, we propose an energy reduction method for heterogeneous clustering. This study focuses on load balancing; resource-aware processor selection based on machine learning is performed using code features. The proposed method identifies energy-efficient kernel candidates (from the employment pool). Then, it selects a pair of kernel candidates from all possibilities that lead to a reduction in both energy consumption as well as execution time. Experimental results show that the proposed kernel approach reduces execution time by 2.23 times compared to a baseline scheduling system. Experiments have also shown that the execution time is 1.2 times faster than state-of-the-art approaches. Collapse

Topics: production management computer hardware database system internet of things mobile system

Methods: computational algorithm machine learning experiment random forest classification gradient boosting

Introduction to the HICSS-55 Software Development for Mobile Devices, the Internet-of-Things, and Cyber-Physical Systems Minitrack

2022 | HICSS | Citations: 0

Authors: Majchrzak, Tim A; Grønli, Tor-Morten; Kaindl, Hermann; Wien, TU

Abstract: Applications for mobile devices (apps) have facilitated the success of smartpho ... Expand

Abstract: Applications for mobile devices (apps) have facilitated the success of smartphones and tablets. By using apps, the multi-purpose hardware of modern devices can be utilized to the full extent. Despite much progress in development methods, software development kits, and frameworks, app development poses many challenges. This is even more so for novel mobile devices such as wearables and for the hardware that constitutes the Internet-of-Things (IoT) and Cyber-Physical Systems (CPS). Compatibility, performance, battery-saving, and security and safety are only some of the issues that are mainly driven by the quality of the used software. A satisfying level of this quality in many cases is very hard to achieve and proper techniques for testing and formal verification are needed.Experiences and methods from classical software development can only be utilized to some degree. Moreover, the inherent challenges of the respective new devices ask for novel solutions. The challenges sketched above are reinforced by the conditions that development activities meet. Typical particularities include the need for multi-platform development, device fragmentation, context-sensitivity, low computational power, little memory, energy conservation requirements, and the heterogeneity of users. With the emergence of multi-platform and multi-device, the new golden standard are applications not only Collapse

Topics: cyber-physical system

Methods: meta analysis

Computational Intelligence in Security of Digital Twins Big Graphic Data in Cyber-physical Systems of Smart Cities

2022 | ACM Transactions on Management Information Systems | Citations: 0

Authors: Lv, Zhihan; Chen, Dongliang; Feng, Hailin; Singh, Amit Kumar; Wei, Wei; Lv, Haibin

Abstract: This investigation focuses on the application of computational intelligence to t ... Expand

Abstract: This investigation focuses on the application of computational intelligence to the security of Digital Twins (DTs) graphic data of the Cyber-physical System (CPS). The intricate and diverse physical space of CPS in the smart city is mapped in virtual space to construct the DTs CPS in the smart city. Besides, Differential Privacy Frequent Subgraph-Big Multigraph (DPFS-BM) is employed to ensure data privacy security. Moreover, the analysis and prediction model for the DTs big graphic data (BGD) in the CPS is built based on Differential Privacy-AlexNet (DP-AlexNet). Alexnet successfully solves the gradient dispersion problem of the Sigmoid function of deep network structures. Finally, the comparative analysis approach is utilized to verify the performance of the model reported here by comparing it with Long Short-Term Memory, Convolutional Neural Network, Recurrent Neural Network, original AlexNet, and Multi-Layer Perceptron in a simulation experiment. Through the comparison in the root mean square error, the mean absolute error, the mean absolute percentage error, training time, and test time, the model proposed here outperforms other models regarding errors, time delay, and time consumption. In the same environment, the system performs better with multi-hop paths, extra relays, and a high fading index; in that case, the outage probability is minimal. Therefore, the DP-AlexNet model is suitable for processing BGD. Moreover, its speed acceleration is more apparent than that of other models, with a higher SpeedUp indicator. The research effectively combines data mining and data security, which is of significant value for optimizing the privacy protection technology of frequent subgraph mining on a single multi-graph. Besides, the constructed DTs of CPS can provide excellent accuracy and a prominent acceleration effect on the premise of low errors. In addition, the model reported here can provide reference for the intelligent and digital development of smart cities. Collapse

Topics: smart city privacy differential privacy systems development computer hardware

Methods: simulation recurrent neural network computational algorithm experiment deep learning

Augmented Spaces: Introducing a Technology-Supported Home Environment to Improve our Mental Health during “Work from Home” Isolation

2022 | HICSS | Citations: 0

Authors: Revelo V., Laura; Thoring, Katja

Abstract: During the COVID-19 pandemic many restrictions were implemented to prevent the s ... Expand

Abstract: During the COVID-19 pandemic many restrictions were implemented to prevent the spread of the disease. These restrictions included working from home (WFH) and self-isolation. However, this situation had a negative impact on our mental health, causing depression and anxiety in many employees around the world. In this context, we hypothesized that our home spaces could become a catalyst of positive emotions through the use of technology-supported home environments, which use cyber-physical systems to reduce mental health symptoms during the lockdown. We used a qualitative approach, through interviews and cultural probes, to understand the experience of people who were forced to work from home during the lockdown. Additionally, we used a design science approach to explore technology-supported solutions that could enhance our home spaces. The result is a system that mixes analog and digital elements to create interactive rooms, which have a positive impact on people’s well-being. Collapse

Topics: pandemic information system use smart device cyber-physical system mobile system

Methods: experiment qualitative interview literature study cultural probe design artifact

Archetypes of Digital Twins

2022 | Business & Information Systems Engineering | Citations: 1

Authors: van der Valk, Hendrik; Haße, Hendrik; Möller, Frederik; Otto, Boris

Abstract: Currently, Digital Twins receive considerable attention from practitioners and i ... Expand

Abstract: Currently, Digital Twins receive considerable attention from practitioners and in research. A Digital Twin describes a concept that connects physical and virtual objects through a data linkage. However, Digital Twins are highly dependent on their individual use case, which leads to a plethora of Digital Twin configurations. Based on a thorough literature analysis and two interview series with experts from various electrical and mechanical engineering companies, this paper proposes a set of archetypes of Digital Twins for individual use cases. It delimits the Digital Twins from related concepts, e.g., Digital Threads. The paper delivers profound insights into the domain of Digital Twins and, thus, helps the reader to identify the different archetypical patterns. Collapse

Topics: digital twin production management database system data governance knowledge base

Methods: qualitative interview cluster analysis literature study triangulation mixed method

Seven Paradoxes of Business Process Management in a Hyper-Connected World

2021 | Business & Information Systems Engineering | Citations: 0

Authors: Beverungen, Daniel; Buijs, Joos C. A. M.; Becker, Jörg; Di Ciccio, Claudio; van der Aalst, Wil M. P.; Bartelheimer, Christian; vom Brocke, Jan; Comuzzi, Marco; Kraume, Karsten; Leopold, Henrik; Matzner, Martin; Mendling, Jan; Ogonek, Nadine; Post, Till; Resinas, Manuel; Revoredo, Kate; del-Río-Ortega, Adela; La Rosa, Marcello; Santoro, Flávia Maria; Solti, Andreas; Song, Minseok; Stein, Armin; Stierle, Matthias; Wolf, Verena

Abstract: Business Process Management is a boundary-spanning discipline that aligns operat ... Expand

Abstract: Business Process Management is a boundary-spanning discipline that aligns operational capabilities and technology to design and manage business processes. The Digital Transformation has enabled human actors, information systems, and smart products to interact with each other via multiple digital channels. The emergence of this hyper-connected world greatly leverages the prospects of business processes – but also boosts their complexity to a new level. We need to discuss how the BPM discipline can find new ways for identifying, analyzing, designing, implementing, executing, and monitoring business processes. In this research note, selected transformative trends are explored and their impact on current theories and IT artifacts in the BPM discipline is discussed to stimulate transformative thinking and prospective research in this field. Collapse

Topics: business process management social media smart device big data digital transformation

Methods: design artifact longitudinal research