@article{4684,
  abstract     = {{Recent years have seen the emergence of physical products that are digitally networked with other products and with information systems to enable complex business scenarios in manufacturing, mobility, or healthcare. These “smart products”, which enable the co-creation of “smart service” that is based on monitoring, optimization, remote control, and autonomous adaptation of products, profoundly transform service systems into what we call “smart service systems”. In a multi-method study that includes conceptual research and qualitative data from in-depth interviews, we conceptualize “smart service” and “smart service systems” based on using smart products as boundary objects that integrate service consumers’ and service providers’ resources and activities. Smart products allow both actors to retrieve and to analyze aggregated field evidence and to adapt service systems based on contextual data. We discuss the implications that the introduction of smart service systems have for foundational concepts of service science and conclude that smart service systems are characterized by technology-mediated, continuous, and routinized interactions.}},
  author       = {{Beverungen, Daniel and Müller, Oliver and Matzner, Martin and Mendling, Jan and vom Brocke, Jan}},
  issn         = {{14228890}},
  journal      = {{Electronic Markets}},
  keywords     = {{Boundary object, Internet of things, Service science, Smart products, Smart service}},
  pages        = {{7--18}},
  publisher    = {{SpringerNature}},
  title        = {{{Conceptualizing smart service systems}}},
  doi          = {{10.1007/s12525-017-0270-5}},
  volume       = {{29}},
  year         = {{2019}},
}

@inproceedings{1156,
  abstract     = {{In this paper, we present an IoT architecture which handles stream sensor data of air pollution. Particle pollution is known as a serious threat to human health. Along with developments in the use of wireless sensors and the IoT, we propose an architecture that flexibly measures and processes stream data collected in real-time by movable and low-cost IoT sensors. Thus, it enables a wide-spread network of wireless sensors that can follow changes in human behavior. Apart from stating reasons for the need of such a development and its requirements, we provide a conceptual design as well as a technological design of such an architecture. The technological design consists of Kaa and Apache Storm which can collect air pollution information in real-time and solve various problems to process data such as missing data and synchronization. This enables us to add a simulation in which we provide issues that might come up when having our architecture in use. Together with these issues, we state r easons for choosing specific modules among candidates. Our architecture combines wireless sensors with the Kaa IoT framework, an Apache Kafka pipeline and an Apache Storm Data Stream Management System among others. We even provide open-government data sets that are freely available.}},
  author       = {{Kersting, Joschka and Geierhos, Michaela and Jung, Hanmin and Kim, Taehong}},
  booktitle    = {{Proceedings of the 2nd International Conference on Internet of Things, Big Data and Security}},
  editor       = {{Ramachandran, Muthu and Méndez Muñoz, Víctor and Kantere, Verena and Wills, Gary and Walters, Robert and Chang, Victor}},
  isbn         = {{978-989-758-245-5}},
  keywords     = {{Wireless Sensor Network, Internet of Things, Stream Data, Air Pollution, DSMS, Real-time Data Processing}},
  location     = {{Porto, Portugal}},
  pages        = {{117--124}},
  publisher    = {{SCITEPRESS}},
  title        = {{{Internet of Things Architecture for Handling Stream Air Pollution Data}}},
  doi          = {{10.5220/0006354801170124}},
  year         = {{2017}},
}