Virtual Sensors
Dominik Martin, Niklas Kühl, Gerhard Satzger · Business & Information Systems Engineering · 2021
Information systems increasingly link to the physical world. Technological advancements and declining unit costs of sensor technology combined with increased connectivity drive the spread and complexity of the Internet of Things (IoT) (Wortmann and Flüchter 2015 ) or so-called cyber-physical systems (Lasi et al. 2014 ; Lin et al. 2017 ). Today, billions of sensors feed information systems (IS) with data describing physical phenomena – such as temperature, pressure, humidity, velocity, chemical components, or material composition – across many areas ranging from industrial applications (e.g., smart factories) to consumer applications (e.g., smart watches). They form a key foundation for AI-based information systems that apply machine learning and generate analytics-based solutions. In particular, sensor data represents an essential building block of digital twins as an important phenomenon of interest for the BISE community (van der Aalst et al. 2018 ). As digital duplicates of real assets in the physical world, they rely on sensor technology for continuous data acquisition: As an example, the digital representation of a production plant (captured via physical or virtual sensors) may be used to optimize the production process by means of simulation or to develop predictive maintenance services (Tao et al. 2019 ). The increasing importance of sensors and IoT-based data for IS is also evident from the rapidly growing number of articles in academic IS journals dealing with ‘sensors’, which has increased more than tenfold within the last two decades. Footnote 1