This is the data set of IoT data from the Fischertechnik Smart Factory Model deployed at the Institute of Computer Science at the University of St.Gallen. It is used as basis for the interactive identification of process activity executions from the IoT data. The corresponding publication can be found here: Seiger, R., Franceschetti, M., & Weber, B. (2023). An Interactive Method for Detection of Process Activity Executions from IoT Data. Future Internet, 15(2), 77. https://doi.org/10.3390/fi15020077 The data set contains: cps_log.txt: A file of all sensor and actuator readings (in JSON format) from the smart factory during the execution of 3 instances of the storage process and 3 instances of the production process. For visualization, it can be fed line-by-line into an Influx database and Grafana can then be used to create visualizations of the data. wfms_log.txt: A file containing the corresponding event log (in JSON format) recorded and extracted from the Camunda Platform workflow management system during the execution of the process instances. For visualization, it can be fed line-by-line into an Influx database and Grafana can then be used to create visualizations of the data. storage_process.bpmn: Executable BPMN 2.0 model of the storage process executed in the smart factory model. production_process.bpmn: Executable BPMN 2.0 model of the storage process executed in the smart factory model. More details on the systems architecture used to execute the processes and record the data from the smart factory can be found in the follow publication: Ronny Seiger, Lukas Malburg, Barbara Weber, Ralph Bergmann, Integrating process management and event processing in smart factories: A systems architecture and use cases, Journal of Manufacturing Systems, Volume 63, 2022, Pages 575-592, ISSN 0278-6125, https://doi.org/10.1016/j.jmsy.2022.05.012