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Auflistung nach Schlagwort "Sensor Data"

1 - 4 von 4
  • Conference Paper 
    Code of Practice for Sensor-Based Learning
    (DELFI 2019, 2019) Yun, Haeseon; Riazy, Shirin; Fortenbacher, Albrecht; Simbeck, Katharina
    Sensor-based learning refers to utilizing physiological sensor data from learners and information from a learning environment to promote learning. Sensor data enclose learner’s personal information so ethical practice of adopting sensor data in learning analytics needs to be explored thoroughly. In this positional paper, we examine current ethical practices in learning analytics to derive a code of practice for sensor-based learning. Furthermore, we critically validate a wearable sensor device developed as a learning support against the derived code of practice.
  • Konferenzbeitrag
    Synthesizing of Process-Aware Digital Twin Cockpits from Event Logs
    (Software Engineering 2023, 2023) Bano, Dorina; Michael, Judith; Rumpe, Bernhard; Varga, Simon; Weske, Mathias
    In this work, we summarize our article “Process-Aware Digital Twin Cockpit Synthesis from Event Logs” published in the Journal of Computer Languages (COLA). The engineering of digital twins and their user interfaces with explicated processes, namely process-aware digital twin cockpits (PADTCs), is challenging due to the complexity of the systems and the need for information from different disciplines within the engineering process. Therefore, we have investigated how to facilitate their engineering by using already existing data, namely event logs. We present a low-code development approach that reduces the amount of hand-written code needed to derive PADTCs using process mining techniques. We describe what models could be derived from event log data, which generative steps are needed for the engineering of PADTCs, and how process mining could be incorporated into the resulting application. A PADTC prototype is created based on the MIMIC III dataset, which simulates an automated hospital transportation system. Initially, our approach requires no hand-written code and empowers the domain expert to iteratively create PADTC prototypes.
  • Konferenzbeitrag
    Understanding and addressing user needs for annotation of simple sensor data: Bridging the gap between human sensemaking and machine interpretation
    (INFORMATIK 2024, 2024) Kurze, Albrecht; Reuter, Christin
    The increasing presence of sensors in smart homes generates vast amounts of data, which require effective interpretation to be useful, often along with data annotation. While automatic approaches can automatically analyze sensor data but require strict and clean annotations, they often neglect the complex, multidimensional nature of human sensemaking. We explore this gap and propose an approach to bridge this gap. We present preliminary findings from three directions: lay user annotations of sensor data collected in a field study using our Sensorkit solution, analysis of existing annotation tools, and a human-centered design process for a new annotation solution. Our goal is to develop a more integrated approach to sensor data interpretation that benefits both humans and machines.
  • Textdokument
    Using Sensor Data of Widespread Smart Home Devices to Save Energy in Private Homes
    (INFORMATIK 2017, 2017) Muth, Peter
    This paper proposes an approach for using sensor data of smart home devices to optimize energy consumption in private homes. For many years, radiator thermostats have been used to keep room temperatures at given desired levels. Smart home thermostats allow the temperature to be controlled by home automation software, advanced models are connected to sensors indicating open windows or sun shining into the room. In contrast to these advances, basic optimizations of the heating system like performing hydraulic balancing or minimizing flow temperature are rarely performed by the plumbers, because the optimization process is time consuming and requires data that are not available at installation time. In this paper, we describe how data delivered by smart home devices can be used to optimize the heating system. Using our approach, hydraulic balancing and minimizing flow temperature can be easily performed by the house owner without the help of a plumber, resulting in substantial energy savings.