This dataset contains multimodal sensor data collected from side-channels while printing several types of objects on an Ultimaker 3 3D printer. Our related research paper titled "Sabotage Attack Detection for Additive Manufacturing Systems" can be found here: https://doi.org/10.1109/ACCESS.2020.2971947. In our work, we demonstrate that this sensor data can be used with machine learning algorithms to detect sabotage attacks on the 3D printer.

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The dataset corresponds the measurement that was implemented on the control accuracy of a mixed reality application for digital twin based crane. 

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This dataset contains requests execution times for comparison of direct requests and requests via API gateway to test API.

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The Here East Digital Twin was a six month trial of a real-time 3D data visualisation platform, designed for the purpose of supporting operational management in the built environment. 

Instructions: 

1. View the project video for context: https://vimeo.com/311089492

2. Review details of the Envirosensor implementation: https://github.com/virtualarchitectures/ICRI_Envirosensor

3. One option for analysing the data is using Spark and Python in a Jupyter Notebook as outlined in the following example GitHub repository: https://github.com/virtualarchitectures/ICRI_Envirosensor_Data_Analysis

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