{'fraction_non_alphanumeric': 0.014222222222222223, 'fraction_numerical': 0.0026666666666666666, 'mean_word_length': 5.546511627906977, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
Augmented Reality Supported Modeling of Industrial Systems to Infer Software Configuration

This paper proposes and evaluates an approach for building models of installed industrial Cyber-Physical Systems using augmented reality on smartphones. It proposes a visual language for annotating devices, containers, flows of liquids and networking connections in augmented reality. Compared to related work, it provides a more lightweight and flexible approach for building 3D models of industrial systems. The models are further used to automatically infer software configuration of controllable industrial products. This addresses a common problem of error-prone and time-consuming configuration of industrial systems in the current practice. The proposed approach is evaluated in a study with 16 domain experts. The study participants are involved in creating a model of an industrial system for water treatment. Their comments show that the approach can enable a less error-prone configuration for more complex systems. Opportunities for improvement in usability and reflections on the potential of the approach are discussed.