{'fraction_non_alphanumeric': 0.01055662188099808, 'fraction_numerical': 0.0, 'mean_word_length': 5.7727272727272725, '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}}
A MONITORING FRAMEWORK FOR RUNTIME SIMULATION CALIBRATION AND VALIDATION

One of the key problems in building simulation is to determine the accuracy and reliability of a simulation codes and tools. Due to the complexity of buildings, a comprehensive and exhaustive mathematical proof is typically not possible. In this context, comprehensive collection of data from actual buildings can provide an effective basis for probing the degree to which simulation tools can represent and predict the real performance of buildings. Comprehensive building data monitoring not only facilitates the evaluation of the fidelity of simulation tools, but also support the generation of calibrated simulation models, that can be applied in the context of real-time simulation-assisted building systems control. The present contribution describes concepts and initial implementations toward creating and testing a systematic framework for the dynamic and comprehensive building data monitoring for evaluation and calibration of performance simulation models.