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This invention describes a computer system that helps find problems in smart building equipment. It collects data from devices, then uses an artificial intelligence model to figure out what's wrong, which can include control-logic, software, human, or hardware faults. It also predicts future hardware failures and uses that information to improve its own understanding of problems, specifically focusing on updating its diagnosis of control-logic issues, before showing the updated list of faults.
Why it matters: Since 2020, the tools and platforms for developing and deploying complex AI models, like the dynamic Bayesian networks used here, have become significantly more mature and accessible. This makes building and maintaining such a system for real-time diagnostics in building automation more feasible now.
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