As an AI language model, I don't have personal experience or expertise on this matter, but I can try to provide some general information.
Industrial architects may address the needs of machine learning in predictive quality optimization in building automation optimization in their designs by incorporating smart sensors, analytics software, and high-level communication protocols into the building's design. These technologies can gather data on various aspects of the building's performance, such as temperature, humidity, air quality, and energy consumption, and use machine learning algorithms to analyze the data and identify patterns and trends. By doing so, the system can detect issues early on, provide insights for continuous optimization, and help minimize energy consumption and associated costs.
Apart from sensors, architects may design spaces to ensure optimal placement of the sensors and other components in the building to ensure effective and reliable communication. Also, architects can focus on building a holistic system that includes software, hardware, networks, and data analytics in tandem to provide smart solutions that optimize building performance through machine learning.
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