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This invention describes a smart system for buildings that uses data from many different sensors, like motion detectors, to figure out what activities are happening. Instead of just reporting what a single sensor sees, it combines information from multiple sensors and remembers past events to infer more complex situations, even if those situations are not directly where a sensor detected something. For example, it could infer someone is cooking in the kitchen based on motion at the door and a temperature change, rather than just reporting motion at the door.
Why it matters: Filed before widespread availability of robust machine learning for contextual inference. The sophisticated reasoning logic and activity inference are now more feasible with modern AI/ML frameworks and cheaper IoT sensors.
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