This invention describes a system that identifies specific real-world events by combining information from different sensors. It works by collecting data from various sensors, like motion or sound detectors, and then checking if that combined data matches any of its stored event patterns. If the sensor readings, their timing, and locations fit a particular pattern, the system recognizes that event and sends out a notification.
Why it matters: Filed before widespread accessible AI tools could easily learn complex event patterns from diverse sensor data. Modern machine learning can now automate the creation and refinement of these 'event profiles' and 'conditions' more effectively, reducing the need for manual rule definition.
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