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This invention describes a home monitoring system that uses a camera to learn a person's typical routine before they leave the house. By analyzing past videos, it identifies the usual timing of their actions. If a new video shows the person performing an action out of sync with their established routine, the system sends them an alert. The system specifically determines timing using methods like cluster analysis or by evaluating action frequency, significance, and pattern strength.
Why it matters: Since 2019, advancements in machine learning and computer vision, particularly convolutional networks, have made real-time video analysis and routine anomaly detection more accurate and computationally efficient. This could simplify the development of the core pattern recognition and timing determination.
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