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METHOD AND SYSTEM FOR PREDICTION OF CORRECT DISCRETE SENSOR DATA BASED ON TEMPORAL UNCERTAINTY
METHOD AND SYSTEM FOR PREDICTION OF CORRECT DISCRETE SENSOR DATA BASED ON TEMPORAL UNCERTAINTY
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机译：基于时间不确定性的准确离散传感器数据预测方法和系统
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摘要
This disclosure relates generally to a method and system for prediction of correct discrete sensor data, thus enabling continuous flow of data even when a discrete sensor fails. The activities of humans/subjects, housed in a smart environment is continuously monitored by plurality of non-intrusive discrete sensors embedded in living infrastructure. The collected discrete sensor data is usually sparse and largely unbalanced, wherein most of the discrete sensor data is ‘No’ and comparatively only a few samples of ‘Yes’, hence making prediction very challenging. The proposed prediction techniques based on introduction of temporal uncertainty is performed in several stages which includes pre-processing of received discrete sensor data, introduction of temporal uncertainty techniques followed by prediction based on neural network techniques of learning pattern using historical data.
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