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Netci Hesvindrati

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Open access Aug 2026

Multi-Sensor IoT Smart Home Anomaly Detection Using Random Forest Algorithm

The experimental results achieved an accuracy of 96.75%, precision of 94.65%, recall of 93.82%, and F1-score of 94.23%, demonstrating that Random Forest is effective for identifying anomalous conditions in smart home IoT environments.

Juarisman, Kamarudin, Netci Hesvindrati · 0 citations

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