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What is Machine Learning Anomaly Detection in IoT Plant Walls about?

This study explores the application of machine learning for anomaly detection in IoT-based vertical plant wall systems aimed at enhancing indoor climate control. It investigates both point and contextual anomalies, demonstrating that neural network models, particularly autoencoders and LSTM encoders, are effective for detecting these anomalies. The research proposes a new data cleaning method and a cloud-based proof-of-concept for real-time anomaly detection, showcasing the integration of IoT and machine le

Author

Laode Ansyarullah

Language

EN