Anomaly detection in sensor systems using lightweight machine learning

Keyphrases

• Sensor Systems 100%
• Recursive Least Squares 100%
• Anomaly Detection 100%
• Tiny Machine Learning 100%
• Prediction Accuracy 50%
• Mote 50%
• LS Method 50%
• Sensor Data 50%
• Linear Least Squares Estimation 50%
• Detection Performance 25%
• Limited Resources 25%
• Data Anomalies 25%
• Embedded Systems 25%
• Sensor Readings 25%
• Rule-based Method 25%
• Long-lived 25%
• Adaptive Thresholding 25%
• Wireless Sensor Networks 25%
• Detecting Anomalies 25%
• Accuracy Performance 25%
• Embedded Devices 25%
• Floating-point 25%

Computer Science

• Machine Learning 100%
• Anomaly Detection 100%
• recursive least square 100%
• Least Squares Methods 50%
• Prediction Accuracy 50%
• Fixed Points 50%
• Large Data Set 25%
• Floating Point 25%
• Detect Anomaly 25%
• Embedded Systems 25%
• Embedded Device 25%
• Detection Performance 25%
• Experimental Result 25%

Engineering

• Anomaly Detection 100%
• Sensor System 100%
• Least Square 100%
• Recursive 66%
• Sensor Data 33%
• Fixed Points 33%
• Energy Engineering 16%
• Experimental Result 16%
• Limited Resource 16%
• Detection Performance 16%
• Model Parameter 16%
• Comparable Result 16%
• Embedded Device 16%
• Wireless Sensor Network 16%
• Sensor Reading 16%
• Floating Point 16%