Table 1 Data from different sensors.

From: Enhancing anomaly detection in IoT-driven factories using Logistic Boosting, Random Forest, and SVM: A comparative machine learning approach

Feature

Description

Ambient temperature

Records the temperature reading from a thermostat within factories and companies

Light intensity

Captures the intensity of light from a sensor

Motion detection

Identifies the presence or absence of motion within factory

Window status

Indicates the state of a window (open or closed)

Door status

Reflects the condition of a door (open or closed)

Power consumption

Measures the power usage from a device within factories and companies

Anomaly

Indicates the presence or absence of irregularities within the factories and companies’system