Project URL: https://github.com/newToCodng/AnomalyDetector.git

TECH STACK: Python, NumPy, Pandas, Mathplotlib, ScyPy(Z-score)

This project simulates fibre-optic sensor data to identify anomalies that could indicate sensor failure. By generating random data using Numpy, injecting random anomalies, and applying Z-score analysis, we can tag irregularities and visualise them.

Features:

• Generate simulated sensor data
• Inject anomalies (failures/spikes) to mimic real-world errors
• Uses Z-score analysis to detect outliers
• Visual Insights with 2 Interactive plots
• Customisable threshold