AI/ML-Based Intelligent Anomaly Detection for Automatic Weather Stations (AWS)

Expected Solution

• Title SkyGuard AI: Intelligent Real-Time Anomaly Detection System for Temperature, Pressure, and Humidity Sensors in Automatic Weather Stations • Background Automatic Weather Stations (AWS) are critical components of modern meteorological observation networks. These stations continuously monitor atmospheric parameters and provide real-time data for weather forecasting, climate monitoring, disaster management, aviation, agriculture, and scientific research.However, AWS observations often contain anomalies caused by sensor malfunction,communication failures, calibration drift, power fluctuations, harsh environmental conditions, and data corruption.Erroneous observations can significantly effect weather forecasting accuracy and decision-making systems. Traditional threshold-based quality co

• Grand Challenge Can AI build a self-aware and self-healing weather observation network that can delivering trustworthy atmospheric data under all environmental conditions?
• Output: Fully executable code with example usage and a document explaining various use cases