AI Powered IoT Security Monitoring System

The rapid growth of Internet of Things (IoT) technology has led to its widespread adoption in critical applications such as smart cold storage systems, healthcare, and industrial automation. However, IoT devices are highly vulnerable to cyberattacks due to limited computational power, insecure communication channels, and lack of intelligent security mechanisms. Traditional rule-based security systems fail to detect advanced attacks such as replay attacks and data injection attacks. This paper proposes an AI-powered IoT security monitoring system designed to detect anomalies and replay attacks in a smart cold storage environment. Sensor data collected using NodeMCU (ESP8266) is transmitted to a Flask-based server where a machine learning model analyzes the data for abnormal behavior. If an anomaly is detected, the system automatically blocks the attacker’s IP address and generates alerts; otherwise, the data is forwarded to the cloud for monitoring using ThingSpeak. Experimental results demonstrate that the proposed system improves real-time security, enhances detection accuracy, and ensures reliable cold storage monitoring