Enhanced IoT-Based Environmental Monitoring System Using MQTT with Real-Time Alerts and Predictive Analytics

We present an IoT environmental monitoring system that  uses three innovative features to improve traditional methods: ESP32-based sensor nodes with DHT22 sensors (30-second sampling,  ±0.5°C/±2% RH accuracy, JSON payloads), real-time alerting via MQTT (QoS 1 +  TLS) and Node-RED (SMS/email in <5s), and predictive analytics using linear regression  (85% accuracy for >2°C/5% RH trends). The Raspberry Pi-based system with Mosquito broker demonstrates 99.8% message reliability and 99.2% uptime during 30-days tests across residential place. Our solution costs less than $50 per node while using open-source tools (InfluxDB/SQLite) to achieve incident response time reduction from hours to seconds and risk forecasting accuracy of 20-40 minutes ahead of existing passive monitoring systems.