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Forest Fire Detection System

Research Background
Forest fires threaten lives, property, and ecosystems while causing severe air pollution and economic losses. Delayed detection often allows fires to spread rapidly, increasing damage.

Problem Statement and Research Objective
Conventional fire detection relies on manual reporting or delayed monitoring. This study aims to develop a low-cost, IoT-based Forest Fire Detection System that continuously monitors smoke and temperature and provides immediate local and remote alerts.

Materials and Methods Used
The prototype uses smoke and temperature sensors connected to an Arduino Uno R4. When abnormal readings are detected, an LED display provides on-site warnings, while real-time notifications are sent through the Blynk mobile application.

Discussion
The dual-alert mechanism improves response time by combining local warnings with smartphone notifications, enabling earlier intervention.

Conclusions
The system demonstrates potential as a cost-effective, scalable solution for early forest fire detection.

Suggestions
Future work includes solar power integration, weatherproof housing, and expanded sensor networks.