  This research introduces an innovative forest monitoring system designed to
detect and mitigate the threats of forest fires. The proposed system leverages
Arduino-based technology integrated with state-of-the-art sensors, including
DHT11 for temperature and humidity detection and Flame sensor along with GSM
module for gas and smoke detection. The integration of these sensors enables
real-time data acquisition and analysis, providing a comprehensive and accurate
assessment of environmental conditions within the forest ecosystem. The Arduino
platform serves as the central processing unit, orchestrating the communication
and synchronization of the sensor data. The DHT11 sensor monitors ambient
temperature and humidity levels, crucial indicators for assessing fire risk and
identifying potential deforestation activities. Simultaneously, the Flame
sensor module detects the occurrence of fire flames nearby thus indicating it
by a buzzer. The collected data is processed through an intelligent algorithm
that employs machine learning techniques to discern patterns indicative of
potential threats. The system is equipped with an adaptive threshold mechanism,
allowing it to dynamically adjust to changing environmental conditions. In the
event of abnormal readings or anomalies, the system triggers immediate alerts,
notifying forest rangers and relevant authorities to facilitate timely response
and intervention. The integration of low-cost, easily deployable Arduino-based
devices makes this solution scalable and accessible for implementation across
diverse forest environments. The proposed system represents a significant step
towards leveraging technology to address environmental challenges and protect
our forests.
