AI-Based Smart Forest Safety Monitoring System Using Real-Time Risk Analysis

Abstract: Forest tourism has seen a steady rise in recent years, as more people are drawn to outdoor adventures and nature-based experiences. Despite its popularity, ensuring the safety of tourists in remote and unpredictable forest environments continues to be a major concern. This paper presents a smart forest safety monitoring system that utilizes artificial intelligence to improve user safety through continuous tracking and intelligent risk assessment.

The proposed system integrates GPS-based location tracking with real-time risk evaluation and behavior analysis to provide timely alerts and guidance. It features a user registration module that collects essential personal and medical information, allowing the system to deliver more personalized safety support. In addition, the system is capable of detecting unusual situations, such as extended periods of inactivity or entry into high-risk zones, by analyzing sensor data and location patterns.

During emergency situations, the system can automatically trigger alerts and record short video clips, which can assist in verification and rescue efforts. The system is implemented using modern web technologies, supported by a Flask-based backend for efficient data handling and processing. The results demonstrate that the proposed solution can effectively identify potential risks and respond in a timely manner, making it a practical and reliable approach for enhancing tourist safety in forest environments.

Keywords: Artificial Intelligence (AI), Forest Tourist Safety, Real-Time Risk Assessment, GPS-Based Tracking Systems, Emergency Detection and Response