Madhya Pradesh Introduced India’s First AI-Powered Real-Time Forest Alert System

Madhya Pradesh has taken a significant leap towards forest conservation with the launch of India’s first AI-based real-time forest alert system. This system uses satellite data, AI, and mobile-based field reporting to detect land encroachment, deforestation, and other changes in forest areas. The initiative is being piloted in five forest divisions and is poised to become a model for effective forest management in India.

Why in the News?

Madhya Pradesh has launched India’s first AI-based real-time forest alert system, a groundbreaking initiative aimed at enhancing forest conservation efforts. By leveraging advanced technologies like satellite imagery, mobile feedback, and artificial intelligence (AI), this system promises to strengthen forest monitoring and improve responses to land encroachment and forest degradation.

Aim of the System

• Proactive Monitoring: The system aims to detect changes in land use, deforestation, and encroachment, facilitating immediate corrective actions.
• Real-Time Alerts: Alerts are generated from satellite images and sent to field staff for immediate verification and action.

Significance of the Initiative

• First of Its Kind: Madhya Pradesh is the first state to integrate AI and satellite data for forest monitoring, setting a precedent for other states.
• Efficiency: The use of real-time data allows forest officers to act swiftly to address issues like illegal logging and land encroachment.
• Sustainability: By identifying and responding to environmental changes faster, the system contributes to better conservation and sustainable forest management.

Background

• The project is a response to frequent issues like illegal logging and land encroachment in forest-rich areas of Madhya Pradesh.
• The system uses satellite imagery from the Google Earth Engine and AI algorithms to track land use changes like vegetation shifts, construction, or agricultural encroachment.

Key Facts

• Pilot Project: The system is currently being tested in five sensitive forest divisions: Shivpuri, Guna, Vidisha, Burhanpur, and Khandwa.
• AI Integration: Machine learning models continuously improve the accuracy of alerts and predictions based on field data.
• Data Features: Each alert includes over 20 data points, including GPS-tagged photos, voice notes, and survey comments from mobile apps.